1. Charisma Choudhury Bangladesh University of Engineering and Technology A Simulation Framework for Evaluating Sustainable Transport Options in Developing Countries 1

2. 2  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 Background

3. 3 Microscopic Traffic Simulation  Microscopic traffic simulation mimic individual drivers to deduce network conditions –Example: MITSIM http://its.mit.edu

4. Motivation  Developing countries have significantly different traffic patterns: –Mixed traffic –Significant movement in the lateral direction –‘Weak’ lane disciplines

5. Example: Mixed traffic in Dhaka Human-haulers/ Tempo Auto-rickshaw/ CNG Car Bus Rickshaw 5 Taxi

6. 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

7. 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

8. 8 Models

9. Behavior Framework  Selecting the Target Leader –Front-Left /Current-Front / Front-Right  Lateral Acceleration –Constrained /Unconstrained  Longitudinal Acceleration –Current Leader / New Leader –Acceleration / Deceleration

10. Methodology  Model estimation – Detailed trajectory data – Comparison of goodness-of- fit against models for lane- based traffic  Model validation – Within simulator – Aggregate data

11. 11 Data

12.  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

13. 13 Ongoing Research

14.  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.

15. Questions? Email: cfc@ce.buet.ac.bd or cfc@alum.mit.edu Web: http://teacher.buet.ac.bd/cfc cfc@ce.buet.ac.bd cfc@alum.mit.edu http://teacher.buet.ac.bd/cfc