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Adaptive Traffic Light Control in Wireless Sensor Network-based Intelligent Transportation System

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). Objectives:.

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Adaptive Traffic Light Control in Wireless Sensor Network-based Intelligent Transportation System

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  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

  16. 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.

  17. Thank you • Questions…

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