1. Feasibility Study Problem Definition Traffic Modeling Guided by Prof Kavi Arya Presented by Shivendra S. Meena 01005030

2. Motivation • Transportation affects • Natural Environment • Economic Prosperity • Social Future • Trends of Transportation • Unsustainable • Resource utilization • Safety reasons

3. Transport Management Systems • Traffic Management Systems • Mass Transport Schedulers • Tracking Systems for Fleets • Crisis Management Systems • Traveler Information Systems

4. Components of TMS • Surveillance and Detection • Loop detectors, GPS/GIS,CCTV etc • Communication and Data Transfer • Ramp meters,VMS etc • Management and Control • Servers,PSAP,IVR etc

5. Assumptions • Surveillance and Detection • GPS on selected vehicles • Communication and Data transfer • Cellular Network and Its services • Management and Control • Central Answering point • No inter vehicle communication

6. Classification • Surveillance • Location Specific Detection • Vehicle Specific Detection • Knowledge Processing • Pattern Matching and Analysis • Neural networks • Functional Approach • Exponential average

7. Case Studies 1. Mumbai Navigator 2. RETINA

8. Mumbai Navigator • Input • Partial Schedule of Public Transportation System • Output • Generates best plan after taking account of • Frequency of vehicles • Delays in arrival • Knowledge Processing Approach • Probabilistic

9. Algorithm • Estimation of distance between stops using linear programming on stage length data. • Estimation of time between two consecutive stops using linear programming. • Generates all bus restricted plans by dynamic programming. • Select the plan with minimum expected time

10. Real Time Traffic Navigation System • Input • Real time locations of vehicle using cellular network • Output • Response to location dependent continuous queries from vehicles

11. Some Issues • Consistency of distributed data • Functional Temporal Logic • Types of queries • Instantaneous Queries • Continuous Queries • Persistent Queries

12. Comparison • Static Vs Dynamic • Dynamic model is the need of hour. • Probabilistic Vs Continuous Queries. • Data consistency • Crisis management • Wandering

13. Conclusion • Functional approach with real time addresses major issues. But... • Probabilistic component is unavoidable.

14. References • Mayur Datar and Abhiram Ranade. Commuting with delay prone buses. In Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms, pages 22-29.Society for Industrial and Applied Mathematics, 2000. • Dick Hung and Kam-Yiu Lam and Edward Chan and Krithi Ramamritham. Processing of Location-Dependent Continuous Queries on Real-Time Spatial Data: The View from RETINA. In Proceedings of the 14th International Workshop on Database and Expert Systems Applications (DEXA'03), page 961.IEEE Computer Society, 2003. • A. Prasad Sistla and Ouri Wolfson and Sam Chamberlain and Son Dao. Modeling and Querying Moving Objects. In ICDE, pages 422-432, 1997.

15. Thank You