Pin-Chun Chen
ABSTRACT
Connected and autonomous vehicles (CAVs) can realize many revolutionary applications, but it is expected to have mixed-traffic including CAVs and human-driving vehicles (HVs) together for decades. In this paper, we target the problem of mixed-traffic intersection management and schedule CAVs to control the subsequent HVs. We develop a dynamic programming approach and a mixed integer linear programming (MILP) formulation to optimally solve the problems with the corresponding intersection models. We then propose an MILP-based approach which is more efficient and real-time-applicable than solving the optimal MILP formulation, while keeping good solution quality as well as outperforming the first-come-first-served (FCFS) approach. Experimental results and SUMO simulation indicate that controlling CAVs by our approaches is effective to regulate mixed-traffic even if the CAV penetration rate is low, which brings incentive to early adoption of CAVs.
- S. Aoki, C.-W. Lin, and R. Rajkumar. 2021. Human-Robot Cooperation for Autonomous Vehicles and Human Drivers: Challenges and Solutions. IEEE Communications Magazine 59, 8 (2021), 35--41.Google Scholar
Cross Ref
- S. Aoki and R. Rajkumar. 2018. Dynamic Intersections and Self-Driving Vehicles. In ACM/IEEE International Conference on Cyber-Physical Systems. IEEE, Porto, Portugal, 320--330.Google Scholar
- S. Aoki and R. Rajkumar. 2019. V2V-based Synchronous Intersection Protocols for Mixed Traffic of Human-Driven and Self-Driving Vehicles. In IEEE International Conference on Embedded and Real-Time Computing Systems and Applications. IEEE, Hangzhou, China, 1--11.Google Scholar
- R. Azimi, G. Bhatia, R. Rajkumar, and Priyantha P. Mudalige. 2014. STIP: Spatio-temporal intersection protocols for autonomous vehicles. In ACM/IEEE International Conference on Cyber-Physical Systems. IEEE, Berlin, Germany, 1--12.Google Scholar
- S. Azimi, G. Bhatia, R. Rajkumar, and P. Mudalige. 2013. Reliable Intersection Protocols Using Vehicular Networks. In ACM/IEEE International Conference on Cyber-Physical Systems. IEEE, Philadelphia, PA, USA, 1--10.Google Scholar
- P. Bansal and K. Kockelman. 2017. Forecasting Americans' Long-Term Adoption of Connected and Autonomous Vehicle Technologies. Transportation Research Part A: Policy and Practice 95 (2017), 49--63.Google ScholarCross Ref
- S. Fayazi and A. Vahidi. 2018. Mixed-Integer Linear Programming for Optimal Scheduling of Autonomous Vehicle Intersection Crossing. IEEE Transactions on Intelligent Vehicles 3, 3 (2018), 287--299.Google ScholarCross Ref
- D. Krajzewicz and J. Erdmann. 2013. Road Intersection Model in SUMO. In SUMO User Conference. Springer, Berlin, Germany, 212--220.Google Scholar
- P. Lopez, M. Behrisch, L. Bieker-Walz, J. Erdmann, Y.-P. Flötteröd, R. Hilbrich, L. Lücken, J. Rummel, P. Wagner, and E. Wießner. 2018. Microscopic Traffic Simulation using SUMO. In IEEE International Conference on Intelligent Transportation Systems. IEEE, Maui, HI, USA, 2575--2582.Google Scholar
- A. Malikopoulos, C. Cassandras, and Y. Zhang. 2018. A Decentralized Energy-Optimal Control Framework for Connected Automated Vehicles at Signal-Free Intersections. Automatica 93 (2018), 244--256.Google ScholarDigital Library
- G. Sharon and P. Stone. 2017. A Protocol For Mixed Autonomous and Human-Operated Vehicles at Intersections. In International Conference on Autonomous Agents and Multiagent Systems. Springer, Springer, Cham, São Paulo, Brazil, 151--167.Google Scholar
- J. Song, Y. Wu, Z. Xu, and X. Lin. 2014. Research on Car-Following Model Based on SUMO. In IEEE/International Conference on Advanced Infocomm Technology. IEEE, Fuzhou, China, 47--55.Google Scholar
- R. Stern, S. Cui, M. Delle Monache, R. Bhadani, M. Bunting, M. Churchill, N. Hamilton, R. Haulcy, H. Pohlmann, F. Wu, B. Piccoli, B. Seibold, J. Sprinkle, and D. Work. 2018. Dissipation of Stop-And-Go Waves via Control of Autonomous Vehicles: Field Experiments. Transportation Research Part C: Emerging Technologies 89 (2018), 205--221.Google ScholarCross Ref
- Y. Wei, C. Avci, J. Liu, B. Belezamo, N. Aydin, P. Li, and X. Zhou. 2017. Dynamic Programming-Based Multi-Vehicle Longitudinal Trajectory Optimization with Simplified Car Following Models. Transportation Research Part B: Methodological 106 (2017), 102--129.Google ScholarCross Ref
- J. Wu, A. Abbas-Turki, and A. Moudni. 2009. Intersection Traffic Control by a Novel Scheduling Model. In IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics. IEEE, Chicago, IL, USA, 329--334.Google Scholar
- H. Yao and X. Li. 2020. Decentralized Control of Connected Automated Vehicle Trajectories in Mixed Traffic at An Isolated Signalized Intersection. Transportation Research Part C: Emerging Technologies 121 (2020), 102846.Google ScholarCross Ref
- N. Yao, M. Malisoff, and F. Zhang. 2019. Contention-Resolving Model Predictive Control for Coordinating Automated Vehicles at a Traffic Intersection. In IEEE Conference on Decision and Control. IEEE, Nice, France, 2233--2238.Google Scholar
- X. Zhao, J. Wang, Y. Chen, and G. Yin. 2018. Multi-objective Cooperative Scheduling of CAVs at Non-Signalized Intersection. In IEEE International Conference on Intelligent Transportation Systems. IEEE, Maui, HI, USA, 3314--3319.Google Scholar
- B. Zheng, C.-W. Lin, H. Liang, S. Shiraishi, W. Li, and Q. Zhu. 2017. Delay-Aware Design, Analysis and Verification of Intelligent Intersection Management. In IEEE International Conference on Smart Computing. IEEE, Hong Kong, China, 1--8.Google Scholar
Index Terms
- Mixed-Traffic Intersection Management Utilizing Connected and Autonomous Vehicles as Traffic Regulators
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