AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.7 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Hybrid cooperative intersection management for connected automated vehicles and pedestrians

Pinlong Cai1Jia 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.

References

[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.
[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.

[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.
[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.

[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.

[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.
[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.

[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.
[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.
[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.
[19]
Transportation Research Board, 2010. Highway Capacity Manual, 5th edn. Washington, DC: The National Academies Press.
[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.

[25]

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

Journal of Intelligent and Connected Vehicles
Pages 91-101
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

265

Views

8

Downloads

5

Crossref

6

Scopus

Altmetrics

Received: 13 December 2022
Revised: 11 February 2023
Accepted: 10 May 2023
Published: 30 June 2023
© The author(s) 2023.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return