A Simulation Framework for Evaluating
Sustainable Transport Options in
Developing Countries
Charisma Choudhury
Bangladesh University of Engineering and Technology
1
Background
 Traffic simulation
– Analyze congestion management strategies and
evaluate alternative transport options
– Example applications:





Evaluating emission control strategies
– Hornstull network, Stockholm (MITNEM)
Quantifying benefits of car-sharing
– HOV lane in I-80, CA (MITSIM)
Improving public transport system
– Bus signal priority, Stockholm (MITSIM)
Removing redundant capacity
– Chung-gae project in Seoul (MITSIM-SDI)
Promoting bicycles and non-motorized traffic
2
Microscopic Traffic Simulation
 Microscopic traffic
simulation mimic
individual drivers
to deduce
network
conditions
– Example: MITSIM
http://its.mit.edu
3
Motivation
 Developing countries have
significantly different traffic
patterns:
– Mixed traffic
– Significant movement in the
lateral direction
– ‘Weak’ lane disciplines
Example: Mixed traffic in Dhaka
Bus
Rickshaw
Car
Taxi
Auto-rickshaw/
CNG
Human-haulers/
Tempo
5
Motivation
 Developing countries have
significantly different traffic
patterns:
– Mixed traffic
– Significant movement in the
lateral direction
– ‘Weak’ lane disciplines
 Existing state-of-the-art
simulators are not applicable in
developing countries
– Do no have driving behavior
models that replicate mixed
traffic and weak lane discipline
Challenges
 Complexities in behavior
– Difficulties in identifying the ‘leader’ due to absence of
strict lane disciplines
– Highly sensitive to traffic condition

Increased capacity and more violation of traffic rules in
congested situations
 Calibration data difficult to gather and process
– Absence of lane discipline warrants need for high
accuracy
Models
8
Behavior Framework
 Selecting the Target
Leader
– Front-Left
/Current-Front
/ Front-Right
 Lateral Acceleration
– Constrained
/Unconstrained
Front
Left
Current
Front
Lateral Acc. to Left
Front
Right
Lateral Acc. to Right
 Longitudinal
Acceleration
– Current Leader /
New Leader
– Acceleration /
Deceleration
Longitudinal Acc.
Longitudinal Acc.
Longitudinal Acc.
Methodology
 Model estimation
 Model validation
Model refinement
Implementation and
verification
Aggregate calibration
of simulation model
MITSIMLab
– Within simulator
– Aggregate data
Model estimation
Aggregate validation
Calibrated and
validated simulation
model
Aggregate
(sensor
data)
– Detailed trajectory data
– Comparison of goodness-offit against models for lanebased traffic
Disaggregate
(trajectory
data)
Data collection
Data
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Data
 GPS trajectories of 1000 vehicles
 Position every 30 seconds for 7 days
– Accuracy not fine enough for direct extraction of
trajectories
 Processed to determine travel times between
origin destination pairs for aggregate calibration
Ongoing Research
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Ongoing Research
 Calibrate the driving behavior models for Dhaka
traffic
 Implement them in the open sourced microscopic
traffic simulator MITSIM
 Apply them for evaluation of sustainable transport
options
–
–
–
–
Benefits of congestion pricing
Effects of increasing fuel price
Effects of separate lanes for non-motorized traffic
Evaluation of BRT lane configuration, etc.
Questions?
Email:
[email protected] or
[email protected]
Web:
http://teacher.buet.ac.bd/cfc