Macroscopic and Microscopic SimulationMacroscopic and Microscopic SimulationMacroscopic and Microscopic SimulationMacroscopic and Microscopic Simulation

for the for the for the for the EEEEvaluation of People Mover Systemvaluation of People Mover Systemvaluation of People Mover Systemvaluation of People Mover Systemssss

Dr.-Ing. Peter Mott

Sven Beller

PTV AG, Karlsruhe, Germany

1. 1. 1. 1. IntroductionIntroductionIntroductionIntroduction

This paper is intended to show how a comprehensive transportation planning

system can be used to analyse the impact of a People Mover or Personal

Rapid Transit (PRT) system on traffic and transportation operations. Both

systems use comparatively small driverless vehicles which are controlled

automatically.

Based on two examples we demonstrate the benefits of macroscopic planning

and microscopic simulation of public transport systems:

In the first example the aim is to choose a system that enables the provision of

efficient transport services in a high density area such as a new development

in West Bay area, Doha, Qatar. An underground system will connect this area

with the other parts of the city. A people mover system is planned to be

integrated into the multi-modal transport system in order to serve the high

density area. According to information on existing and future land use, traffic

demand is generated by office buildings, hotels, a congress centre and a

shopping mall in this area. Due to difficult climate conditions, the footpaths

between these origins of traffic and the people mover stations have to be as

short as possible. An important aspect here is to find out how the smaller

vehicles of the people mover system can handle the expected flow emerging

from the high-capacity underground trains.

The second example models and analyses a demand-responsive transport

system (DRT) which means that vehicles are not assigned to fixed routes and

fixed times. DRT matches the service more closely to the customers' needs:

passengers request a journey as soon as they arrive at the pick-up point and

the vehicles will then take them to the desired destination on the shortest

possible route without any intermediate stops. Small vehicles along with a

simple but effective empty vehicle management provide a highly available

transport service. In most situations there are no waiting times for the

passengers. Other transport systems may also be integrated to form a

comprehensive, city-wide, multi-modal transport model for further analysis –

even including private transport modes such as cars and bikes. For clarity, the

other systems are not shown here.

Both examples are modelled and analysed with the transportation planning

software suite PTV Vision. The macroscopic software tool VISUM is used for

the first application and the microscopic application VISSIM is used for the

second one. Among others, these systems provide the following options:

• Detailed representation of public transport services with line routes, detailed timetables and vehicle types allocated to each line route.

• Demand modelling defined in terms of space and time: zone or station based with a passenger volume distributed by time according to variable intervals, e.g. 15 or 30 seconds, one or several hours.

• The macroscopic analysis is based on assignment methods which take both travel demand distribution in terms of time and capacity of individual public transport systems into account.

• Modelling the interaction between vehicles and passengers as part of a multi-modal microscopic simulation.

• Calculation of a wide range of performance indicators from the passenger's and the operator's point of view, such as travel time and waiting time, number of transfers, passenger volume and volume capacity ratio per link etc.

• Option to export a macroscopic model from VISUM for further (microscopic) analysis to VISSIM, hence providing an almost seamless top-down workflow.

2222. . . . The The The The Macroscopic ViewMacroscopic ViewMacroscopic ViewMacroscopic View

The goal in the first example is to assess whether the transport system can

cope with the predicted passenger volumes, in particular regarding the

transfer between the metro and the people mover system. The traffic volumes

are based on estimated passenger flows during the morning peak period

including a temporal distribution with 30-min intervals. The system is defined

by stations, routes, the service frequency and the vehicle size. This

distribution display is parameterised so that changes can be modelled easily.

Figure 1 shows the layout of a north-south metro line (M1) operating every 10

minutes and two people mover lines (PM Red and PM Blue) that depart every

5 minutes. This service covers a total of six stations.

Figure 1: Layout of a Metro and People Mover network

The travel demand is based on the assumption that there are major passenger

flows from the other parts of the city during the morning peak, lasting about

two hours. Additional demand arises from the passengers travelling within the

area only. Figure 2 illustrates the Origin-Destination matrix based on the

network; Figure 3 shows the relative distribution of the demand over time.

Figure 2: Layout of a Metro and People Mover network, superposed by the structure

of the origin-destination matrix

Figure 3: Distribution of passenger demand during the morning peak period

After defining the timetable and the vehicle types including the total number of

seats, it is possible to automatically calculate the line route capacity and the

volume capacity ratio for each link and time interval. In this particular case, the volume capacity ratio per time interval is an

important factor. An even volume assignment during the morning peak period

does not reveal any problems (see Figure 4).

Figure 4: Volume capacity ratio using even volume assignment during morning peak

However, the analysis which is based on time intervals shows the situation to

be quite different: as expected, the load factor soars and the travel demand is

too high on some routes to accommodate the planned number of passengers,

while there is sufficient capacity on alternative routes (see Figure 5).

Figure 5: Volume capacity ratio per time interval to identify transport capacity

bottlenecks on network sections

The inclusion of the volume capacity ratio in the so-called timetable-based

assignment leads to a completely different result: the impedance takes into

account an additional penalty, depending on the volume capacity ratio per link

and time interval. If the volume capacity ratio per route section exceeds the

defined values the impedance on this route is increased. Hence other

connections - if available – become more attractive to passengers. This

approach can be interpreted as controlled guiding of passenger flows to less

busy routes. Hence it is possible to determine the amount of passengers that

can still be managed and to analyse the preferred services in a more realistic

and reliable manner.

Based on the assignment results and the calculation of performance

indicators, the planning program calculates the following indicators used for

system evaluation:

• Passenger volume and capacity utilisation per route, link and time interval, waiting time per stop and travel time from origin to destination

• Performance like no. of vehicles required, vehicle kilometres etc.

• Estimation of operating costs and expected fare revenues.

System analysis based on macroscopic assignment provides more than only

the "big picture" and allows identifying potential bottlenecks in the system over

time. Even capacity restraints in public transport assignment can be taken into

account. For a more detailed assessment of the various processes

determining the overall system performance the microscopic simulation

comes into play. It can also cope with situations where the demand

significantly exceeds the capacity.

3333. . . . The Microscopic ViewThe Microscopic ViewThe Microscopic ViewThe Microscopic View

In contrast to macroscopic models, microscopic models simulate the

movement and interaction of individual entities.

The software package VISSIM is part of the PTV Vision software suite as well

and provides microscopic simulation methods for assessing and solving a

wide range of transportation problems. The heart of VISSIM includes

scientifically approved models for car-following, lane-changing and pedestrian

movements. Simulations include road users, public transport and pedestrians

and their interactions with each other. All is based on an integrated network

model of roads and rails along with their control methods as well as the

pedestrian infrastructure to connect with them. This multi-modal network is

then used by cars, HGVs, buses, trams and trains as well as cyclists and

pedestrians - only to name a few. During the simulation a wide selection of

evaluations are available for online and offline analysis. Another special

characteristic is an animated visualisation in 2D or 3D which offers an instant

comprehension of the simulated traffic situation and also fills the gap between

the technical expertise and a non-technical audience.

3333....1111. Line. Line. Line. Line----Based OperationBased OperationBased OperationBased Operation

Line-based operation is the typical application of public transport in VISSIM.

The essential input data for the microsimulation model includes

• Road/rail infrastructure: tracks/roads (with length, width, gradient), branches and merges (switches/junctions), stations (with platforms), depots (if required)

• Operational data: line allocation (based on routes on the network), departure times (timetable/frequency), vehicle type and capacity, depot capacity

• Passenger volumes: either the desired route relations (origin-destination matrix) or the line-specific passenger volumes at individual stations, and their temporal distribution. If passenger volumes are not available dwell time distributions may be used instead.

Looking at the first example mentioned above, a detailed representation of the

processes at the transfer station is useful in particular, if the number of

passengers currently waiting at the station exceeds the capacity of the next

vehicle. This may happen as a large number of passengers alight from a

metro train at the interchange and the next people mover vehicles arriving

cannot handle all of them instantly. In such a situation, the microscopic system

allows passengers to enter the vehicle until its capacity is reached. The

remaining passengers wait for the next vehicle.

The network used in the first example is exported from the macroscopic model

to the microscopic simulation tool VISSIM. Some further adjustments ensure

that all data is supplied in order to run the simulation. That means that the first

example encompasses both macroscopic simulation of the total system and

microscopic simulation of the processes at the transfer station in order to

precisely calculate the number of passengers affected by the delay and their

waiting times at the transfer points.

3333....2222. Demand. Demand. Demand. Demand----Based OperationBased OperationBased OperationBased Operation

A major benefit of a PRT system is the "freedom of travel", i.e. that vehicles

don't travel on fixed routes with a timetable, but serve the passengers

individually by providing an on-demand service. In contrast to line-based

operation, this challenges the use of standard microscopic simulation software

as different methods and control operations are required. For these purposes

VISSIM offers an application programming interface (API) which allows

expanding its simulation capabilities beyond what comes directly out of the

box. The API offers a wide range of options on how to implement various

external control strategies: It ranges from handing over parameters up to total

control of vehicle movement and PRT system operation. This approach also

allows for applying complex control strategies modelled by an external

system.

The second example is a case study which shows such a demand-based

operation of a PRT system. It covers an area of 500m by 350m and includes

4.7 km of guideways, 17 branches/switches, 7 stations and 1 depot (see

Figure 6 and Figure 7). The main objective of such a model is to analyse and

visualise the PRT operation for variations in temporal and spatial demand as

well as to assess the impact of different control strategies.

Since the operation of such a demand-based model is much more complex

than a line- and timetable based model, some additional information is

required in order to get a realistic model:

• Structural data: Number of vehicles the station can hold, station type, number of berths for boarding and alighting at each station

• Operational data: Dynamic route assignment (depending on the destination), empty vehicle redistribution, demand-based pre-allocation to stations, re-allocation during empty journey, recharging

• Passenger volumes: max. and min. group sizes and their distribution

Figure 6: Structure of the model for the simulation of a demand-responsive PRT

system with vehicles, stations, switches and the depot (2D view)

Figure 7: Structure of the model for the simulation of a demand-responsive PRT

system with vehicles, stations, switches and the depot (3D view)

The vehicle assignment and main

system control is done by scripting

through the VISSIM API. The script

language used for this example is

Visual Basic for Applications (VBA)

using Microsoft Excel as front end.

Here control buttons for loading the

network, running the simulation and

changing some parameters such as

the total number of vehicles in the

system are provided.

During the simulation, in addition to

the visual animation, several program

indicators are shown in Excel for each

station in order to ensure system

integrity and to help trouble-shooting.

One indicator shows for example the

trip demand at each station and how

many vehicles are available to meet

that demand.

The vehicle movements and

interactions are done automatically in

VISSIM with no need for scripting. It

also includes conflict handling, e.g. at

guideway merges.

Figure 8: Excel front end to control the

simulation

The principle of the simulated process is as follows:

• Initially all PRT vehicles (pods) reside in the depot. Then some vehicles are assigned to each station according to the parameter setting of how many free vehicles should ideally be available at each station.

• Passengers who arrive at a station enter their desired destination at the service terminal and request a pickup. Typically, vehicles are available at each station so that there are no waiting times. If not, a free vehicle is sent to the station.

• The selected vehicle receives the information of the passenger’s desired destination. The passenger transport starts immediately after boarding.

• At each guideway branch the vehicle receives the direction information according to its destination so that the vehicle takes the optimum route to its destination.

• During the trip, the vehicle reacts to the other vehicles in the network by considering speeds and necessary time gaps between the vehicles.

• As the vehicle arrives at the destination it proceeds to the drop-off location for passengers to alight.

• The empty vehicle can then be re-scheduled: If there are less empty vehicles than desired, it will stay at this station. If there are enough vehicles, the first vehicle in the queue will return to the depot empty. It can be re-allocated during the trip if a new request for a ride has been submitted from a station along the route or if a station is in need for more empty vehicles.

The time required for boarding and alighting and the departure times result

from the station layout, the number of passengers, operation processes,

walking speeds of pedestrians and their service time at the terminal, where

they enter their destination. If there are always enough vehicles available and

passengers don't arrive in large numbers at the same time then there is

virtually no delay for them to start travelling.

Figure 9: Layout of a station in 2D view. Passengers alight on the left and board on

the right side of the station. The optional window for each vehicle shows technical

data such as current speed during the simulation.

The station layout will become a major factor as soon as large groups of

passengers arrive at a station in order to depart and/or if many vehicles arrive

here at short intervals. Then a station with multiple berths and/or a sawtooth

layout has the advantage of parallel boarding/alighting.

All these parameters can be varied and combined in several scenarios to be

tested. Consequently, several simulation runs are executed evaluating the

proposed scenarios. During each run user-configurable data is collected which

is used to compare and evaluate the scenarios. Typical performance

indicators are:

• From the passenger's point of view: waiting time at the station and journey time from the starting point to the destination.

• From the operator's point of view: number of required vehicles, vehicle kilometres, empty vehicle movements, dwell time at the depot

As an example, the average waiting time at stations has been evaluated to

see the impact of the number of vehicles available in the system as well as the

impact of empty vehicle redistribution. These scenarios were simulated:

• Scenario 1: 30 vehicles in total, 3 free vehicles at each station

• Scenario 2: 40 vehicles in total, 1 free vehicle at each station

• Scenario 3: 40 vehicles in total, 3 free vehicles at each station

Figure 10 shows the average waiting time at each station. The simulated total

passenger demand was chosen to be below capacity. The differences in time

within each scenario result mainly from the different demands at each station.

Most passengers depart from station no. 6 whereas most passengers arrive at

station no. 1.

From the results it is clearly visible that looking only at the total number of

vehicles is not enough to assess a PRT system. The empty car management

is equally important which can be seen especially for the stations with the

highest demand (4, 6 and 7) where the negative impact is much higher for

scenario 2.

The extra 10 vehicles for scenario 3 help to further reduce the waiting time

compared to scenario 1, but even with the situation shown in scenario 1 the

system can operate well - for some stations (2, 5 and 1) there is virtually no

difference in waiting time as compared to scenario 3.

Figure 10: Average waiting time per station for three scenarios. The time needed for

passenger interaction at the terminal is not included here.

One conclusion of this simulation could be that 25% of the money for rolling

stock could be saved if the empty car management is done well.

Other examples for microsimulation assessments could include longer

simulation periods (e.g. an entire day), consider the battery status of the

vehicles, predict station demand by learning from history, include sawtooth-

shaped stations versus in-line stations and of course different control

strategies for vehicle assignment and empty vehicle re-destribution.

When all the simulation work is completed, the animation may be recorded as

a 3D movie so that the results can be visualised and presented, also to a non-

technical audience.

Figure 11: 3D movie recording of the simulation nearby station 3

Figure 12: 3D movie recording of boarding passengers at station 6

3333.3.3.3.3. Multi. Multi. Multi. Multi----Modal OperationModal OperationModal OperationModal Operation

Another interesting application for simulation is a multi-modal transport model.

It offers the entire range of real-world transport: private traffic such as car and

bike, public transport such as trains, trams, buses and PRT and all linkage

between the different modes, even taking into account movements of

pedestrians.

One way of assessing the multi-modal networks is to export a demand model

from VISUM and import it into the microsimulation tool VISSIM. Questions to

be addressed could be:

• What are the average transfer times between a train arrival and the PRT, bus and tram system?

• What would be the total journey time depending on the combination of public transport modes?

• How are the effects of vehicles arriving at "rendezvous" type stations? Will the capacity be sufficient to allow transfer without substantial delays caused by crowding?

A multi-modal network takes care of all the inter-dependencies between the

traffic modes and hence provides a single model for complex assessments.

Therefore it is essential that each mode of traffic and – even more important –

that all interactions between them are modeled realistically. Here the VISSIM

microsimulation provides a profound concept for handling all the traffic modes

including their interactions. As for a PRT system, this kind of interaction rarely

occurs as it usually travels on a guideway which is separated from all other

traffic. However, for systems that share the same space with other traffic (such

as trams or busses) all relevant interaction can be modeled and hence the

resulting transport model is very accurate.

4. 4. 4. 4. ConclusionConclusionConclusionConclusion

The impact of People Mover and PRT systems on traffic can and should be

analysed at a macroscopic and microscopic level.

The planning suite PTV Vision incorporates the two systems VISUM

(macroscopic) and VISSIM (microscopic). An interface between the two

systems allows the export of relevant data from the macroscopic to the

microscopic model. This reduces the time and cost required for data supply if

both systems are used for a specific analysis.

Users of the PTV Vision suite benefit also from its particularly wide range of

features designed to model a variety of public transport applications. At the

same time, it integrates all relevant modes of transport for multi-modal

analysis. The impact of the overall system and its individual components can

therefore be analysed and evaluated from the passenger's and operator's

point of view. Application programming interfaces (API) make the software fit

for the future by providing expansion slots to include handling of non-standard

tasks.

Wrapping it all together, the macroscopicmacroscopicmacroscopicmacroscopic approach is ideal for large networks

and line- and timetable-based systems as it allows analysis of service,

demand and capacity utilisation differentiated according to time.

The mmmmicroscopicicroscopicicroscopicicroscopic analysis is an excellent method for providing a detailed view

on the situation, in particular with regard to operation at or above capacity

limits, demand-dependent control methods and differentiated analysis of traffic

and transportation operations. It also provides a 3D visualization.

In addition to standard tasks in traffic and transport, the presented

transportation planning software also proofs to be a capable and valuable tool

for a wide range of assessments for both people mover and PRT systems.

Applying such a tool contributes to an efficient, straight-forward planning

process and helps cutting investment cost by providing a solid base for

financial decisions.