|Table of Contents|

[1] Bian Chentong, Yin Guodong, Xu Liwei, Zhang Ning, et al. Compact passing algorithm for signalized intersectionmanagement based on vehicular network [J]. Journal of Southeast University (English Edition), 2019, 35 (1): 103-110. [doi:10.3969/j.issn.1003-7985.2019.01.015]

Compact passing algorithm for signalized intersectionmanagement based on vehicular network()

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

2019 1
Research Field:
Traffic and Transportation Engineering
Publishing date:


Compact passing algorithm for signalized intersectionmanagement based on vehicular network
Bian Chentong Yin Guodong Xu Liwei Zhang Ning
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
intersection management signalized intersection vehicular network compact passing phase timing
To improve the traffic efficiency at signalized intersections, a compact passing algorithm is proposed based on a vehicular network. Its basic principle is that several waiting vehicles after the stop line of the considered intersection should simultaneously start in green periods. Thus, more vehicles can pass the intersection in a green period. Then, the having passed vehicles should follow the planned trajectories to enlarge their longitudinal clearances. Phase timing is not considered in the compact passing algorithm, and therefore, the proposed compact passing algorithm can be combined with other algorithms on phase timing to further improve their performances. Several simulations were designed and performed to verify the performance of the proposed algorithm. The simulation results show that the proposed algorithm can increase the number of completed vehicles and decrease the travel time in the signalized intersections managed by fixed-time and vehicle actuated algorithms, which indicates that the proposed algorithm is effective for improving the traffic efficiency at common signalized intersections.


[1] Araghi S, Khosravi A, Creighton D. A review on computational intelligence methods for controlling traffic signal timing[J]. Expert Systems with Applications, 2015, 42(3): 1538-1550. DOI:10.1016/j.eswa.2014.09.003.
[2] Chen Z M, Liu X M, Wu W X. Optimization method of intersection signal coordinated control based on vehicle actuated model[J]. Mathematical Problems in Engineering, 2015, 2015: 1-9. DOI:10.1155/2015/749748.
[3] Feng S M, Ci Y S, Wu L N, et al. Vehicle delay estimation for an isolated intersection under actuated signal control[J]. Mathematical Problems in Engineering, 2014, 2014: 1-7. DOI:10.1155/2014/356707.
[4] Li Y, Fan X P. Design of signal controllers for urban intersections based on fuzzy logic and weightings[C]//Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems. Shanghai, China, 2003: 867-871. DOI:10.1109/ITSC.2003.1252073.
[5] Shirvani Shiri M J, Maleki H R. Maximum green time settings for traffic-actuated signal control at isolated intersections using fuzzy logic[J]. International Journal of Fuzzy Systems, 2017, 19(1): 247-256. DOI:10.1007/s40815-016-0143-7.
[6] Qiao J, Yang N D, Gao J. Two-stage fuzzy logic controller for signalized intersection[J]. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 2011, 41(1): 178-184. DOI:10.1109/tsmca.2010.2052606.
[7] Zhang S, Wei Q P. On-line Q learning model for minimizing average queue length difference [J]. Journal of Hunan Institute of Science & Technology, 2013, 26(4): 22-25. DOI:10.3969/j.issn.1672-5298.2013.04.005. (in Chinese)
[8] Wen K G, Yang Z H. Intersection signal control based onreinforcement learning with CMAC[J]. Computer Engineering, 2011, 37(17): 152-154. DOI:10.3969/j.issn.1000-3428.2011.17.051. (in Chinese)
[9] Chen S K, Sun D J. An improved adaptive signal control method for isolated signalized intersection based on dynamic programming[J]. IEEE Intelligent Transportation Systems Magazine, 2016, 8(4): 4-14. DOI:10.1109/mits.2016.2605318.
[10] Xu L H, Xi L, Zhong L S. Adaptive multi-phase fuzzy control of single intersection based on neural network[J].China Journal of Highway and Transport, 2005, 18(3): 90-93. DOI:10.3321/j.issn:1001-7372.2005.03.018. (in Chinese)
[11] Xu X. Design of hierarchical weighted neural network control system for city traffic in single intersection[J]. Computer Science, 2010, 37(2): 250-252. DOI:10.3969/j.issn.1002-137X.2010.02.062. (in Chinese)
[12] Chen L, Englund C. Cooperative intersection management: A survey[J].IEEE Transactions on Intelligent Transportation Systems, 2016, 17(2): 570-586. DOI:10.1109/tits.2015.2471812.
[13] Dresner K, Stone P. A multiagent approach to autonomous intersection management[J].Journal of Artificial Intelligence Research, 2008, 31: 591-656. DOI:10.1613/jair.2502.
[14] Vasirani M, Ossowski S. A market-inspired approach to reservation-based urban road traffic management [C]// International Conference on Autonomous Agents and Multiagent Systems. Budapest, Hungary, 2009: 617-624.
[15] Carlino D, Boyles S D, Stone P. Auction-based autonomous intersection management[C]//16th International IEEE Conference on Intelligent Transportation Systems. Hague, The Netherlands, 2013: 529-534. DOI:10.1109/ITSC.2013.6728285.
[16] Zohdy I H, Rakha H A. Intersection management via vehicle connectivity: The intersection cooperative adaptive cruise control system concept[J].Journal of Intelligent Transportation Systems, 2016, 20(1): 17-32. DOI:10.1080/15472450.2014.889918.
[17] Lee J, Park B. Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment[J].IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1): 81-90. DOI:10.1109/tits.2011.2178836.
[18] Zhu F, Ukkusuri S V. A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment[J].Transportation Research Part C: Emerging Technologies, 2015, 55: 363-378. DOI:10.1016/j.trc.2015.01.006.
[19] Kesting A, Treiber M. Calibrating car-following models by using trajectory data[J].Transportation Research Record: Journal of the Transportation Research Board, 2008, 2088: 148-156. DOI:10.3141/2088-16.
[20] Ioannou P A, Chien C C. Autonomous intelligent cruise control[J].IEEE Transactions on Vehicular Technology, 1993, 42(4): 657-672. DOI:10.1109/25.260745.


Biographies: Bian Chentong(1988—), male, Ph.D. candidate; Yin Guodong(corresponding author), male, doctor, professor, ygd@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No. 51575103, U1664258), the National Key Research and Development Program of China(No.2016YFB0100906, 2016YFD0700905), Six Talent Peaks Project in Jiangsu Province(No. 2014-JXQC-001), Fundamental Research Funds for the Central Universities(No. 2242016K41056), the Southeast University Excellent Doctor Degree Thesis Training Fund(No.YBJJ1703).
Citation: Bian Chentong, Yin Guodong, Xu Liwei, et al.Compact passing algorithm for signalized intersection management based on vehicular network[J].Journal of Southeast University(English Edition), 2019, 35(1):103-110.DOI:10.3969/j.issn.1003-7985.2019.01.015.
Last Update: 2019-03-20