Home Journal of Intelligent and Connected Vehicles Article
PDF (2.7 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript
Research Article | Open Access

Hybrid cooperative intersection management for connected automated vehicles and pedestrians

Pinlong Cai1, Jia He2(), Yikang Li1
Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
Show Author Information

Abstract

Connected Automated Vehicles (CAVs) have drawn much attention in recent years. High reliable automatic technologies can help CAVs to follow given trajectories well. However, safety and efficiency are hard to be ensured since the interactions between CAVs and pedestrians are complex problems. Thus, this study focuses on cooperative intersection management for CAVs and pedestrians. To avoid the effects of uncertainty about pedestrian behaviors, an indirect way is to use pedestrians’ signal lights to guide the movements of pedestrians, and such lights with communication devices can share information with CAVs to make decisions together. In time domains, a general conflict-free rule is established depending on the positions of CAVs and crosswalks. Geometric analysis with coordinate calculation is used to accurately determine the feasible vehicle trajectories and the reasonable periods for signal lights turning green. Four control strategies for the same conditions are compared in simulation experiments, and their performances are analyzed. We demonstrate that the proposed cooperative strategy not only balances the benefits of vehicles and pedestrians but also improves the traffic efficiency at the intersection.

Keywords

connected automated vehicleintersectionpedestriancrosswalkcooperative management

References

[1]

Bichiou, Y., Rakha, H. A., 2019. Developing an optimal intersection control system for automated connected vehicles. IEEE Trans Intell Transp Syst, 20, 1908−1916.

Crossref Google Scholar
[2]

Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen, P. et al., 2012. A survey of Monte Carlo tree search methods. IEEE Trans Comput Intell AI Games, 4, 1−43.

Crossref Google Scholar
[3]
Cai, P. L., Wang, Y. P., Lu, G. Q., 2019. Intersection self-organization control for connected autonomous vehicles based on traffic strategy learning algorithm. In: 19th COTA International Conference of Transportation Professionals, 5551–5562.
Crossref
[4]

Chai, L., Cai, B., Wei, S. G., Wang, J., Wang, H., 2018. Connected and autonomous vehicles coordinating approach at intersection based on space-time slot. Transp A Transp Sci, 14, 929−951.

Crossref Google Scholar
[5]
Dresner, K., Stone, P., 2004. Multiagent traffic management: A reservation-based intersection control mechanism. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 530–537.
Crossref
[6]

Ge, Q., Sun, Q., Wang, Z., Li, S. E., Gu, Z., Zheng, S., et al., 2021. Real-time coordination of connected vehicles at intersections using graphical mixed integer optimization. IET Intell Transp Syst, 15, 795−807.

Crossref Google Scholar
[7]

González, D., Pérez, J., Milanés, V., Nashashibi, F., 2015. A review of motion planning techniques for automated vehicles. IEEE Trans Intell Transp Syst, 17, 1135−1145.

Crossref Google Scholar
[8]

Jiang, Z., Yu, D., Zhou, H., Luan, S., Xing, X., 2021. A trajectory optimization strategy for connected and automated vehicles at junction of freeway and urban road. Sustainability, 13, 9933.

Crossref Google Scholar
[9]

Levin, M. W., Boyles, S. D., Patel, R., 2016. Paradoxes of reservation-based intersection controls in traffic networks. Transp Res A, 90, 14−25.

Crossref Google Scholar
[10]
Li, B., Zhang, Y., Zhang, Y., Jia, N., Ge, Y., 2018. Near-optimal online motion planning of connected and automated vehicles at a signal-free and lane-free intersection. In: 2018 IEEE Intelligent Vehicles Symposium (IV), 1432–1437.
Crossref
[11]

Malikopoulos, A. A., Cassandras, C. G., Zhang, Y. J., 2018. A decentralized energy-optimal control framework for connected automated vehicles at signal-free intersections. Automatica, 93, 244−256.

Crossref Google Scholar
[12]

Meng, Y., Li, L., Wang, F. Y., Li, K., Li, Z., 2017. Analysis of cooperative driving strategies for nonsignalized intersections. IEEE Trans Veh Technol, 67, 2900−2911.

Crossref Google Scholar
[13]

Mirheli, A., Hajibabai, L., Hajbabaie, A., 2018. Development of a signal-head-free intersection control logic in a fully connected and autonomous vehicle environment. Transp Res C, 92, 412−425.

Crossref Google Scholar
[14]
Prautzsch, H., Boehm, W., Paluszny, M., 2002. B-spline techniques. In: Bézier and B-Spline Techniques. Prautzsch, H., Boehm, W., Paluszny, M., Eds. Berlin, Heidelberg: Springer, 77–89.
Crossref
[15]
Rashidi, T. H., Najmi, A., Haider, A., Wang, C., Hosseinzadeh, F., 2020. What we know and do not know about connected and autonomous vehicles. Transp A Transp Sci, 16, 987–1029.
Crossref
[16]

Rasouli, A., Tsotsos, J. K., 2020. Autonomous vehicles that interact with pedestrians: A survey of theory and practice. IEEE Trans Intell Transp Syst, 21, 900−918.

Crossref Google Scholar
[17]

Rios-Torres, J., Malikopoulos, A. A., 2017. Automated and cooperative vehicle merging at highway on-ramps. IEEE Trans Intell Transp Syst, 18, 780−789.

Crossref Google Scholar
[18]
Tachet, R., Santi, P., Sobolevsky, S., Reyes-Castro, L. I., Frazzoli, E., Helbing, D. et al., 2016. Revisiting street intersections using slot-based systems. PLoS One, 11, e0149607.
Crossref
[19]
Transportation Research Board, 2010. Highway Capacity Manual, 5th edn. Washington, DC: The National Academies Press.
[20]

Wang, Y., Cai, P., Lu, G., 2020. Cooperative autonomous traffic organization method for connected automated vehicles in multi-intersection road networks. Transp Res C, 111, 458−476.

Crossref Google Scholar
[21]

Wu, W., Liu, Y., Hao, W., Giannopoulos, G. A., Byon, Y. J., 2022. Autonomous intersection management with pedestrians crossing. Transp Res C, 135, 103521.

Crossref Google Scholar
[22]

Xu, B., Li, S. E., Bian, Y., Li, S., Ban, X. J., Wang, J., et al., 2018. Distributed conflict-free cooperation for multiple connected vehicles at unsignalized intersections. Transp Res C, 93, 322−334.

Crossref Google Scholar
[23]

Xu, H., Zhang, Y., Li, L., Li, W., 2019. Cooperative driving at unsignalized intersections using tree search. IEEE Trans Intell Transp Syst, 21, 4563−4571.

Crossref Google Scholar
[24]

Yu, H., Jiang, R., He, Z., Zheng, Z., Li, L., Liu, R., et al., 2021. Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives. Transp Res C, 127, 103101.

Crossref Google Scholar
[25]

Zhong, Z., Nejad, M., Lee, E. E., 2020. Autonomous and semiautonomous intersection management: A survey. IEEE Intell Transp Syst Mag, 13, 53−70.

Crossref Google Scholar
Journal of Intelligent and Connected Vehicles
Volume 6 Issue 2,
June 2023
Pages 91-101
DOI: 10.26599/JICV.2023.9210008
Cite this article:
Cai P, He J, Li Y. Hybrid cooperative intersection management for connected automated vehicles and pedestrians. Journal of Intelligent and Connected Vehicles, 2023, 6(2): 91-101. https://doi.org/10.26599/JICV.2023.9210008
Metrics & Citations  
Article History
Copyright
Rights and Permissions
Return