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Kildare County Council

Traffic Modelling Report

Maynooth Strategic Traffic Model

Issue Date: 31-01-2017

Document Control

Prepared By: Conor de Courcy AECOM

Checked By: Jonathan Hennessy AECOM

Approved By: AECOM

Revision History

Revision Date Comments

1 31-01-2017 Work In Progress

AECOM Maynooth Traffic Management Plan and Traffic Model

Kildare County Council Traffic Modelling Report

Page 1

Maynooth Strategic Traffic Model

Traffic Modelling Report

TABLE OF CONTENTS

1. Introduction ................................................................................................................. 4

1.1 Overview ....................................................................................................................... 4

1.2 Project Background ....................................................................................................... 4

2 Data Collection ............................................................................................................ 7

2.1 Introduction ................................................................................................................... 7

2.2 National Transport Model .............................................................................................. 7

2.3 National Traffic Model ................................................................................................... 8

2.4 Traffic Surveys .............................................................................................................. 8

2.5 GeoDirectory Data ...................................................................................................... 25

3 Model Development .................................................................................................. 28

3.1 Overview ..................................................................................................................... 28

3.2 Definition of Model Study Area .................................................................................... 28

3.3 Network Development ................................................................................................. 29

3.4 Matrix Development .................................................................................................... 35

3.5 Assignment Model ...................................................................................................... 35

3.6 Estimation of Annual Average Daily Traffic (AADT) ..................................................... 36

4 Model Calibration & Validation ................................................................................ 38

4.1 Introduction ................................................................................................................. 38

4.2 Calibration................................................................................................................... 38

4.3 Model Validation ......................................................................................................... 41

4.4 Comparison of Traffic Patterns .................................................................................... 44

4.5 Model Convergence .................................................................................................... 47

5 Future Year Model Development.............................................................................. 49

5.1 Introduction ................................................................................................................. 49

5.2 Future Year Matrix Development ................................................................................ 49

5.2.1 Overview ..................................................................................................................... 49

5.3 Maynooth Area Future Development........................................................................... 49

5.4 Future Land Use Projections & Associated Traffic Generation .................................... 52

5.5 Allocation & Distribution of Future Growth ................................................................... 55

5.6 Comparison of KCC Forecast to ERM and NTM ......................................................... 55

5.7 Future Year Matrix Analysis ........................................................................................ 57

6 Future Year Scenario Assessment .......................................................................... 62

6.1 Maynooth LAP Roads Objectives ................................................................................ 62

6.2 Future Year Scenarios Assessed ................................................................................ 65



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6.3 Do-Minimum Network ................................................................................................. 65

6.4 Do Something Networks ............................................................................................. 65

6.5 Results ........................................................................................................................ 69

7 Conclusion ................................................................................................................ 81

7.1 Conclusion .................................................................................................................. 81

Appendix A – Traffic Surveys

Appendix B – Model Calibration

Appendix C – Model Validation

Appendix D – Future Year Forecasting & Demand Allocation - Technical Note 1



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Chapter 1

Introduction



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1. Introduction

1.1 Overview

This Traffic Modelling Report (TMR) outlines the development, calibration/validation and traffic

forecasting process for a strategic local area traffic model of Maynooth. The traffic model has

been developed as part of the Maynooth Traffic Management Plan and Traffic Model project on

being undertaken by AECOM on behalf of Kildare County Council (KCC). The model will be used

to test the impacts of future traffic management proposals, highway network interventions and

land use proposals in the Maynooth area. The traffic model study area for the proposed scheme

is illustrated in Figure 1.1 below.

The strategic traffic model has been developed in accordance with Transport Infrastructure

Irelands’ (TII’s) Project Appraisal Guidelines (PAG) 2016. These guidelines are in compliance

with the Department of Transport, Tourism and Sports’ Common Appraisal Framework for

Transport Projects and Programmes (2016).

Figure 1.1 – Maynooth Traffic Model Study Area

1.2 Project Background

Maynooth is defined in the Regional Planning Guidelines (RPG’s) for the Greater Dublin Area

(GDA), 2010-2022, as a Large Growth Town II. As a Large Growth Town, Maynooth is an

important self-sustaining regional economic driver, accommodating significant investment in

transport, housing, economic and commercial activity with high-quality transport links to Dublin

and other towns.

Maynooth also functions as a vibrant college town with a growing population, an expanding

university complex and potential new commercial and science/technology offerings. Within



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Maynooth there are new residential developments under construction and a number of potential

developments are currently in the early planning process.

The current transport network and traffic management arrangements can result in significant

delays and congestion, particularly along the R406, Moyglare Road and R148. The majority of

the north-south and east-west traffic has to travel through the Main Street /Straffan Road junction

or the Mill Street / Leinster St /Main St junction. These junctions are currently operating at

capacity and have major impact on congestion within the town. This traffic congestion causes a

reduction in the quality of life for people living in and visiting Maynooth.

The Maynooth Local Area Plan 2013 to 2019 contains a number of new road links that will

provide alternative routes to the existing arrangement and provide much needed relief to the

main links within the town. The provision of these new links will provide further opportunity for

improvements to the public realm and to the pedestrian/cyclists network.

Resources for the delivery of these new links are however limited and some of the infrastructure

will need to be delivered in conjunction with other commercial developments. As a consequence

there is a need to understand the benefits that these new links may provide so that their delivery

can be prioritised and any investments appropriately focused. The Maynooth Traffic

Management Plan will provide KCC with plan led approach to future traffic management that

assists in the fulfilment of the Maynooth Local Area Plan 2013 to 2019 objectives. The Plan, with

clear recommendations for the management of traffic within Maynooth, will provide KCC with

important information in relation to transport within Maynooth, including the following:

Traffic Management Plans for local schools.

Details on potential relief provided by new link roads and streets.

Cross-sectional and junction requirements for new link roads.

Preliminary layouts for future improvements, such as Main Street and its associated junctions.

Options for future traffic management of Maynooth.

Options for traffic management and circulation within the core town centre.

The Maynooth Strategic Traffic Model (STM) will allow KCC to investigate the impact and

opportunities presented by the provision of new link roads and other infrastructure improvements.

It will provide the means to assess the impact of major traffic management changes on the

overall road network and will be a useful tool in assessing the impact of future developments on

the transport network. The results from the traffic model will help to provide a strategic overview

of existing and future traffic conditions within Maynooth.



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Chapter 2 Data Collection



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2 Data Collection

2.1 Introduction

In order to develop a traffic model, a significant level of traffic data is required to ensure that the

model can replicate existing traffic patterns and volumes. This section of the TMR describes the

collation of data for the construction of the Base Year (2016) Maynooth STM.

2.2 National Transport Model

The starting point for the development of the Base Year STM was the 2015 Base Year National

Transport Model1 (NTpM), which was developed by Transport Infrastructure Ireland (TII). The

NTpM is a strategic multi-modal variable demand model used by TII to assess the impact of

infrastructure or policy changes at National, Regional and local level. Within the NTpM there are

four modules, which are as follows:

National Traffic Model (NTM);

National Rail Model (NRM);

National Bus Model (NBM); and

Variable Demand Model (VDM)

The three assignment models (NTM, NRM & NBM) are used to assign the demand for travel

represented by the demand matrices to the network, generating travel costs (e.g. time, distance,

tolls, fares) for each mode. A brief overview of the Variable Demand Model is provided in the

following section.

2.2.1 Variable Demand Modelling

The role of the Variable Demand Model (VDM) is to assess, if required, the impact of a change in

the transport network or change in the cost of travel (e.g. fuel costs, fares) upon the demand for

travel (mode switching, induced demand etc.). Table 5.2.1 of PAG Unit 5.2: Construction of

Transport Models provides guidance on when variable demand modelling is required.

The VDM operates at a national level as it requires the full cost of a trip between an origin and

destination; therefore any assessment of potential demand responses arising from strategic

highway network investments in Maynooth should be undertaken with the NTpM and not the

Maynooth STM. However, any demand responses identified as a result of the proposed schemes

can be incorporated into the STM using demand matrix adjustment techniques.

1 TII National Transport Model documentation - http://www.tii.ie/tii-library/strategic-planning/

http://www.tii.ie/tii-library/strategic-planning/



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2.3 National Traffic Model

The NTM is a strategic (macroscopic) traffic model developed using the transportation modelling

software VISUM and forms the highway element of the NTpM as outlined above. The model

covers the entire national and regional road network and is used by TII as a tool in the appraisal

of potential road schemes and land-use and policy changes. The NTM provides demand data for

Light Vehicles (Car & Light Goods Vehicles) and Heavy Vehicles (Other Goods Vehicle 1, Other

Goods Vehicle 2 and Buses/Coaches) for the following time periods:

Average AM Peak Hour (average hour between 07:00 – 09:00); and

Average Inter Peak Hour (average hour between 12:00 – 14:00).

The model provided both the initial highway network and demand matrices for the Maynooth

STM. The NTM is high level strategic traffic model and though it is suitably refined to test impacts

on a national scale it is not detailed enough to assess local impacts on the network.

2.4 Traffic Surveys

A summary of the traffic survey data that was collated to inform the development of the Base

Year (2016) STM is outlined in Table 2.1 below. Figures 2.1 to 2.4 illustrate the location of the

traffic surveys.

Table 2.1 - Traffic Survey Data

Survey Type Description

Origin – Destination (OD)

Automatic Number Plate Recognition (ANPR) surveys were carried out at 21 sites on Thursday the 19

th May 2016 from 07:00 to 19:00.

In addition to the ANPR surveys Automatic Traffic Counts (ATC) surveys were carried out at the 21 ANPR sites 24 hours a day over a two week period from Tuesday the 17

th to Monday the 30

th May

2016.

Traffic Counts

Automatic Traffic Counts (ATC) surveys were carried out at an

additional 6 sites in the Town Centre 24 hours a day over the two

week period from Tuesday the 17th to Monday the 30

th May 2016.

Junction Turning Movement Count (JTC) surveys were carried out

at 31 locations from 07:00 to 19:00 on Tuesday the 17th May 2016

and Thursday the 19th May 2016.

Traffic data from 2 permanent Transport Infrastructure Ireland (TII)

Traffic Monitoring Units (TMU) local to the Maynooth area.

Journey Time

Journey time survey data was collected as part of the ANPR

surveys.



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Figure 2.1 – Overview of ANPR & ATC Survey Locations

Figure 2.2 - Overview of Additional ATC Survey Locations



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Figure 2.3 - Overview of JTC Survey Locations

Figure 2.4 – TII Traffic Monitoring Units within the Study Area



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2.4.1 Automatic Traffic Counts

An Automated Traffic Count (ATC) captures the traffic flow passing a given point on a road and

classifies the flow into different vehicle classifications, such as Cars, Light Goods Vehicles (LGV)

and Heavy Goods Vehicles (HGV). Traffic flow data, extracted from the ATC survey sites (21

ATC survey sites indicated in Figure 2.1 and the 6 additional ATC survey sites indicated in Figure

2.2) undertaken over the two week period from Tuesday the 17th to Monday the 30th May 2016,

is presented in Table 2.2 below for the following time periods:

AM Peak (08:00 – 09:00); and

PM Peak (17:00 – 18:00).

Table 2.2 also provides annual average estimates of both weekday (Mon – Fri) and 7 day traffic

flow based on the ATC Surveys. The following estimates are presented:

2016 Annual Average Weekday Traffic (AAWT); and

2016 Annual Average Daily Traffic (AADT).

It should be noted that a seasonality factor of 0.97 for the month of May has been applied to the

collected data in line with guidance provided in TII PAG Unit 16.2: Expansion Factors for Short

Period Traffic Counts. A graphical summary of the peak hour AAWT and AADT information

presented in Table 2.2 & 2.3 below is shown in Figure 2.5 and Figure 2.6.



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Table 2.2 - Automatic Traffic Counter Data 2 Way Flow (2016)

Site Location Vehicles per Hour Vehicles per Day

AM PM AAWT AADT

Site A R406, south of M4 Interchange 1,305 1,340 16,031 15,365

Site B R405, north of M4 Overbridge 429 471 5,712 5,757

Site C R406, north of M4 Interchange 1,376 1,237 17,502 16,609

Site D Straffan Wood 607 656 7,067 6,593

Site E R405, east of R406 Junction 613 466 6,319 5,858

Site F R408, south of Ashley Grove 344 367 3,930 3,684

Site G R408 west of Junction with

Meadowbrook Lawns 286 356 4,107 3,713

Site H R406, north of Junction with R405 1,333 1,480 20,464 19,676

Site I R148, east of Maynooth 729 856 9,890 9,296

Site J R148 each of Junction with R157

south of JTC Site 20 414 477 5,868 5,555

Site K R406 north of Railway Junction 1,228 1,314 18,236 15,732

Site L R148, north of Pound Lane 1,148 1,103 16,110 15,332

Site M R148, west of NUIM entrance 633 571 7,368 6,972

Site N R148 east of NUIM entrance 608 619 9,097 8,643

Site O R148, west of Dunboyne Road

Junction 780 684 11,571 11,353

Site P R148 between Dunboyne Road

Junction and Tesco 600 701 11,139 10,985

Site Q R148, east of R157 Junction 854 1,000 11,166 10,516

Site R Dunboyne Road, north of Pebble Hill 377 358 4,017 3,735

Site S Moyglare Road, north of Maynooth 624 651 7,722 7,285

Site T R157 north of Junction with Dunboyne

Road 796 850 8,358 7,663

Site U Local Road, east of Moyglare Road 527 593 5,052 4,443

Table 2.3 - Automatic Traffic Counter Data Town Centre 2 Way Flow (2016)

Site Location Vehicles per Hour Vehicles per Day

AM PM AAWT AADT

Site 1 Kelly’s Lane 14 28 393 387

Site 2 Fagan's Lane 17 23 351 350

Site 3 Coates Lane 3 5 98 103

Site 4 Double Lane 63 44 688 641

Site 5 Back Lane 2 4 41 40

Site 6 Doctors Lane 193 279 3,065 2,882



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Figure 2.5: Estimated AADT’s within the Study Area



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Figure 2.6: Estimated AADT’s within the Study Area Town Centre



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2.4.2 Junction Turning Counts

A Junction Turning Count (JTC) captures the number of vehicles turning at a junction and

observes which turn they take. As with the ATCs they classify the traffic into different vehicle

categories. JTC surveys were undertaken at 31 junctions from 07:00 to 19:00 on Tuesday the

17th May 2016 and Thursday the 19

th May 2016. Traffic flow was classified by vehicle type and

recorded in 15 minute time intervals. The junctions listed in Table 2.4 below were surveyed (refer

to Figure 2.3).

Table 2.4 – Junction Turning Movement Counts (2016)

Site Location Date

1 R406(N) / Local Road / R406(S) / Maynooth Business Campus / Slip Road Off M4

Tuesday 17th May 2016

2 R406(N) / Slip Road Onto M4 / R406(S)

3 R406(N) / Slip Road Off M4 / R406(S) / Slip Road onto M4

4 R406(N) / Local Road / R406(S) / Lidl Access Road

5 R406(N) / Straffan Wood / R406(S) / Bus Bay

6 Meadowbrook Road(N) / Meadowbrook Road(S) /Straffan Wood

7 Meadowbrook Road(N) / Beaufield /Meadowbrook Road(S)

8 R408(W) / Beaufield / R408(E)

9 R408(N) / R408(W) / Meadowbrook Road

10 R406(N) / R406(S) / R405

11 R406(N) / Train Station / R406(S)

12 R406(N) / R406(S) / Access Road

Thursday 19th May 2016

13 Fagan's Lane / R148(W) / R406 / R148(E)

14 R148(N) / R408 / Canal Place / R148(E)

15 Moyglare Road / R148(W) / R148(S)

16 Moyglare Road(N) / University Access / Moyglare Road(S)

17 Moyglare Road(N) / Moyglare Road(S) / Moyglare Hall

Tuesday 17th May 2016 18

Moyglare Road(N) / Local Road(W) / Moyglare Road (S) / Local Road(E)

19 University Access / R148(W) / Library Access /

Tuesday 17th May 2016 20 Maynooth Campus / R408(S) / R408(E)

21 Dillow's Road / R148(W) / Doctors Lane / R148(E)

22 (1) R148(W) / Exit Only Access / R148(E)

Tuesday 17th May 2016

22 (2) Local Access / R148(W) / Main Tesco Access / R148 (East)

22 (3) R148(W) / Tesco Access / R148(E)

23 R157(N) / Local Road / R157(S)

24 R157(N) / Dillow's Road / R157(S)

25 R157 / R148(W) / R148(E)

26 R148(W) / L5053 / R148(E)

27 L5053 / R405(W) / R405(E)

28 R405(N) / Lawrence’s Avenue / R405(S)

29 R405(N) / R405(S) / Rail Park

30 R406(N) / R406(S) / Maynooth Park

31 R406(N) / R406(S) / Rail Park



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2.4.3 Automatic Number Plate Recognition (ANPR) Surveys

In order to ensure a robust representation of current traffic patterns within the Maynooth STM,

ANPR surveys were undertaken. ANPR surveys are used to provide Origin-Destination data over

a wide area and to also provide journey time information. ANPR cameras are placed on the

roadside at key locations, capturing vehicle registration plates as they passed and time stamping

the registration plate. The data was stored for each unit and the registration plate was ‘tracked’

as it passed through different sites. The time stamps allowed vehicles which make several

prolonged stops to be removed from the data.

By ‘tracking’ the registration plates the ANPR surveys captured the origin and destination of a

given vehicle within the study area. A number of sites were strategically set up throughout the

study area to form a closed cordon and data was recorded on the 19th

May 2016 (a typical

weekday) from 07:00 to 19:00. The survey data was presented on a ‘first seen-last seen’ basis,

whereby the survey data recorded the first site and last site the vehicle was seen at. A vehicle’s

origin and destination within the study area is considered to be the first and last site it was seen

at.

Origin-Destination data was collated at 21 locations within the study area as shown in Figure 2.1.

These locations were chosen to establish traffic pattern information in the area.

For presentation purposes the Origin-Destination dataset has been grouped into nine sectors as

shown in Figure 2.7. Sector 8 represents Maynooth Town Centre whilst Sector 7 represents the

Maynooth University North Campus. The remaining sectors (Sectors 1, 2, 3, 4, 5, 6 and 9)

represent the key strategic routes which provide access and egress to the Town Centre and

University.

The data is presented (expressed as proportions of origin trips) for the AM and PM peak periods

in Tables 2.5 - 2.6 below. The vertical column of row labels represents the sector at which

vehicles were first observed within the network. The horizontal row labels represent the sector at

which vehicles were last seen. Therefore, the tables outline the Origin of a vehicle (the first time

a vehicle was captured within the network) and the Destination (as the last time a vehicle was

captured).

Same site flows (i.e. first seen at Site 2 and last seen at Site 2) and vehicles only seen once in

the network (i.e. seen at only one site) have all been considered and are included into the data.

For example in Table 2.5 for Sector 1, 38% of traffic is considered local traffic as it is not seen at

any other ANPR site. Therefore this traffic has an origin and destination within Sector 1.



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Figure 2.7 – ANPR Sectors



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Table 2.5 – AM Peak O-D Results

AM Destination Sector

1 2 3 4 5 6 7 8 9

Ori

gin

Se

cto

r

1 38% 2% 4% 7% 3% 3% 18% 22% 3%

2 23% 25% 9% 2% 5% 0% 18% 16% 2%

3 10% 3% 30% 18% 1% 4% 15% 19% 1%

4 26% 1% 39% 8% 1% 4% 4% 13% 5%

5 28% 4% 10% 4% 28% 5% 4% 12% 5%

6 12% 1% 19% 2% 5% 22% 22% 15% 1%

7 15% 15% 20% 0% 10% 15% 5% 20% 0%

8 14% 2% 16% 14% 2% 5% 5% 41% 2%

9 31% 6% 11% 25% 1% 4% 2% 10% 10%

Table 2.6 – PM Peak O-D Results

PM Destination Sector

1 2 3 4 5 6 7 8 9

Ori

gin

Se

cto

r

1 24% 1% 4% 8% 16% 8% 6% 22% 10%

2 21% 25% 4% 4% 0% 8% 8% 17% 13%

3 7% 1% 24% 36% 2% 7% 2% 16% 6%

4 22% 1% 18% 13% 1% 3% 2% 19% 20%

5 15% 0% 8% 5% 24% 18% 4% 19% 7%

6 6% 0% 5% 2% 17% 27% 27% 17% 0%

7 29% 5% 16% 4% 12% 7% 1% 22% 4%

8 24% 4% 7% 6% 4% 12% 5% 30% 9%

9 20% 2% 5% 18% 10% 2% 0% 26% 18%

As can be seen from the above tables there are significant volumes of local trips in the Maynooth

area with the majority of trips having a destination within Maynooth Town Centre (Sector 8) in the

AM and PM peak hours. The traffic desire lines for the R406 north and R148 east and west of

Maynooth, and the R405 west and R157 south during the AM and PM peaks are presented in

Figures 2.8 to 2.17 below.



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Figure 2.8 – AM Peak – R406 Northbound Desire Lines

Figure 2.9 – AM Peak – R148 Westbound Desire Lines



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Figure 2.10 – AM Peak – R148 Eastbound Desire Lines

Figure 2.11 – AM Peak – R405 Westbound Desire Lines



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Figure 2.12 – AM Peak – R157 Southbound Desire Lines



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Figure 2.13 – PM Peak – R406 Northbound Desire Lines

Figure 2.14 – PM Peak - R148 Westbound West Desire Lines



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Figure 2.15 – PM Peak - R148 Eastbound Desire Lines

Figure 2.16 – PM Peak – R405 Eastbound Desire Lines



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Figure 2.17 – PM Peak – R157 Southbound Desire Lines

2.4.4 Journey Times

Journey time information was collated from the ANPR data in order to ensure that the travel time

on existing roads was properly reflected within the base models, thereby ensuring that a robust

assignment could be undertaken. A cap was placed on the recorded journey times from the

ANPR data in order to ensure trips with stop offs included as part of the recorded journey times

were excluded. Analysis was also undertaken to remove statistical outliers from the data. These

journey times represent an average of journey time surveys captured on Tuesday 19th of May

2016.

The journey times for 6 key routes in the model were analysed, these key routes are shown

graphically in Figure 2.18 below. Details of the resultant journey times for the AM and PM Peak

periods are presented in Table 2.7. This journey time data was used to validate the base year

models.



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Figure 2.18 Journey Time Routes

Table 2.7 – Average Journey Time during Modelled Peak Hours

Route Description Direction Average Duration (min:sec)

AM PM

A R148 & R406 through

Maynooth

Northbound 00:08:43 00:08:37

Southbound 00:10:58 00:11:06

B R405 & Moyglare Road

through Maynooth

Northbound 00:10:52 00:09:36

Southbound 00:10:23 00:08:59

C R408 & Dunboyne Road

Through Maynooth

Eastbound 00:09:37 00:12:46

Westbound 00:10:33 00:12:42

D R148 through Maynooth

Eastbound 00:08:24 00:09:29

Westbound 00:08:30 00:10:32

2.5 GeoDirectory Data

The GeoDirectory dataset is a database jointly established by An Post and Ordnance Survey

Ireland. The dataset is a complete address database of all buildings in Ireland, with each building

classified as commercial, residential or both (commercial and residential use) within the dataset.

The data for the study area was utilised to help inform the disaggregation of NTM zones and the



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placement of zone connectors. Figure 2.19 below shows the GeoDirectory units by type within

the study area.

Figure 2.19 – GeoDirectory Points within Traffic Model



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Chapter 3

Model Development



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3 Model Development

3.1 Overview

This section of the report describes the development, calibration and validation of the 2016 Base

Year Maynooth STM’s which have been developed for the following time periods:

AM Peak Hour (08:00 – 09:00); and

PM Peak Hour (17:00 – 18:00).

These peak hours were defined (as highlighted in green below) following an assessment of the

ATC’s within the study area. Traffic flows at each of the ATCs within the study area were

aggregated together to reveal the following traffic demand profile.

Figure 3.1 – Peak Hour Selection

3.2 Definition of Model Study Area

In order to identify the extent of the study area for the Maynooth STM a high level assessment

was undertaken using the National Traffic Model (NTM). An indicative route alignment was coded

into the future NTM (2030 High Growth) and assessed to establish the extents of the existing

road network impacted upon.

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3.3 Network Development

As mentioned previously, the NTM was used as a starting point for developing the 2016

Maynooth STM’s. Having identified the extent of the study area, the subsequent area of influence

was ‘cordoned’ out of the 2015 NTM Base model and is shown in Figure 3.2 below.

Figure 3.2 – Maynooth STM Study Area Cordoned from NTM

As outlined in Figure 3.2 above in cordoning the roads impacted by the Maynooth LAP 2013 to

2019 proposals from the NTM it was noted that the road impacted include all radial routes

connecting into Maynooth namely the M4, R148, R157, R405 and R406. These routes link the

neighbouring towns of Kilcock, Dunboyne, Leixlip and Celbridge to Maynooth. Therefore in the

subsequent refinement of the STM for Maynooth external zones which represent each of the

neighbouring towns were created to ‘feed’ traffic into the network, further details of the model

zone refinement process are given in Section 3.3.2 of this report.

3.3.1 Refinement of STM Road Network

Once the study area had been cordoned from the NTM, the road network was further refined to

reflect the 2016 road network conditions (i.e. inclusion of further detail such as refined road

capacity, turn bans, junction types etc.). This information was collected through site observations

and aerial mapping.



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There were a significant number of local roads which are not included in the 2015 NTM modelled

network. These local roads were coded into the 2016 STM as they could be potentially impacted

upon by any proposed schemes.

The road network was developed to a level of detail that included all National Primary,

Secondary and Regional roads and all significant local roads throughout the study area. The

information on each link included:

Link Length;

Link type, for example, National Regional Road, Local Urban, Local Rural etc.;

Link capacity;

Speed limit and free flow speed; and

Reference to an appropriate speed flow curve

3.3.2 Refinement of STM Zoning System

The refinements to the highway network needed to be accompanied by a finer representation of

trip demand through the use of smaller zone sizes in the Maynooth STM. The zoning system in

the NTM is based on the aggregation of Electoral Divisions (ED’s), which is not suitable for a

smaller local area model such as the Maynooth STM. A refined zoning system was therefore

needed to be designed.

Additionally the refined zoning system for the Maynooth STM was required to be designed in a

fashion that ensured the Maynooth STM zones were compatible with both TII’s NTM and the

National Transport Authorities (NTA) Eastern Regional Model (ERM). A zone disaggregation

process as outlined below was therefore undertaken.

Zone Disaggregation

Within the NTM the Maynooth urban area is covered by one large zone, Zone 490, which also

includes the Celbridge and Leixlip urban areas. Within the ERM the zone structure local to

Maynooth is more refined with nine smaller zones covering the Maynooth urban area. The zone

structures of both the NTM and the ERM in the area local to Maynooth are entirely compatible

with the ERM zoning structure representing a sub-set of the NTM zone structure. The zone

structure local to Maynooth from both the NTM and the ERM are shown in Figures 3.3 and 3.4

overleaf.



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Figure 3.3 – NTM Zone 490 Coverage

Figure 3.4: NTM & ERM Zone Structure Local to Maynooth



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The Maynooth STM required a zone structure which could accurately reflect local traffic patterns

in Maynooth whilst at the same time maintaining compatibility with the zone structure of both TII’s

NTM and the NTA’s ERM. In order to achieve these objectives NTM Zone 490 was initially

disaggregated in three sub zones representing the Maynooth, Celbridge and Leixlip urban areas.

The disaggregation of NTM zone 490 was based on analysis of the An Post Geo-Directory data

contained within each of the ERM model zones in the three resultant NTM sub zones. Figure 3.5

below refers.

Figure 3.5: NTM Zone 490 Disaggregation

Upon completion of the initial disaggregation of NTM Zone 490 in three sub zones the resultant

Maynooth zone as indicated in Figure 3.5 above was then disaggregated into a significantly finer

zone structure which is capable of reflecting, to a high degree of accuracy, the local traffic

movements in the Maynooth town centre and its environs. The starting point in this

disaggregation was the ERM zone system; however a finer zoning structure (which maintains

compatibility with the ERM and NTM) has been developed to reflect local traffic movements. The

Maynooth STM zone structure takes account of existing and future land use patterns. The

development of the zone structure again utilised An Post Geocoding information which allowed a

detailed understanding of the quantum of residences and commercial buildings in each zone.

Figure 3.6 overleaf outlines the ERM zone structure local to Maynooth and the Maynooth STM

zone structure which forms a subset of the ERM zones.



Page 33

Figure 3.6: ERM Zone Structure and Maynooth STM Zone Structure

As part of the NTM cordoning process three more full NTM zones (Zones 326, 488 and 496)

were entirely cordoned from the NTM. Additionally 21 external zones were created as part of the

model cordoning process. These zones all represented external zones in the Maynooth STM as

they essentially feed traffic into and out of the detailed modelled area as outlined in Figure 3.6

above. For external zones an aggregation process was therefore undertaken which matched the

external zones to each of the radial routes feeding into the detailed modelled area. In instances

where a number of external zones created from the NTM cordoning process were found to feed

traffic onto the same radial route they aggregated to simplify the final demand matrix.

The original model cordoned from the NTM contained 25 zones, which included the 4 internal

zones and 21 external zones. The disaggregation of the various zones noted above produced a

model containing a total of 56 zones, including 11 external zones. The refined STM highway

network and zoning structure is shown in Figure 3.7 below.



Page 34

Figure 3.7 – Refined Maynooth STM Zone Structure

3.3.3 Link Travel Times

The total travel time of a trip from origin to destination is a function of both link travel time and

junction delay. Link travel times in the network are determined by a predefined Volume-Delay

Function (VDF) in VISUM, which describes the relationship between current traffic volumes (q)

and the capacity of the link (qmax). The VDF used in this model is based on the Bureau of Public

Roads 3 (BPR 3) function:

t cur = t0 * (1 + a * sat

b) , if sat ≤ sat crit

t0 * (1 + a * satb) + (q – q max) * d , if sat > sat crit

Where: t0 = free flow travel time (based on link length (km) and free flow speed (v0))

sat = q/(qmax * c)

The VDF function is globally applied to all links in the network as the capacity (q) and free flow

speed (v0) of each link (input during network development) feed directly into the VDF. A VDF is

applied to each link classification in the model based on adjusted a, b, c and d parameter values

which reflect the quality of that road type.



Page 35

3.4 Matrix Development

The following time periods were required for the Maynooth STM:

Morning peak from 08:00 – 09:00 (AM Peak Period); and

Evening Peak from 17:00 – 18:00 (PM Peak Hour)

‘Prior’ AM Peak Light and Heavy vehicle matrices were extracted from the cordoned 2015 NTM.

The matrices were disaggregated to provide a more refined STM zoning system as discussed in

Section 3.3.2 above. The process of zone splitting was undertaken using VISUM, whereby origin

and destination trip ends were allocated to the sub-zones based on An Post GeoDirectory

information whilst maintaining the equivalent distribution of the larger zones.

The resultant ‘Prior’ matrices were then adjusted during the calibration process using matrix

estimation methods to reflect 2016 demand. As there is no PM Peak Hour NTM an alternative

approach to generate the PM Peak Hour ‘Prior’ matrices was adopted. The calibrated AM Peak

Hour matrices were transposed to give a ‘Prior’ PM matrix as a starting point for the calibration

process. Each of these matrices were then modified during the calibration process using the

2016 traffic survey data ascertained for each peak, using select link analysis and matrix

estimation tools in VISUM.

3.5 Assignment Model

The assignment model applies the demand for travel, represented by the trip matrices, to the

supply, in the form of the road network. The ‘generalised cost’ of a journey, represented by a

combination of time, distance and tolls is compared in a route choice algorithm, and a stable

output is produced, where ideally, all possible routes between an origin and destination have the

same ‘cost’. Generalised cost is computed as follows:

Generalised Cost = Value of Time * Time + Vehicle Operating Cost * Distance + Toll

3.5.1 Assignment Algorithm

The Route Choice Algorithm selected is based on Equilibrium Lohse. This assignment method

models the learning process of road users using the network. The first iteration step is an ‘all or

nothing’ assignment, which means that all trips are assigned onto the lowest impedance route

(route with the lowest generalised cost) of the unloaded network. No congestion or delay is taken

into account in the route choice for each trip.

In each subsequent iteration, the new lowest impedance route for each OD pair is found. Drivers

make use of information gained during their previous trips for the new route search and all known

‘shortest’ routes are searched for in an iterative process. For the route search the impedance is

deduced from the impedance of the current volume and the estimated impedance from the

previous iteration step. In other words the route search estimates delay based on impedance in

the previous iteration and uses this to inform the new route choice.

The assignment terminates when a stable solution is calculated and user equilibrium is reached.

When equilibrium conditions have been reached, no user can further reduce the impedance of

their trip by switching route.



Page 36

3.6 Estimation of Annual Average Daily Traffic (AADT)

To estimate the Annual Average Daily Traffic (AADT), conversion rates were developed which allowed the extrapolation of AM and PM peak hour traffic flows to AAWT, using a calculated conversion factor then from AAWT to AADT:

Regression analysis, based on data from TMU’s located within the study area, was used to generate the equation outlined above. In order to assess the accuracy of the AM and PM Peak hour expansion factors to AADT a comparison of observed and modelled 2014 & 2015 AADTs has been undertaken in Table 3.1. Table 3.1 - Accuracy of AM, Inter & PM Peak Hour Expansion Factors to AADT

TII TMU

AADT

Accuracy Observed Modelled

TMU 20041 2014 49,281 50,343 -2.2%

TMU 20041 2015 50,690 50,405 0.6%

TMU 20042 2014 35,798 35,645 0.4%

TMU 20042 2015 37,586 36,996 1.6%

The table above shows that the expansion factors used to estimate AADT from AM and PM peak hour models leads to accurately modelled AADT forecasts.

2.20 * (a + b) = LV AAWT

2.81 * (x + y) = HV AAWT

(LV AAWT) * 0.96 = LV AADT

(HV AAWT) * 0.82 = HV AADT

LV AADT + HV AADT = Total AADT

Where,

a = AM Peak Period LV Demand, x = AM Peak Period HV Demand

b = PM Peak Period LV Demand, y = PM Peak Period HV Demand



Page 37

Chapter 4

Model Calibration & Validation



Page 38

4 Model Calibration & Validation

4.1 Introduction

Following the development of the base year models, the process of calibrating and validating the

models was undertaken.

4.2 Calibration

The purpose of model calibration is to ensure that the model assignments reflect the existing

travel situation. Calibration is an iterative process, whereby the model is continually revised to

ensure that base year conditions are accurately represented.

4.2.1 Matrix Estimation

Matrix Estimation (ME) is the process in which the number of trips assigned along a model link is

adjusted to match an observed total. ME can be undertaken manually through select link (flow

bundle) analysis or through the “TFlow Fuzzy” matrix estimation tool provided in VISUM. “TFlow

Fuzzy” is designed to automatically adjust trip matrices to match modelled volumes to observed

volumes along multiple links or turns.

The Maynooth STM’s were calibrated utilising flow bundle analysis as it allowed greater control

over the calibration process than “TFlow Fuzzy”. Flow bundle matrices were extracted, examined

and subsequently adjusted to match observed flows both up and downstream of the point at

which the flow bundle was taken.

4.2.2 Calibration Criteria

The model calibration process has been undertaken based on the requirements of the TII PAG

Unit 5.2: Construction of Traffic Models and with reference to the calibration criteria outlined in

Table 5.2.2 of that document. The PAG specifies the acceptable values for modelled and

observed flow comparisons and suggests how calibration should relate to the magnitude of the

values being compared. A summary of these targets is shown in Table 4.1 below.

Table 4.1 - Model Calibration Criteria: Individual Flows

Criteria & Measures Guideline

Assigned Hourly Flows (e.g. links or turning movements) vs. Observed Flows:

Individual flows within 100 vph for flows <700 vph

>85% of cases Individual flows within 15% for flows 700 – 2700 vph

Individual flows within 400 vph for flows > 2700

The standard method used to compare modelled values against observations on a link involves

the calculation of the Geoff E. Havers (GEH) statistic (Chi-squared statistic), incorporating both

relative and absolute errors. The GEH statistic is a measure of comparability that takes account

of not only the difference between the observed and modelled flows, but also the significance of

this difference with respect to the size of the observed flow. The GEH statistic is calculated as

follows:



Page 39

𝑮𝑬𝑯 = √(𝑴 − 𝑶)𝟐

𝟎. 𝟓(𝑴 + 𝑶)

Where M = Modelled Flow and O = Observed Flow.

Guidance in the PAG sets out the following criteria in relation to GEH values:

Table 4.2 - Model Calibration Criteria: GEH Values

Criteria and Measures Requirement

GEH statistic Individual flows: GEH < 5 > 85% of cases

4.2.3 Calibration Results

A total of 44 links flows and 77 turning flows were used in the calibration process, the results of

which are summarised in Tables 4.3 - 4.6. The results in full can be found in Appendix B of this

report.

Table 4.3 - Link Calibration Results: Individual Flows

% of Calibration Sites Meeting Individual Flow Criteria

Time Period Link Flows

Required Total Traffic Lights Heavies

AM Peak 96% 93% 98% >85%

PM Peak 96% 93% 98% >85%

Table 4.4 - Link Calibration Results: GEH Values

% of Calibration Sites with GEH < 5

Time Period Link Flows Required

Total Traffic Lights Heavies

AM Peak 96% 96% 87% >85%

PM Peak 98% 98% 93% >85%

Table 4.5 - Turn Calibration Results: Individual Flows

% of Calibration Sites Meeting Individual Flow Criteria



AM Peak 100% 96% 100% >85%

PM Peak 95% 94% 100% >85%

Table 4.6 - Turn Calibration Results: GEH Values

% of Calibration Sites with GEH < 5



AM Peak 96% 96% 100% >85%

PM Peak 89% 89% 100% >85%



Page 40

The comparison of modelled and observed flows demonstrates that the AM and PM Peak period

models match the flow criteria for all user classes. Likewise, the GEH results show that the AM

Peak and PM Peak periods models also match the criteria for all user classes. The results

therefore confirm that the models have been calibrated to a standard compliant with the PAG

criteria for all user classes and all time periods.

4.2.3 Trip Length Distribution Check

The output trip matrix from the matrix estimation process must be checked to ensure that the

process has not significantly altered trip distribution. It is possible that in seeking to increase the

flow along a particular link, that the matrix estimation process might add significant numbers of

short trips between the two zones at either end of the link in question. This could have the effect

of creating excessive short distance trips while longer distance trips are unaffected, which in turn

would push the trip distance distribution toward short trips.

To check the output of the matrix estimation process, the Trip Length Distributions (TLD) from

before (pre) and after (post) matrix estimation are compared. The TLD for each peak hour for

Light Vehicles are represented as histograms in Figure 4.1 and 4.2.

Figure 4.1 - TLD AM Peak Hour (LV)

0

0.05

0.1

0.15

0.2

Pro

po

rtio

n o

f T

rip

s

Trip Length (km)

AM Peak Uncalibrated

AM Peak Calibrated



Page 41

Figure 4.2 - TLD PM Peak Hour (LV)

In undertaking the matrix calibration process for Maynooth it was noted that the proportion of

short distance trips in the distance bands 2 km to 4 km and 4 km to 6 km decreased in each of

the AM and PM peak demand matrices. However this was not a concern in this instance as Zone

490 (which has a radius of circa 5km) was disaggregated into 45 sub-zones in the model building

process. A large volume of internals trips was noted in the ANPR surveys and the pre calibration

matrices were developed to reflect these internal trips between the sub zones. A quantum of

existing internal trips were present in the original demand matrices from the NTM. This resulted

in a double counting of some short distance trips, which then had to be reduced in the calibration

process. Overall the TDL figures illustrate that the TLD has not been significantly altered as a

result of matrix estimation.

4.3 Model Validation

Model validation comprises the comparison of calibrated flows against an independent dataset

which was not used as part of the calibration process. Validation checks included:

Additional link flows;

Turning flow validation; and

Overall model validation (e.g. journey times)

The model was also checked against the OD data collected as part of the ANPR and used as

part of matrix development though this is not required under PAG guidance.

4.3.1 Validation of Link Flows

A total of 22 observed and modelled link flows were compared at a number of validation sites

which were kept exclusive of the calibration data, in accordance with the criteria above. The

permissible difference was calculated for each value (based on the observed figure) and

compared with that which had been modelled. Validation results are included in Appendix C and

are summarised in Tables 4.7 and 4.8.

0

0.05

0.1

0.15

0.2P

rop

ort

ion

of

Tri

ps

Trip Length (km)

PM Peak Uncalibrated

PM Peak Calibrated



Page 42

Table 4.7 - Validation Results: Individual Flows

% of Validation Sites Meeting Individual Flow Criteria



AM Peak 92% 92% 100% >85%

PM Peak 100% 100% 100% >85%

Table 4.8 - Validation Results: GEH Values

% of Validation Sites with GEH < 5



AM Peak 92% 92% 92% >85%

PM Peak 100% 100% 192% >85%

A comparison against the validation counts shows that the AM and PM Peak period models all

exceed the PAG requirements for the validation of traffic flow on links. Likewise, all models

exceed the GEH criteria of 85%. The results therefore demonstrate that the validation criteria as

set out by TII in the PAG are successfully met by all models.

4.3.2 Validation of Turning Flows

A further 34 observed and modelled turning flows were compared at each of the validation sites

in accordance with the criteria above. The permissible difference was calculated for each value

(based on the observed figure) and compared with that which had been modelled. Validation

results are included in Appendix C and are summarised in Tables 4.9 and 4.10 below.

Table 4.9 - Validation Results: Turning Flows

% of Validation Sites Meeting Individual Flow Criteria



AM Peak 98% 98% 100% >85%

PM Peak 96% 93% 100% >85%

Table 4.10 - Validation Results: GEH Values

% of Validation Sites with GEH < 5



AM Peak 87% 87% 100% >85%

PM Peak 87% 87% 100% >85%

A comparison against the validation turning counts shows that all the models exceed the PAG

requirements for the validation of traffic flow. Likewise, all models exceed the GEH criteria of

85%. The results therefore demonstrate that the validation criteria as set out by TII in PAG are

successfully met by all models.



Page 43

4.3.3 Validation of Journey Times

As part of the validation process, the modelled journey times were compared against the

surveyed journey times to ensure the model gave a reasonable representation of existing

conditions. The results of the journey time validation are presented in tables 4.11 to 4.12 for the

AM and PM peak hours respectively, for the journey time routes shown previously in Figure 2.6.

Table 4.11 - AM Peak Modelled/Observed Journey Times

Route Description Direction

Average Duration (min:sec)

ABS Diff %

Diff Validated

Observed AM

Modelled AM

A

R148 & R406 through Maynooth

Northbound

00:08:43

00:09:02 00:00:19 4%

Southbound 00:10:58 00:10:00 00:00:58 9%

B

R405 & Moyglare Road through Maynooth

Northbound 00:10:52 00:10:00 00:00:52 8%

Southbound 00:10:23 00:10:28 00:00:05 1%

C

R408 & Dunboyne Road Through Maynooth

Eastbound 00:09:37 00:11:57 00:02:20 24%

Westbound 00:10:33 00:08:57 00:01:36 15%


Eastbound 00:08:24 00:09:42 00:01:18 15%

Westbound 00:08:30 00:08:30 00:00:00 0%

Percentage Validated 87.5%

Table 4.12 - PM Peak Modelled/Observed Journey Times

Route Description Direction

Average Duration (min:sec)

ABS Diff %

Diff Validated

Observed AM

Modelled AM

A R148 & R406 through Maynooth

Northbound 00:08:37 00:09:04 00:00:27 5%

Southbound 00:11:06 00:09:49 00:01:17 12%

B

R405 & Moyglare Road through Maynooth

Northbound 00:09:36 00:10:08 00:00:32 6%

Southbound

00:08:59 00:10:10 00:01:11 13%

C

R408 & Dunboyne Road Through Maynooth

Eastbound 00:12:46 00:09:43 00:03:03 24%

Westbound

00:12:42 00:11:11 00:01:31 12%


Eastbound 00:09:29 00:09:18 00:00:11 2%

Westbound 00:10:32 00:09:06 00:01:26 14%

Percentage Validated 87.5%

All models satisfy the PAG requirement that 85% of all modelled journey times are within 15% of

observed data or within 1 minute if higher than 15%. As such, the base year models are



Page 44

considered validated to the requirements of PAG Unit 5.2: Construction of Transport Models in

terms of journey times.

4.4 Comparison of Traffic Patterns

Although not required under PAG guidance, the routing of traffic though the study area was

checked against the results from the OD surveys outlined in Section 2.4.3. The difference

between observed and modelled traffic patterns are presented in Tables 4.13 – 4.14 below for

both light and heavy vehicles.

Whilst no guidelines exist on the validation of OD patterns, a target of +/- 20% was used as a

target deviation limit. The tables below show that all of OD pairs are within the +/- 20% target

value. There were a number of instances in which the +/- 20% criteria was slightly exceeded as a

result of matrix manipulation to meet the calibration criteria. Each of these instances was

amended in the matrices, and afterwards the calibration criteria were rechecked.



Page 45

Table 4.13 - Comparison of AM Peak Traffic Patterns

490009 490011 490008 490003 490025 490002 490042 490010 490038 490034 490037 490005 490029 490024 490021 490019 490004 1009 Average

490009 - -1% -3% 0% -2% 0% 0% -9% 0% 0% 11% 9% -3% -3% 0% 0% 6% 12% 1%

490011 -3% - 3% -1% 14% -1% 0% -8% 0% 0% -9% 2% 0% 3% -1% 2% -1% 0% 0%

490008 -12% 5% - 0% -2% -1% 0% -2% 0% 2% -13% -2% -1% -3% -1% 0% -2% 0% -2%

490003 0% -11% 0% - 3% 1% 0% -11% 0% 2% 2% 8% 0% 0% 0% 0% 0% 1% 0%

490025 -2% 0% -13% 0% - -1% 0% 3% 0% 3% -5% 5% -3% -3% -1% 0% 1% 2% -1%

490002 -8% 0% 1% 13% 8% - 0% -3% 0% 1% -2% -2% 1% 1% 1% -1% 0% -2% 0%

490042 0% 0% 9% 0% 0% -3% - 1% 2% 1% 0% 0% 0% 0% 0% 0% 0% 0% 1%

490010 -2% -4% -9% 0% 0% -1% 0% - 0% -2% -9% -2% 3% 6% -2% 1% -1% 18% 0%

490038 0% 0% -3% 0% 0% 5% 0% -5% - 0% -13% -4% 0% 2% 3% 0% 0% -3% -1%

490034 3% -1% -3% 8% 5% 0% 0% -10% 0% - -3% -1% -2% -1% -2% 0% 1% -4% -1%

490037 -4% -1% -20% 0% 7% -4% 0% -8% -1% 0% - 18% 0% 0% 0% 0% 2% 0% -1%

490005 -7% -3% -10% 0% -5% 0% 0% -11% 0% -3% 16% - -1% -5% -2% 0% 3% 0% -2%

490029 0% 0% -7% 0% -6% 0% 0% 0% 0% -4% -17% -1% - 11% 0% 14% 0% 1% 0%

490024 16% 0% 2% 0% -3% 0% 0% -4% -3% -3% -2% -9% 2% - -7% 2% -3% 16% 0%

490021 -5% 0% -7% 0% -5% 0% 0% -2% 0% 0% 0% 5% 0% 0% - 0% 0% 1% -1%

490019 -11% 0% 5% 0% -3% 0% 0% -4% 0% 0% -14% -3% 0% 16% 0% - 0% 2% -1%

490004 -8% -3% -19% 0% -2% -4% 0% -2% -1% -1% -1% 2% -2% -2% -1% 0% - 19% -1%

1009 3% -1% -11% 0% 3% -2% 0% 1% 0% 4% -2% 9% 0% -2% -3% 0% 5% - 0%

Average -2% -1% -5% 1% 1% -1% 0% -4% 0% 0% -4% 2% 0% 1% -1% 1% 1% 4% 0%

AM

Destination Zone

Ori

gin

Zo

ne



Page 46

Table 4.14 - Comparison of PM Peak Traffic Patterns

490009 490011 490008 490003 490025 490002 490042 490010 490038 490034 490037 490005 490029 490024 490021 490019 490004 1009 Average

490009 - -2% -8% 0% 1% -6% 0% -1% 0% 4% 3% -7% -4% -6% 0% 1% -15% 9% -2%

490011 -7% - 9% 0% 0% -4% 0% -7% -3% 7% -1% -5% -1% -2% -2% -2% -10% 1% -2%

490008 -3% 0% - 0% 0% 4% 7% -2% 0% 0% -9% -7% -2% -4% 0% -1% -15% 1% -2%

490003 0% 0% 0% - 0% -3% 0% 0% 0% 19% -7% 0% 0% 0% -7% 0% -7% 3% 0%

490025 -9% -1% -9% 0% - -1% 0% -2% -1% 5% -3% -6% -3% -7% 2% 0% -8% 3% -2%

490002 -4% -2% -14% 3% -1% - 18% -2% 2% 0% -5% -1% -3% -13% -1% 0% -7% -4% -2%

490042 0% 0% 0% 0% 0% 0% - 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

490010 -10% -5% -5% -1% 6% -5% 0% - -1% 4% -5% -5% -1% 7% -3% 2% 2% 19% 0%

490038 0% 0% -6% 0% 4% 0% 2% -6% - 0% -14% -6% -12% -12% -6% 0% 1% -5% -4%

490034 0% 0% 2% -1% 5% -13% 1% 1% 0% - -2% -10% 1% -12% 0% 0% -7% 6% -2%

490037 -8% -4% -19% 6% 3% -3% 0% -6% -2% 11% - 17% -1% -8% 8% -1% 0% 0% 0%

490005 -4% -6% -12% 2% 3% -1% 0% -2% -2% 0% 15% - -1% -7% 0% 0% -9% 6% -1%

490029 0% 0% -12% 0% 0% -9% 0% 12% 0% 0% 13% -20% - 0% 0% 0% -4% 0% -1%

490024 -12% 3% -19% 0% 0% -7% 0% 17% 1% -6% -4% -16% 4% - -1% 18% -4% 18% -1%

490021 -6% -2% -9% 0% 0% 1% 0% -8% 2% 2% -1% -4% 0% 1% - 0% -2% 13% -1%

490019 -5% 2% -19% 0% 2% -4% 0% 1% -5% 17% -5% 0% 18% -14% -5% - 0% 0% -1%

490004 -2% -5% -12% 0% 12% -6% 0% -3% -2% 1% 2% -7% -3% -8% -3% 0% - 13% -1%

1009 -9% -4% -9% 0% 6% -12% -1% 9% -1% 0% 0% -1% 1% 16% -2% 1% 15% - 0%

Average -5% -2% -8% 1% 2% -4% 2% 0% -1% 4% -1% -5% 0% -4% -1% 1% -4% 5% -1%

PM

Ori

gin

Zo

ne

Destination Zone



Page 47

4.5 Model Convergence

The model assignment procedure involves the model reaching a point of equilibrium through an

iterative process. The model must therefore achieve a satisfactory point of convergence in order

to produce results that are both reflective of the network over a number of iterations of assigning

demand to the network.

The convergence indicators vary by different transport modelling packages; therefore multiple

criteria are outlined in the UK Department for Transport (DFT) Transport Appraisal Guidance

(TAG) Unit M3.1 – Highway Assignment Modelling (Jan 2014). The criterion that is used to show

that the VISUM software reaches a level of convergence is as follows:

The difference between the costs along the chosen routes and those along the minimum

cost routes, summed across the whole network, and expressed as a percentage of the

minimum costs, usually known as 'Delta' or the ‘%GAP’ (<0.1%); and

The percentage (P) of links on which flows or costs change by less than a fixed

percentage (<5%)2 for four consecutive iterations greater than 98%.

The model software produces the convergence information by user class, defining the

percentage difference in link volume per vehicle class. Table 4.15 below indicates that the AM

Peak and PM Peak models have reached a satisfactory level of convergence.

Table 4.15 - Model Convergence

Time

Period %GAP

Light Heavies

Iterations P Iterations P

AM 0.003 55 100.00% 55 100.00%

PM 0.004 61 100.00% 61 100.00%

2 TAG Unit M3.1 recommends a value of <1% but the VISUM software only provides data at <5% as per the previous UK

DMRB guidance on convergence. However due to the nature of the scheme it is estimated that a value of <1% would readily be achieved.



Page 48

Chapter 5

Future Year Demand Development



Page 49

5 Future Year Model Development

5.1 Introduction

This section of the report summaries the development of the future year traffic models for the

Maynooth Traffic Management Plan. Full details on the process can be found in the Future Year

Forecasting & Demand Allocation - Technical Note 1 contained in Appendix D of this report.

The future years models developed were (+ 5 years) 2021 and (+10 years) 2031. These years

were selected as they complied with guidance provided on forecast assessment years outlined in

TII’s Traffic and Transport Assessment (TTA) Guidelines 2014.

5.2 Future Year Matrix Development

5.2.1 Overview

The future years for the Maynooth STM are 2021 and 2031. As it was a requirement of the study

that the zone structure of the Maynooth STM was compatible with both TII’s NTM and the NTA’s

ERM future year traffic growth projections were developed for three potential growth projection

scenarios namely:

The projections inherent in the NTpM future year models;

The projections inherent in the ERM future year models; and

Projections developed by KCC based on the land use zonings and forecasts contained

within the Maynooth Local Area Plan 2013 to 2019 and the Draft Kildare County

Development Plan (CDP) 2017 – 2023.

The KCC growth projections scenario was developed based on the land-use zoning information

provided by KCC covering the periods: 2016 to 2021, and 2021 to 2031. It is worth noting however

that the actual full development zoned lands contained within the Maynooth Local Area Plan 2013

to 2019 and the Draft Kildare County Development Plan (CDP) 2017 – 2023 will likely occur at a

point beyond the horizon of the current plans.

5.3 Maynooth Area Future Development

5.3.1 Land Use Zonings Maynooth

The future land use zoning objectives of the Maynooth Local Area Plan 2013 to 2019 outline the

spatial locations throughout Maynooth where future land-use is anticipated and accordingly zoned.

Figure 5.1 below refers. These land-use zonings together with growth projections outlined in the

Draft Kildare CDP 2017-2023 formed the basis of the future land use development forecasts in the

Maynooth area as outlined by KCC.



Page 50

Figure 5.1: Maynooth LAP Land Use Zonings

5.3.2 Population Projections and Assumptions

The core strategy for the Draft Kildare CDP 2017-2023 proposes a population increase in

Maynooth of 5,786 for a 9 year horizon, i.e. a population growth of 642 people per annum from

2017 - 2026. Based on data as supplied by KCC it was considered reasonable to use this figure of

642 people per annum to estimate population increases for 2021 and 2031. The estimated

population growth projections are shown in Table 5.1 below.

Table 5.1 -: Population Projections for 2021 and 2031 Maynooth

Year Population Population Increase (642 per annum)

2016 13,210 -

2021 16,420 + 3210

2031 22,840 + 6420



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5.3.3 Non-Residential Land Use Projections

The zoning objectives of the Maynooth LAP 2013 to 2019 and the Draft Kildare CDP 2017-2023 as

they relate to the Maynooth study area and the quantum of zoned lands (hectares) for non-

residential land uses are presented in Table 5.2 below.

Table 5.2 - Maynooth Quantum of Zoned Lands

Other Future Land Use Type 2021 2031

Secondary School 2 schools*

Office 75.5 ha** 70.2 ha****

Industrial 2.9 ha 2.9 ha

Warehousing 3.2 ha***

Community 0.7 ha

* Planning permission 13/828 granted for two post-primary schools with capacity for 2,000 pupils

** 73.2 hectares zoned for Research and Technology. No permission granted – this is a long term strategic

employment site, post 2021.

*** 3.2 ha ‘Warehousing’ also included under ‘Office’

**** Includes 59 hectares zoned for Research and Technology at Collinstown.

In order to estimate the potential impact of the zoning objectives set out in Table 5.2, in terms of

the generation of additional traffic, the following methodology was applied:

KCC’s Planning Department were consulted to ascertain their estimation of the future land use projections for each of the zones within the STM and anticipated build out date for the land use projections;

Trip rates associated with the population growth and land use quanta as indicated in Tables 5.1 and 5.2 were established using the TRICS database and Trip Rates synthesised by AECOM for use in similar land use and transport studies;

These trips rates were then applied to the quantum of undeveloped lands as specified by KCC’s Planning Department.

5.3.4 Maynooth University Growth

Forecasts were obtained from Maynooth University for an anticipated growth from 9,000 students

(in 2016) to 18,000 students by 2031. Using this information it was estimated that the traffic

demand at Maynooth University would likely double in the period 2016 to 2031. Using a linear

interpolation between the existing 2016 demand at Maynooth University and the forecast 2031

demand a future demand projection for 2021 was estimated. The additional demand for the

Maynooth University zone was added to the future forecast 2021 and 2031 demand matrices.



Page 52

5.4 Future Land Use Projections & Associated Traffic Generation

5.4.1 Future Land Use Projections - Kildare County Council

In order to simplify the matching of future land use projections (both residential and other future

land use) with the disaggregated Maynooth STM zone structure, AECOM worked with KCC to

develop a future land use matrix of the STM zones numbers set against a range of typical land use

types. The land use types corresponded with the planning data received from KCC and the zoning

objectives of the Maynooth LAP 2013 to 2019 and the Draft Kildare CDP 2017 – 2023. These land

use types and their units of measurement are specified in Table 5.3 below.

Table 5.3 – Land use Types and Units of Measurement

Land use Type Measurement

Residential Population or No. of Units

Secondary School No. of Units

Office Site Area (ha/m2)

Industrial and Warehousing Site Area (ha/m2)

Retail Site Area (ha/m2)

Enterprise and Employment Site Area (ha/m2)

Community Site Area (ha/m2)

KCC’s Planning Department then populated the matrix with their future land use projections for

each zone in the STM and specified an anticipated build out date for each of the land use

projections.

5.2 Future Residential Development (KCC)

It is considered reasonable that up to the year 2021, 80% of all new population will be located in

areas where ‘new residential’ land is zoned and that the remaining 20% would be located on other

zoned lands where ‘residential’ would be permitted (Town Centre, Existing Residential & Infill). By

2026, it is assumed that the ‘new residential’ zoned lands will be built-out. Of the population

increase for the 10 year period 2021-2031, 45% is assigned to ‘new residential’ zoned land (to

reflect 2021-2026), 45% to ‘agricultural’ zoned land within the plan area (which could potentially be

re-zoned for residential purposes in future plans) and 10% to other zoned lands where ‘residential’

would be permitted (town centre, existing residential & infill). The calculations are set out in Table

5.4 below.



Page 53

Table 5.4 - Geographical Location of New Population (2021 and 2031 Maynooth)3

Year Population of

Maynooth

Population

Increase

(642 per

annum)

New Population

in STM’s with

Lands Zoned C

(New

Residential

Areas)

New Population

in STM’s with

lands Zoned

A1, A2 and B

New Population

in STM’s with

Lands Zoned I

(Agriculture)

2016 13,210 - - - -

2021 16,420 + 3210

2568

(80% of new

population)

642

(20% of new

population)

0

2031 22,840 + 6420

2889

(45% of new

population to the

year 2026 only)

642

(10% of

population

increase)

2889

(45% of

population

increase post

2026)

5.3 Future Employment Development

In the absence of future jobs forecasts for Maynooth it was necessary for AECOM to develop a

number of assumptions regarding future employment development based on information from the

Draft Kildare CDP 2017 – 2023 and information supplied by KCC’s Planning Department in relation

to future population growth projections and future land use data (as described above). Based on

section 5.2.3 of the Draft Kildare CDP 2017 – 2023, the following high level data was extracted:

A jobs to population ratio of 0.7 is assumed;

The total Kildare labour force will increase by as much as 126,800 by 2023 (50% of population).

AECOM developed a set of high level assumptions regarding future employment development

based on the assumption that the jobs ratio and ratio of labour force to population increase hold

true for both 2021 and 2031. Furthermore, it is assumed that these countywide assumptions for

Kildare apply to the Maynooth area. Table 5.5 below sets out future employment projections for the

Maynooth area based on the above assumptions on the labour force to population ratio and job

ratio in addition to the population projections supplied by KCC.

Table 5.5 – Maynooth Employment Projections

2016 2021 2031 2016 -

2021

2021 -

2031

Population 13,210 16,420 22,840 3,210 6,420

Estimated Labour Force 6,605 8,210 11,420 1,605 3,210

Estimated Number of Jobs 4,624 5,747 7,994 1,124 2,247

Table 5.5 demonstrates that the projected additional number of jobs in Maynooth in 2021 and 2031

will be, respectively, 1,124 and 2,247. The estimated number of new jobs required for the

Maynooth area (based on the population projections) is assumed to be distributed across the future

employment type land uses in 2021 and 2031 by the process described below.

3 Source: Kildare County Council Memorandum ‘Maynooth Future Growth Forecasts 2021 and 2031’,

17/11/2016.



Page 54

5.4 National Traffic Model Forecasts

Future year growth in the Maynooth STM external zones (i.e. volume of traffic entering and leaving

the model cordon) was applied based on the forecast data from TII’s NTM module of the National

Transport Model (NTpM). Furthermore, the forecasts based on KCC’s data were compared to

those generated by the NTM.

5.5 Trip Rates

Trip Rates for of the land use types as specified in the future land use matrix were sourced from

the TRICs database and Trip Rates synthesised by AECOM for use in similar land use and

transport studies. Details of these trip rates are provided in Table 5.6 below.

Table 5.6 – Maynooth Land Use Trip Rates

Land Use Setting PT Accessibility

AM Peak (08:00

–09:00)

PM Peak

(17:00 – 18:00)

In Out In Out

Residential

(per unit)

Semi-D Suburban / Out

of Town Low / None 0.15 0.38 0.38 0.20

Mixed Suburban / Edge

of Town Medium 0.14 0.34 0.35 0.18

Office

(per employee)

Business Park

Low / None 0.30 0.04 0.04 0.25

Business Park

Medium 0.20 0.03 0.03 0.17

Industrial

(per employee) Edge of town Low/None 0.27 0.07 0.06 0.34

Warehousing

(per employee) Edge of town Low/None 0.22 0.11 0.11 0.20

Community

(per hectare) - - 9.61 7.85 21.91 20.92

Secondary School

(per pupil)

Urban (1,000 pupils per

school) n/a 0.10 0.07 0.01 0.02

In order to estimate the additional traffic in 2021 and 2031, the AM/PM arrival/departure trip rates

presented in Table 5.6 above are applied to the number of projected residential units (for

residential land-use), to the projected number of employees (for all employment type land-uses), to

the number of pupils (for the proposed secondary schools) and to the number of hectares (for

community development proposals).

5.6 Maynooth Area Additional AM / PM Trips

The additional traffic generated by each of the Maynooth STM zones as a result of the zoning

objectives of the Maynooth LAP 2013 to 2019 and the Draft Kildare CDP 2017 – 2023 and the

quanta of land use specified by KCC are presented in Table 5.7 (2016 to 2021 additional trips) and

Table 5.8 (2016 to 2031 additional trips).

Table 5.7 – 2021 Trip Generation Estimates

STM Zone Number AM Departures AM Arrivals PM Departures PM Arrivals

Total 780 862 767 643



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Table 5.8 – 2031 Trip Generation Estimates

STM Zone Number AM Departures AM Arrivals PM Departures PM Arrivals

Total 1529 2045 1956 1381

The resultant additional trip generation (presented in Tables 5.7 and 5.8) were then added to

known 2016 traffic data for Maynooth in order to develop future demand origin and destination trip

ends for 2021 and 2031. Future year demand for external zones was assumed to be the same as

that given by TII’s NTM.

5.5 Allocation & Distribution of Future Growth

The additional trips for 2021 and 2031 were added to the base year (2016) known trip ends. Future

year trip distribution was undertaken utilising the furnessing distribution method. In order to carry

out the trip distribution process, it was first necessary to ‘seed’ the cells with no trips in the base

year matrices with very small numbers (0.01 vehicles) to allow for future year trips between those

specific cells. Otherwise any cell with a zero will remain zero irrespective of the factor applied. As

part of the trip distribution process the matrix totals were doubly constrained to the mean of the

forecast trip ends totals. The distribution of these trips was then based on that of the existing sub

zone or if the land use type had been updated significantly, a neighbouring zone of existing land

use type comparable to that of the updated zone.

5.6 Comparison of KCC Forecast to ERM and NTM

In order to ensure a robust forecasting approach was utilised in line with other similar projects the

trip generation estimates outlined in the tables above were compared to growth forecasts

contained in TII’s NTM and the NTA’s ERM.

Since the zone structure of the Maynooth STM is compatible with TII’s NTM the NTA’s ERM by

definition it was possible to compare the overall future light matrix totals based on the KCC, NTM

and ERM forecasts. The 2021 and 2031 forecasts for the NTM and ERM were based on a linear

interpolation of the demand in zones related to the Maynooth STM between the base year and

future year models. A per annum percentage growth rate was established from the examination of

the NTM and ERM linear interpolations and applied to develop 2021 and 2031 Maynooth STM

forecasts based on NTM and ERM forecasts respectively. Table 5.9 below outlines a comparison

of the NTM, ERM and KCC growth forecasts for Maynooth.



Page 56

Table 5.9 – Comparison of KCC Forecast to NTM and ERM Forecasts (LV)

Growth 2016 2021 2031

Growth

2016 – 2021

Growth

2016 - 2031

AM PM AM PM AM PM AM PM AM PM

KCC 16,532 17,142 18,490 18,999 22,237 22,782 11.8% 10.8% 34.5% 32.9%

NTM 16,532 17,142 18,079 18,737 21,772 22,545 9.4% 9.3% 31.7% 31.5%

ERM 16,532 17,142 17,717 18,513 20,748 21,851 7.2% 8.0% 25.5% 27.5%

Figure 5.2 and Figure 5.3 below compares the AM and PM matrix totals generated by each of the

growth forecasts for light vehicles. There is a clear correspondence between the KCC and TII

forecasts with the KCC forecast producing slightly higher growth overall (refer to Table 5.9).

Figure 5.2: Comparison of the KCC, NTM and ERM forecast for the AM Peak Period (LV)

16000

17000

18000

19000

20000

21000

22000

23000

24000

2016 2021 2031

Matr

ix T

ota

l

Year

KCC NTM ERM



Page 57

Figure 5.3: Comparison of the KCC, NTM and ERM forecast for the PM Peak Period (LV)

Table 5.10 below provides the future heavy vehicle (HV) matrix totals based on the KCC, NTM

and ERM forecasts. Once again the KCC forecasts closely correspond to the NTM and ERM

forecasts.

Table 5.10 – Comparison of KCC Forecast to NTM and ERM Forecasts (HV)

Growth

Forecast

2016 2021 2031 Growth

2016 – 2021

Growth

2016 - 2031

AM PM AM PM AM PM AM PM AM PM

KCC 944 944 1152 1141 1673 1652 22.0% 20.8% 77.3% 75.1%

NTM 944 944 1116 1116 1656 1656 18.2% 18.2% 75.4% 75.4%

ERM 944 944 1165 1068 2183 1585 23.4% 13.2% 131.3% 67.9%

The total growth in the Maynooth STM is based on the development zones and land use types

identified by KCC – the outcome of this process shows a good correspondence with the both TII’s

NTM and the NTA’s ERM growth forecasts as identified above. However based on KCC’s local

knowledge and close correspondence with both TII’s and the NTA’s forecast in the Maynooth

region, it was determined that KCC’s forecast was the most appropriate forecast to proceed with.

As a result, 2021 and 2031 demand matrices were developed based on the KCC forecast. Due to

the close correspondence between the zone structure of the Maynooth STM and the ERM, any

demand impacts associated with public transport proposals may be accounted for by applying a

percentage change in the forecast trip ends.

5.7 Future Year Matrix Analysis

The PAG requires a quantitative assessment of the impact of the traffic forecasting process to be

undertaken upon the following criteria:

Trip Length Distribution;

Trip End Growth; and

16000

17000

18000

19000

20000

21000

22000

23000

24000

2016 2021 2031

Matr

ix T

ota

l

Year

KCC NTM ERM



Page 58

Zone to Zone Growth.

5.7.1 Trip Length Distribution

Trip Length Distribution (TLD) graphs for the AM Peak and PM Peak (Light Vehicles) are illustrated

below for the KCC growth scenario. The figures compare the TLD in the 2016 Base Year models

and the 2031 Future Year Growth Do-Minimum models.

The purpose of comparing the TLD in the base and future year models is to assess the impact of

the trip distribution (furnessing) process. The proportions of trips in the various distance bands

should be similar between the base and future years. TLD graphs for AM Peak, Inter Peak and PM

Peak are shown respectively in Figures 5.4 and 5.5 below.

Figure 5.4 - AM Peak TLD (LV)

0

0.05

0.1

0.15

0.2

Pro

po

rtio

n o

f T

rip

s

Trip Length (km)

AM Peak 2016

AM Peak 2031



Page 59

Figure 5.5 - PM Peak TLD (LV)

Overall the TLD is similar between the Base and Design Year models in the AM and PM peak;

however some minor changes were noted as a result of the trip distribution process. It was noted

that short distance trips in the distance band 0 km to 2 km decreased in the AM and PM peaks and

that trips in the distance band 6 km to 8 km increased and 10 to 12 km in each of the peaks.

Checks were undertaken on these distance bands to ascertain the reasons for the increases in trip

volumes. In these distance bands the decrease in shorter distance trips in the distance band 0 km

to 2 km and the increase in trips from 6 to 8km in the AM and PM peak periods occurred as a result

of the forecast future land use growth in internal model zones as specified by KCC. The increase in

trips in the distance band 10 km to 12 km occurred as a result of increased growth forecast

increases in external to external zone growth as predicted by the NTM. The changes in the

distance bands were considered acceptable given the forecast future network conditions.

5.7.2 Trip End Growth

An assessment of the Trip End Growth (TEG) between the Base and Design Year demand in the

AM and PM Peak was undertaken to assess if there were any significant changes in demand at trip

end level when compared to the overall growth between the Base and Design Year demand.

The PAG guidance on the GEH statistic indicates that any GEH statistic above 10 warrants further

investigation. Of the 11 external zones 9 have a GEH greater than 10. This is reasonable as they

are large zones connecting to adjacent towns.

A total of 9 out of 45 internal zones in the model exceeded a GEH statistic of 10; these zones are

presented in Table 5.11 below. These zones were investigated to ascertain the reasons for the

large increases in growth in these zones. It was noted all cases that the large increase in growth

occurred as a forecast future land use in the zones. The larger growth predicted in these zones

was therefore considered acceptable given the forecast future network conditions.

0

0.05

0.1

0.15

0.2P

rop

ort

ion

of

Tri

ps

Trip Length (km)

AM Peak 2016

AM Peak 2031



Page 60

Table 5.11 - Model Calibration Criteria: Zones with TLD GEH Values above 10

Zone Future Land use Forecast (KCC)

490005 Maynooth University to increase from 9,000 to 18,000 students

490006 Residential zone, Population increase of 649



490014 Planning permission 13/828 granted for two post primary schools with capacity for 2,000 pupils



490021 3.2ha zoned for Office/light industry/warehousing & 2.9ha site zoned Office


5.7.3 Zone to Zone Growth

The same procedure for TEG was also undertaken for zone to zone growth. The GEH statistic for

each origin-destination pair was assessed to show any significant outliers or issues in the AM Peak

and PM Peak demand. In the AM Peak and PM Peak 0.6% of zone to zone growth had a GEH

greater than 10. These zones were further investigated. All of these instances were external zones

and zones with increased demand shown in Table 5.11 above.



Page 61

Chapter 6

Future Year Scenario Assessment



Page 62

6 Future Year Scenario Assessment

6.1 Maynooth LAP Roads Objectives

The function of the Maynooth STM is to act as a tool that KCC can use to assess the relative

merits of the provision of new link roads and other infrastructure improvements within Maynooth

and of land use changes and associated traffic demand on the existing transport network in

Maynooth.

Within the Section 7.5.3 of the Maynooth LAP 2013 to 2019 a suite of Roads Objectives are

referenced, namely:

TRO 1: To carry out a study investigating the safety and capacity of the existing Straffan Road

M4 Interchange to establish whether an upgrade or new interchange working in tandem with

the existing one is required. In the event that a new interchange is required the location shall

be identified together with connections to the existing and proposed non-national road

network.

TRO 2: To facilitate the future construction of the following roads and in the interim protect

these routes from development:

a) Between the Straffan Road (A) and the Celbridge Road (B)

b) Between the Moyglare Road (C) and the County Boundary (D) (only a small section of

this road to the County Boundary has to be completed)

c) Between the Celbridge Road (B) and the Leixlip Road (E)

d) Between the Kilcock Road (F) and the Moyglare Road (C)

e) Between the Kilcock Road (F) and the Rathcoffey Road (G)

f) Between the Rathcoffey Road (G) and the Straffan Road (A)

g) Between the Dunboyne Road (H) and the Moyglare Road (I)

h) A new Street that will connect the Straffan Road (J) with Leinster Street (K) and onto

Parson Street (L)

TRO 3: To carry out the following road realignments and improvements at:

a) Sharp bend on Convent Lane

b) Along the Rathcoffey Road between the town boundary and Bond Bridge, where

necessary

c) Along sections of the Dunboyne Road

d) Pound Lane

e) Moneycooley Road

f) Kilcock road at Laraghbyran

g) Roundabout at Maynooth Business Park

h) Beaufield road, Rathcoffey road junction

i) Meadowbrook link road and the Straffan Road junction

TRO 4: To provide passive traffic calming measures throughout the town of Maynooth

where necessary, as funding allows.



Page 63

TRO 5: To carry out the following in relation to car parking:

a) Provide distinctly coloured disabled car parking spaces at appropriate locations

throughout the town.

b) Investigate the provision of additional off street public car parking in the town

centre.

c) Ensure the provision of permanent durable surfaces to all public and private car-

parking facilities.

d) Ensure adequate car parking spaces are provided in all new developments with

suitably sized oil/water interceptors

TRO 6: To ensure that the objectives of the Maynooth Traffic Management Plan (once

adopted) are delivered.

TRO 7: To include all signalised junction installations within the SCOOT/UTC system in place

within the area of the plan

Of the above mentioned objectives those mentioned under noted under objective TRO 2 constitute

new roads objectives. These new roads objectives are shown graphically in Figure 6.1 overleaf.

In order to assess the relative merits of the provision of these new roads AECOM worked with KCC

to develop three future year Do Something scenarios which were assessed in the Maynooth STM

2021 and 2031 future year models. The future year Do Something scenarios assessed comprised

varying combinations of the TRO 2 new roads objectives and are outlined in the following sections

of this report.



Page 64

Figure 6.1: Maynooth LAP New Roads Objectives

AECOM Traffic Management Plan and Traffic Model for Maynooth

Kildare County Council Traffic Modelling Report – Base Year

Page 65

6.2 Future Year Scenarios Assessed

In assessing potential Do Something scenarios it is necessary to assess the range of Do

Something Scenarios against a baseline Do Nothing or Do Minimum Scenario. The Do Minimum

Scenario in this case was taken to be the existing road network with no improvement beyond

general maintenance.

Three potential Do Something scenarios were assessed. Do Something Scenarios 1 & 2 were

developed to assess the relative merits of constructing either an eastern or western of the Royal

Canal and Maynooth Rail Line. The Do Something 1 & 2 scenarios comprised varying

combinations of TRO 2 objectives (a) to (f). A third scenario, Do Something 3, was also developed

which assessed the merits of progressing the TRO 2 short term objectives (g) and (h).

Further detail on the Do Minimum Scenario and Do Something Scenarios are discussed in the

following sections.

6.3 Do-Minimum Network

A future year ‘Do-Minimum’ network should include the existing road network plus any committed

infrastructure improvements in the study area. As there are no significant road improvements

committed within the study area, the ‘Do-Minimum’ future network for the Maynooth Traffic

Management Plan consists of the existing road network, which is assumed to be maintained over

time.

6.4 Do Something Networks

Three scenarios were developed for assessment in the future year 2021 and 2031 models, namely:

Scenario 1 – Long Term Objectives – Progression of Eastern Orbital Route

Scenario 2 – Long Term Objectives – Progression of Western Orbital Route

Scenario 3 – Short Term Objectives

These options were modelled and assessed through the Maynooth STM’s. In assessing the

relative benefits of each option network statistics were extracted from the traffic models for each

scenario and a comparison was made between the Do-Minimum and the Do-Something Options

under consideration. The key network statistics comprised the following:

Total Network Travel Time (hours) for all vehicles;

Total Network Vehicle Kilometres (hrs) for all vehicles; and

Total Delay (hrs)

The three Do Something scenarios are detailed below.

6.4.1 Do Something Scenario 01 – Long Term Objectives –Eastern Orbital Route

Do Something Scenario 1 provides an Eastern Orbital Route beginning north of the Royal Canal on

the R148 Kilcock Road. The route provides a link from the R148 to the Moyglare Road north of

Maynooth University. The proposed road then continues eastwards joining with the R157 and

traveling southwards down to the R148 Leixlip Road. This scenario involves an eastern crossing of

the Royal Canal and Maynooth Rail Line connecting up with the R405. The final link of the Eastern

Orbital Route is a link form the R405 to the R406 north of the M4/R406 interchange. This final link



Page 66

is included in all Do Something modelled scenarios. Figure 6.2 below outlines the potential Eastern

Orbital Route assessed.

Figure 6.2 – Do Something Scenario 01 – Eastern Orbital Route



Page 67

6.4.2 Do Something Scenario 02 – Long Term Objectives –Western Orbital Route

Do Something Scenario 02 provides a Western Orbital Route and contains the same upgrades as

Scenario 01 from the R148 Kilcock Road connecting back to the R148 Leixlip Road. New links are

proposed from the R148 Kilcock Road to the R408 Rathcoffey Road and continuing on adjacent to

the M4 to link up with the R406 Straffan Road. Again the link from Straffan Road to the R405 is

modelled in this scenario. Figure 6.3 below outlines the potential Western Orbital Route assessed.

The results of the network statistics were compared for Scenario 01 and 02 to assess the relative

merits of constructing an eastern or western crossing of the Royal Canal and Maynooth Rail Line.

Figure 6.3 – Do Something Scenario 02 – Western Orbital Route



Page 68

6.4.3 Do Something Scenario 03 – Short Term Objectives

Do Something Scenario 03 assessed the shorter term TRO 2 objectives. A link from the Straffan

Road (R406) to the Celbridge Road (R405) is provided as in Do Something Scenarios 01 and 02.

An additional proposed link from Moyglare Road to Dunboyne Road is provided to alleviate the

amount of traffic passing through the town centre. Figure 6.4 below outlines the shorter term

objectives.

Figure 6.4 - Scenario 03 – Short Term Objectives



Page 69

6.5 Results

The following sections outline individually the results the analysis of each of the Do Something

Scenarios 01, 02 and 03 versus the Do Minimum scenarios in each of the future year 2021 and

2031 models. The assessment of the benefits of each scenario was developed based on the

impacts on the network performance parameters:

Total Network Travel Time (hours) for all vehicles;


Total Delay (hrs)

In addition to the network performance parameter assessment, volume difference plots were also

examined for each option versus the Do Minimum scenario. The figures below show difference

plots for each scheme. Traffic increases on road sections are represented in red whilst decreases

on particular road sections are shown in green.

A further comparison has also been undertaken in addition to the individual assessments. The

network performance parameters from the Do Something Scenarios 01 and 02, have been

compared to assess the relative merits of constructing an either and eastern or western crossing of

the Royal Canal and Maynooth Rail Line.

6.5.1 Do Something Scenario 01 Results

Figure 6.5 below presents the volume difference plot of Do Something Scenario 01 (Eastern Orbital

Route) versus the Do Minimum Scenario.

Figure 6.5 – Difference Plot 2021 – Do Something Scenario 01 vs Do Minimum

The proposed of the Eastern Orbital Route scheme is seen to provide significant benefits to the

local road network providing a level of congestion relief to nearly all of the main radial routes

leading into Maynooth, namely:

The R406 (Straffan Road);

The R148 (Kilcock and Leixlip Roads);

The R405 (Celbridge Road); and

The Moyglare Road



Page 70

Tables 6.1 to 6.4 below present the results of the network performance statistics analysis of Do

Something Scenario 01 (Eastern Orbital Route) versus the Do Minimum Scenario. The network

performance statistics analysis confirms that the Eastern Orbital Route would have a positive

impact on network performance with total network travel time and congestion related delay reduced

in both the AM and PM peak hours.

Table 6.1 – Do Something Scenario 01 Network Statistics – AM Peak 2021

Scenario Total Network

Trips

Total Distance

(km)

Total Travel

Time (hrs) Total Delay (hrs)

2021 DM AM 19,641 171,864 3,387 799

2021 DS1 AM 19,641 171,275 3,188 629

% change relative to Do Min

n/a 0.3% 5.9% 21.2%

Table 6.2 – Do Something Scenario 01 Network Statistics – PM Peak 2021

Scenario Total Network

Trips

Total Distance

(km)

Total Travel

Time (hrs) Total Delay (hrs)

2021 DM PM 20,140 175,459 3,423 789

2021 DS1 PM 20,140 174,911 3,282 674


n/a 0.3% 4.1% 14.6%


Scenario Total Trips (Vehs/hr)

Total Distance (km)

Total Travel Time (hrs)

Total Delay (hrs)

2031 DM AM 23,892 213,620 4,646 1,360

2031 DS1 AM 23,892 210,547 4,364 1,140


n/a 1.4% 6.1% 16.1%



Total Distance (km)


Total Delay (hrs)

2031 DM PM 24,435 217,206 4,757 1,414

2031 DS1 PM 24,435 214,582 4,515 1,225


n/a 1.2% 5.1% 13.4%



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6.5.2 Do Something Scenario 02

Figure 6.6 below presents the volume difference plot of Do Something Scenario 02 (Western

Orbital Route) versus the Do Minimum Scenario.


The proposed of the Western Orbital Route scheme is seen to provide significant benefits to the

local road network providing a level of congestion relief to all of the main radial routes leading into

Maynooth, namely:


The R408 (Rathcoffey Road);



The Moyglare Road


Something Scenario 02 (Western Orbital Route) versus the Do Minimum Scenario. Again the

network performance statistics analysis confirms that the Western Orbital Route would have a

positive impact on network performance with total network travel time and congestion related delay

recused in both the AM and PM peak hours. The Western Orbital Route is seen to provide more

congestion relief overall than the Eastern Orbital Route.



Total Distance (km)


Total Delay (hrs)

2021 DM AM 19,641 171,864 3,387 799

2021 DS2 AM 19,641 169,903 3,165 600


n/a 1.1% 6.6% 24.8%



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Total Distance (km)


Total Delay (hrs)

2021 DM PM 20,140 175,459 3,423 789

2021 DS2 PM 20,140 173,055 3,252 635


n/a 1.4% 5.0% 19.6%



Total Distance (km)


Total Delay (hrs)

2031 DM AM 23,892 213,620 4,646 1,360

2031 DS2 AM 23,892 209,536 4,279 1,047


n/a 1.9% 7.9% 23.0%



Total Distance (km)


Total Delay (hrs)

2031 DM PM 24,435 217,206 4,757 1,414

2031 DS2 PM 24,435 213,630 4,420 1,120


n/a 1.6% 7.1% 20.8%

6.5.3 Do Something Scenario 03 Results

Figure 6.7 below presents the volume difference plot of Do Something Scenario 03 (Shorter Term

Objectives) versus the Do Minimum Scenario.


The proposed short term objectives are seen to provide benefits to the local road network providing

a level of congestion relief to all of the following radial routes leading into Maynooth, namely:

The R148 (Leixlip Road);




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The Moyglare Road


Something Scenario 03 (Shorter Term Objectives) versus the Do Minimum Scenario. The network

performance statistics analysis confirms that the proposed scheme would have a positive impact

on network performance with total network travel time and congestion related delay recused in both

the AM and PM peak hours. The short term objectives do not however provide as significant a level

of benefit as either the Eastern or Western Orbital Routes.`



Total Distance (km)


Total Delay (hrs)

2021 DM AM 19,641 171,864 3,387 799

2021 DS3 AM 19,641 171,276 3,302 719


n/a 0.3% 2.5% 10.0%



Total Distance (km)


Total Delay (hrs)

2021 DM PM 20,140 175,459 3,423 789

2021 DS3 PM 20,140 174,796 3,357 727


n/a 0.4% 1.9% 7.9%



Total Distance (km)


Total Delay (hrs)

2031 DM AM 23,892 213,620 4,646 1,360

2031 DS3 AM 23,892 210,875 4,555 1,298


n/a 1.3% 2.0% 4.5%



Total Distance (km)


Total Delay (hrs)

2031 DM PM 24,435 217,206 4,757 1,414

2031 DS3 PM 24,435 215,011 4,652 1,329


n/a 1.0% 2.2% 6.0%



Page 74

6.5.4 Do Something Scenario 01 versus Do Something 02

A further comparison has also been undertaken in addition to the individual assessments, the

network performance parameters from the Do Something Scenarios 01 and 02, have been

compared to assess the relative merits of constructing an either and eastern or western crossing of

the Royal Canal and Maynooth Rail Line.

Figures 6.8 and 6.9 below graphically present a comparison of the total travel time and total delay

savings relative to the Do Minimum Scenario for the Do Something Scenarios 01 and 02 for the

future years 2021 and 2031.

Figure 6.8 – 2021 Total Network Travel Time & Delay Savings – Scenario 01 vs Scenario 02

-

50

100

150

200

250

2021 DS1 AM 2021 DS2 AM 2021 DS1 PM 2021 DS2 PM

Total Travel Time (hrs) Total Delay (hrs)



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Figure 6.9 – 2031 Total Network Travel Time & Delay Savings – Scenario 01 vs Scenario 02

As can be seen from both Figures 6.8 and 6.9 whilst both Do Something Scenario 01 and 02

present significant travel time and delay savings, relative to the Do Minimum scenario, Do

Something Scenario 02 (Western Orbital Route) is seen to deliver a greater level of travel time

savings.

The results however should be viewed in the context of the impact they have on the radial routes

feeding into Maynooth and streets with Maynooth’s town centre. As discussed in Sections 6.5.1

and 6.5.2 above Do Something Scenario 01 (Eastern Orbital Route) provides relief to the following

radial routes:




The Moyglare Road

Whilst Do Something Scenario 02 (Western Orbital Route) provides relief to the below list of radial

routes:


The R408 (Rathcoffey Road);



The Moyglare Road

Do Something Scenario 02 therefore provides relief to all the radial links that Do Something

Scenario 01 benefits and additionally provides relief to the R408 (Rathcoffey Road). However it is

necessary to examine Figures 6.10 and 6.11 below, which outline the volume to capacity ratio on

all key road links, to determine where congestion relief is required on the network. As can be seen

-

50

100

150

200

250

300

350

400

2031 DS1 AM 2031 DS2 AM 2031 DS1 PM 2031 DS2 PM

Total Travel Time (hrs) Total Delay (hrs)



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in Figure 6.10 and 6.11 below, by 2021 capacity issues are not forecast on the R408 (Rathcoffey

Road).

Figure 6.10 – 2021 Do Minimum AM Volume to Capacity Ratio on Road Links Maynooth

Figure 6.11 – 2021 Do Minimum PM Volume to Capacity Ratio on Road Links Maynooth

R405 Celbridge Road

R408 Rathcoffey Road

R148 Kilcock Road

R148 Leixlip Road

M4

M4

M4

M4


R406 Straffan Road

R406 Straffan Road

Moyglare Road

Moyglare Road

R148 Leixlip Road

R148 Kilcock Road

R405 Celbridge Road

M4 / R406

Interchange

M4 / R406

Interchange



Page 77

In examining Figures 6.10 and 6.11 above it can be seen that capacity issues are not forecast on

the R408 during either the AM or PM peak hours by 2021. Rather congestion is forecast on the:

R406 Straffan Road;

The Moyglare Road;

The M4; and

The M4 / R406 Interchange

Figures 6.12 and 6.13 below outline the volume to capacity ratio on all key road links upon the

implementation of Do Something Scenario 01 (Eastern Orbital Route). It can be seen that there are

notable improvement in the volume to capacity ratio on the:

R406 Straffan Road;

The Moyglare Road; and

Sections of the M4.

Capacity issues however still remain on at the M4 / R406 Interchange in the PM peak.

Figure 6.12 – 2021 Do Something 01 AM Volume to Capacity Ratio on Road Links Maynooth

M4 / R406

Interchange

M4

M4

R148 Kilcock Road

Moyglare Road

R405 Celbridge Road

R148 Leixlip Road R408 Rathcoffey Road

R406 Straffan Road



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Figure 6.13 – 2021 Do Something 01 PM Volume to Capacity Ratio on Road Links Maynooth

Figures 6.14 and 6.15 overleaf outline the volume to capacity ratio on all key road links upon the

implementation of Do Something Scenario 02 (Western Orbital Route). It can be seen that there

are notable improvement in the volume to capacity ratio on the:

R406 Straffan Road;

The Moyglare Road; and

Sections of the M4.

However capacity however still remain on at the M4 / R406 Interchange in the PM peak and the

progression of the Western Orbital Route is seen to increase traffic flow through the M4 / R406

Interchange in the AM peak hour. The progression of the Western Orbital Route would therefore

necessitate improvements in capacity at the M4 / R406 Interchange.

M4 / R406

Interchange

M4

M4

R148 Kilcock Road

Moyglare Road

R405 Celbridge Road

R148 Leixlip Road


R406 Straffan Road



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Figure 6.11 – 2021 Do Something 02 AM Volume to Capacity Ratio on Road Links Maynooth

Figure 6.15 – 2021 Do Something 02 PM Volume to Capacity Ratio on Road Links Maynooth

M4 / R406

Interchange

M4 / R406

Interchange

M4

M4

M4

M4

R148 Kilcock Road

R148 Kilcock Road

Moyglare Road

Moyglare Road

R405 Celbridge Road

R405 Celbridge Road

R148 Leixlip Road

R148 Leixlip Road



R406 Straffan Road

R406 Straffan Road



Page 80

Chapter 7

Conclusion



Page 81

7 Conclusion

7.1 Conclusion

The aim of KCC in developing the Maynooth Strategic Traffic Model (STM) was to develop a tool

that accurately represents existing traffic conditions in Maynooth and that can be used by KCC to

assess the impacts of major land-use changes and transport network infrastructural improvements

in the Maynooth Area and its environs. It was a requirement of the commission that the Maynooth

STM should be compatible, at a zonal level, with the both Transport Infrastructure Ireland’s (TII’s)

National Transport Model (NTpM) and the National Transport Authorities (NTA’s) Eastern Regional

Model (ERM).

The Maynooth STM has therefore been developed in the software VISUM as a cordon of the

National Traffic Model (NTM) element of the NTpM. The zone structure in the STM has been

developed in such as fashion that it maintains compatibility with the NTM and ERM zone

structures. Therefore any demand impacts associated with public transport proposals or large

infrastructural changes assessed in the NTpM or ERM can easily be accounted for in the Maynooth

STM by applying a percentage change in the forecast trip ends in the zones local to Maynooth in

the larger models to the Maynooth STM zones.

Prior to the development of the Maynooth STM a significant collection programme which included

link counts, junction turning movement counts, origin-destination surveys and journey time surveys

was carried out in May 2016. This data has been used to fully calibrate and validate AM and PM

peak hour models for Maynooth to the standard recommended in the PAG Unit 5.2: Construction of

Transport Models.

Upon completion of the 2016 base year model future year forecast models for 2021 and 2031 were

developed. The forecast models were developed based on KCC’s forecasts for the Maynooth area

as outlined in the Maynooth Local Area Plan 2013 to 2019 and the Draft Kildare County

Development Plan (CDP) 2017 – 2023. In order to sense check the forecasts developed based on

KCC’s projections a comparison was made between the forecasts based on KCC’s projections and

forecasts developed based on the projections in the NTpM and the ERM future year models. The

KCC forecasts were found to closely correspond to the NTM and ERM forecasts and based on

KCC’s local knowledge it was considered appropriate that the future year forecasts based on

KCC’s projections were taken forward for future year scenario assessment.

Three future year scenarios were then developed for assessment in the future year 2021 and 2031

models, namely:

Scenario 01 –Progression of Eastern Orbital Route

Scenario 02 –Progression of Western Orbital Route

Scenario 03 – Short Term Objectives

These scenarios were developed based on the future road construction objectives outlined in TRO

2 of the Maynooth Local Area Plan 2013 to 2019. These future year scenarios were then assessed

based on their impacts on the network performance parameters:

Total Network Travel Time (hours);


Total Delay (hrs)



Page 82

Each of the future year scenarios were found to deliver improved levels of network performance

with Scenario’s 01 and 02 delivering the most significant levels of network performance

improvement.

A further comparison of Scenario’s 01 and 02 was then undertaken. Scenario 02 (the Western

Orbital Route) was found to deliver the most significant level of network improvement of all the

scenarios assessed. This scenario however attracts more traffic through the already congested M4

/ R406 Interchange and the progression of the Western Orbital Route would therefore necessitate

improvements in capacity at the M4 / R406 Interchange.



Page 83

Appendices