Christchurch (NZ) Transport Model Update – A Moving Feast

Julie Ballantyne

Christchurch

Largest city in South Island Third largest city in NZ Population, 425k Transport:

International Airport Large Port (inland ports) Flat terrain – cycle-friendly Bus system (central focus) Car travel dominates (>80%)

4 Stage Model (land use ---> travel) Uses:

Infrastructure/PT system assessments Demands for lower tiered models

Owned by regional/local Govt agencies Calibrated to 2006 4 Stage Models checked every 5 years Validation check planned after 2011 (Census)

Christchurch Transportation Model (CTM)

But then…..

Earthquakes, 2010-2011 Half roads suffered some damage CBD

Closed, businesses forced to relocate Over 1000 buildings (1/3) demolished

Residential Significant damage in east

Census delayed to 2013 Rebuild still ongoing

The Project

Check the CTM predictions for 2013 against observedHow is the model performing?Model inputs:

Land use from 2013 Census Transport network – roads & intersections Transport network – bus system

Normally straight-forward but……

The Challenge

Massive shift in land use distribution

Roadworks still prevalent in 2013

2015 hub-and-spoke buses on 2013 network

Had to work with data available

Lots of traffic counts –> lots of processing

Software update => results change

Change to the Landscape - Residential

Waimakariri

Selwyn

Change to the Landscape - Residential

River corridor

Hill suburbs

Change to the Landscape - Business

Change to the Landscape - Business

CBD

Road Network

Road Network – Road Works

Road Network – Road Works

Road Network - Closures

Bus Network Bus exchange

Temporary 2013 New 2015

Bus routes: Through routes 2013 Hub-and-spoke 2015

Change in road directions

Network - 2006

Network - 2013

Network - 2015

Traffic Counts

Link counts required on screenlines Significant amount of data available But ….

Not processed (raw files, not geo-referenced) Processing/mapping significant (and tedious) task Inconsistent formats – more manual intervention Directional discrepancies

Traffic Counts – Lessons

Never underestimate data processing required

Model useful tool to check counts

Significant gaps in screenlines… …but no point counting in some areas (road

works/red zones) Solution:

Include factored old counts to complete the screenlines

Traffic Counts – Mind the Gap

Traffic Counts

Validation - Targets

Validation Data

Vehicle travel times

PT Boardings (2015)

Census Journey-to-Work

Traffic counts

Model Performance – Travel Times

Model Performance – Travel Times

AM IP PM

Model Performance – PT BoardingsAM – Corridor by Destination

Model Performance – Counts

Total Vehicles GEH Criteria AM IP PM ON Daily

% Screenlines with GEH<5 > 60% 59% 55% 64% 82% 86%<7.5 > 75% 73% 82% 77% 91% 91%<10 > 90% 73% 91% 77% 100% 95%

% Links with GEH

<5 >= 65% 52% 66% 49% 82% 68%<7.5 >= 75% 72% 80% 66% 96% 87%<10 >= 85% 83% 92% 79% 97% 94%<12 >= 95% 92% 97% 88% 100% 97%

RMSE 30% 32% 30% 40% 47% 29%

Model Performance – Counts

Model Performance - JTW

Model Performance - JTW

Census JTW Model HBW

Summary

Significant changes in Christchurch Variation in counts – model used to identify

outliers The model:

CTM outputs checked using 2013/15 observed CTM performing well

Next challenge: Ongoing monitoring of changing land use patterns