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EMME/2 Users Conference — October 2003. Data Collection and Model Development in Sarawak, East Malaysia Edwin Hull, TSi Consultants, Burnaby BC and Alastair Burns, Wilbur Smith Associates, Hong Kong. Public Transport. Four private bus companies No operating subsidies

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Emme 2 users conference october 2003
EMME/2 Users Conference — October 2003

Data Collection and Model Development in Sarawak, East Malaysia

Edwin Hull, TSi Consultants, Burnaby BC and Alastair Burns, Wilbur Smith Associates, Hong Kong.


Public transport
Public Transport

  • Four private bus companies

  • No operating subsidies

  • Fares strictly controlled

  • Inadequate revenues to upgrade

  • Old inadequate buses


Public transport1
Public Transport

  • Licensed van service

  • Un-licensed (illegal) van service

  • Tambang (Water Taxis)


Public transport2
Public Transport

  • 30% decline over past five years

  • 11% of total trips

  • Low density development (sprawl)

  • Increasing traffic congestion


Kuching public transport study
Kuching Public Transport Study

  • Long Term (2020) Master Plan

  • Medium Term (2010) Master Plan

  • Short Term Action Plan

  • Maintain & improve PT

  • Address overall transportation system


Kuching public transport study1
Kuching Public Transport Study

  • Develop EMME/2-based Model

  • Calibrate to 2002 Conditions

  • Apply to 2020 and 2010


Data collection
Data Collection

  • Road network inventory

  • PT routes & service characteristics

  • Demographic & Land Use Data

  • Household Interview Surveys

  • Roadside interview surveys

  • Traffic & passenger screenline counts


Household interview survey
HOUSEHOLD INTERVIEW SURVEY

  • 1250 Interview Administered Surveys Randomly Selected from Study Area Population

  • Household Socio-Economic & Travel Characteristics

  • - Purpose of Travel

  • - Frequency & Timing of Trips

  • - Mode of Transport

  • - Origin-Destination Patterns


Other surveys
OTHER SURVEYS

  • Other Vehicle/Passenger Surveys

    - Tambang Passenger Counts

    - Bus Corridor Survey (4 locations)

    - Special Generators [Hospital, Airport & UNIMAS)

    -Taxi/Minibus/Bus Terminal Surveys

  • Attitude Surveys

    - Private Van Talking Point Informal Interview

    - Bus/Minibus/Tambang Passenger Attitude Surveys

    - Hotel Guest Transport Survey



Data problems
Data Problems

  • Bus service discrepancies

  • Low RSI sample

  • Illogical HIS data

  • Significant HIS under-reporting

  • Bus passenger volume reconciliation


Data synthesis
Data Synthesis

Extensive Use of Demand Adjustment and other Techniques to Match Assigned Matrices to Screenline Volumes


4

3

1

2

Screenline & Cordon Locations


Data synthesis1
Data Synthesis

  • Aggregate HIS data to 12 districts

  • Expand by household control totals and generate 24-hour matrices.

  • Develop hourly matrices by mode.

  • Compare with observed counts and develop adjustment factors

  • Expand adjusted matrices to match observed volumes.

  • Develop provisional trip generation equations based on “expanded” data.


Data synthesis2
Data Synthesis

  • Generate provisional trip ends by zone.

  • Disaggregate expanded trip matrices by provisional trip ends.

  • Assign disaggregated matrices.

  • “Demand adjust” to fit observed screenline counts.

  • Develop Demand Adjustment Factors by Time Period

  • Develop “Blended” Daily Adjustment Factors by Trip Purpose






Calibration results4

Model

Observed

% error

Bus Screenline

North

1699

1803

-5.8%

South

39074

34843

12.1%

River

15516

14584

6.4%

Total

56289

51230

9.9%

Tambang (Water taxi) Screenline

River

8004

7722

3.7%

Calibration Results

Table 5 : Modeled & Observed Bus & Tambang Passengers by Day


Model application
Model Application

  • Road and junction improvement concepts

  • Public transport project concepts

  • Land use/demographic scenarios

  • Policy scenarios


Study findings
Study Findings

  • Road building alone cannot meet objectives

  • Public transport improvements cannot meet objectives

  • Integrated Multi-Modal Plan Required

  • Supported by PT-friendly land use and some TDM policies


Conclusions
Conclusions

  • Reliable data is essential to the development of a transport model.

  • Close supervision of all surveys essential with inexperienced local staff

  • Demand adjustment is a valuable tool where there are errors in data.

  • Caution required in the interpretation and application of model.


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