Abstract
Intersections are one of the most common conflicting scenarios, where vehicles intend to pass through them at the same time. As the technology advances, connected and autonomous vehicles (CAVs) provide a revolutionary solution at intersections. In this chapter, we consider connected and autonomous vehicles at intersections and introduce distributed and centralized approaches solving the problem of intersection management. The approaches provide feasibility, safety (collision-freeness), liveness (deadlock-freeness), stability, efficiency, and real-time decision.
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Notes
- 1.
Note that this is different from the strategies discussed in [4], which only considers the arrival time at the intersection.
- 2.
As there is dependency between vehicles, the vertex entering time of each vertex cannot be given as an input.
- 3.
We do not consider overtaking in this section; otherwise, we can relax the constraint to potentially change Type-2 edges.
- 4.
This is the reason that we need the item 2 in the problem formulation.
- 5.
- 6.
If all of the conditions are false, then Δi can move from Ξj to \(\Xi _{j^{\prime }}\). A similar claim is not true for G′, so having no cycle in G′ cannot guarantee deadlock-freeness.
- 7.
Though it may not go back to (i, j, j′).
- 8.
It is believed that an intersection manager has much better computational capability than a current vehicle.
References
Liu, C., Tomizuka, M.: Enabling safe freeway driving for automated vehicles. In: 2016 American Control Conference, pp. 3461–3467. IEEE, Piscataway (2016)
Liu, C., Chen, J., Nguyen, T.-D., Tomizuka, M.: The robustly-safe automated driving system for enhanced active safety. Technical report, SAE Technical Paper (2017)
Dresner, K., Stone, P.: Multiagent traffic management: an improved intersection control mechanism. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 471–477. ACM, New York (2005)
Azimi, S., Bhatia, G., Rajkumar, R., Mudalige, P.: Reliable intersection protocols using vehicular networks. In: Proceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems (ICCPS’13), pp. 1–10. ACM, New York (2013). https://doi.org/10.1145/2502524.2502526
Pandit, K., Ghosal, D., Zhang, H.M., Chuah, C.-N.: Adaptive traffic signal control with vehicular ad hoc networks. IEEE Trans. Veh. Technol. 62(4), 1459–1471 (2013)
Liu, C., Zhan, W., Tomizuka, M.: Speed profile planning in dynamic environments via temporal optimization. In: 2017 IEEE Intelligent Vehicles Symposium (IV), pp. 154–159. IEEE, Piscataway (2017)
Liu, C., Lin, C.-W., Shiraishi, S., Tomizuka, M.: Distributed conflict resolution for connected autonomous vehicles. IEEE Trans. Intell. Veh. 3(1), 18–29 (2017)
Zhou, H., Liu, C.: Distributed motion coordination using convex feasible set based model predictive control. In: International Conference on Robotics and Automation (ICRA 2021) (2021)
An, J., Giordano, G., Liu, C.: Flexible MPC-based conflict resolution using online adaptive ADMM. In: European Control Conference (ECC 2021) (2021)
Peterson, J.L.: Petri nets. ACM Comput. Surv. 9(3), 223–252 (1977)
Kleinberg, J., Tardos, E.: Algorithm Design. Pearson, Addison Wesley, London (2006)
Karp, R.M.: Reducibility among combinatorial problems. In: Complexity of Computer Computations. The IBM Research Symposia Series, pp. 85–103 (1972)
Kann, V.: On the approximability of np-complete optimization problems. Ph.D. Thesis, Department of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm (1992)
Kruskal, J.B.: On the shortest spanning subtree of a graph and the traveling salesman problem. Am. Math. Soc. 7(1), 48–50 (1956)
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Lin, YT., Lin, CW., Jiang, I.HR., Liu, C. (2023). Distributed Coordination and Centralized Scheduling for Automobiles at Intersections. In: Kukkala, V.K., Pasricha, S. (eds) Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-28016-0_3
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