Optimal Signal Timing of Single Intersection for Traffic Emission Control

Abstract:

Traffic emission is one of the main pollution sources of urban atmospheric environment. Traffic control scheme of intersection has important influence on vehicle emission. Research on low emission traffic signal control scheme has become one of focuses of Intelligent Transportation. Current typical control methods of traffic emission are based on optimizing the average delay and number of stops. However, it is extremely difficult to use mathematical formula to calculate the delay and the number of stops in the presence of initial queue length of intersection. In order to solve this problem, we proposed a traffic emission control algorithm based on reinforcement learning. The simulation experiments were carried out by using the microscopic traffic simulation software. Compared with the Hideki emission control scheme, the experimental results show that the reinforcement learning algorithm is more effective. The average vehicle emissions are reduced by 12.2% for high saturation of the intersection.

• Periodical: Applied Mechanics and Materials (Volumes 587-589)
• Pages: 2137-2140
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.587-589.2137
• Online since: July 2014
• Authors: Xin Li*, Feng Chen
• Keywords: Intersection, Queue Length, Reinforcement Learning, Traffic Emission

References

[1] Z.R. Chen, D.F. Fu: The analysis of Excess Emission at the Signalized Intersection[J]. Journal of Highway and Transportation Research and Development, 1993, 3: 012.

[2] J. Q. Li, G . Wu and N . Zou: Investigation of the impacts of signal timing on vehicle emissions at an isolated intersection[J]. Transportation Research Part D: Transport and Environment, 2011, 16(5): 409-414.

DOI: 10.1016/j.trd.2011.03.004

[3] J.P. Lv and Y.L. Zhang: Effect of signal coordination on traffic emission [J]Transportation Reserch Part D 17 (2012)149-153.

[4] Nakamura H: Cycle Length Optimization at Isolated Signalized Intersections from the Viewpoint of Emission[J]. Traffic and Transportation Studies, 2010, 2010: 275-284.

DOI: 10.1061/41123(383)24

[5] S.P. Zhou: Research on Traffic Signal Control Strategies in Urban Intersections Based on Emission Factors[D][D]. Wuhan: Wuhan University of Technology, (2009).

[6] S.W. Li, L.H. Wang, D. Guo, W.C. Sun and Z.F. Yang: Adaptive Signal Control Model Based on Vehicle Emission [J]Journal of south china university of technology: nature science edition, 2011, 39(3): 101-105.

[7] Z. Liu, H.H. Li and Q. Liu: Research on algorithm of reinforcement learning[J]. Computer Engineering and Design 2008. 11 Vol. 29(22).

[8] D.H. Huang: Study of the relation of vehicle's driving cycles and emission rate and database [D][D]. Wuhan: Wuhan University of Technology, (2008).