1. Adaptive Traffic Light Control in Wireless Sensor Network-based Intelligent Transportation System
Binbin Zhou;   Jiannong Cao;   Xiaoqin Zeng;   Hejun Wu;    Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China 
Presentation by: Vipul Singh(vs2416)

2. Objectives:
Proposes an Adaptive Traffic light algorithm that adjusts both the sequence and length of traffic lights in accordance with the real time traffic detected.
Compares the results obtained with fixed-time control algorithm and also actuated control algorithm.

3. Challenge
Coping with dynamic changes in the traffic volume is one of the biggest challenges in intelligent transportation system (ITS). The main contribution is the real-time adaptive control of the traffic lights. Our aim is to maximize the flow of vehicles and reduce the waiting time while maintaining fairness among the other traffic lights.

4. Results:
Higher throughput
Lower vehicle’s average waiting time

5. Results: Performance Evaluation
Simulation Done on Matlab and iSensNet.
Compared the effectiveness of the present method with fixed-time traffic control(FTC) and actuated traffic control(ATC)

6. Metrics
Throughput to Volume
Volume-to-capacity
Average waiting time

7. Results(2/3)

8. Average Waiting time comparison

9. Problem Model Assumptions: All vehicles are of the same type.
All vehicles travel at the same speed.

10. Adaptive Traffic Light Control Algorithm
Outline of the approach
Vehicle Detection
Green Light Sequence Determination
Light Length Determination

11. Vehicle Detection
Arrival Rate
Departure Rate
Density of Traffic Flow

12. Green Light Sequence Determination
Traffic Volume
Waiting Time
Blank Circumstance
Special Circumstance
Hungry Level

13. Traffic Volume
TraVol(i,t) is defined as the total number of vehicles in the lane from time t to following Tcontrol time.
FV(i,t) is defined as the number of vehicles that would reach the intersection in time t in lane i.

14. Waiting time

15. Hungry Level
The more times the case got green before, the lower hunger level it gets currently; the fewer times the case got green before the higher hunger level it gets

17. Reference
Adaptive Traffic Light Control in Wireless Sensor Network-based Intelligent Transportation System, Binbin Zhou, Jiannong Cao, Xiaoqin Zeng and Hejun Wu, Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China.

18. Thank you
Questions…