Mixed-Traffic Intersection Management Utilizing Connected and Autonomous Vehicles as Traffic Regulators
Mixed-Traffic Intersection Management Utilizing Connected and Autonomous Vehicles as Traffic Regulators
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DOI：
10.1145/3566097.3567849
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发表时间：
2023-01
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影响因子：
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通讯作者：
Pin-Chun Chen;Xiangguo Liu;Chung-Wei Lin;Chao Huang;Qi Zhu
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作者：
Pin-Chun Chen;Xiangguo Liu;Chung-Wei Lin;Chao Huang;Qi Zhu
互联和自动驾驶汽车（CAV）可以实现许多革命性的应用，但预计几十年内将同时拥有包括CAV和人类驾驶汽车（HV）在内的混合交通。本文针对混合交通交叉口的管理问题，通过调度CAV来控制后续的HV。我们开发了一个动态规划方法和一个混合整数线性规划（MILP）公式，以最优地解决相应的交叉模型的问题。然后，我们提出了一个基于MILP的方法，这是更有效的和实时适用的比解决最佳MILP配方，同时保持良好的解决方案的质量，以及优于先到先得（FCFS）的方法。实验结果和SUMO仿真表明，即使CAV的穿透率较低，采用本文的方法控制CAV也能有效地调节混合交通，从而促进CAV的早期采用。
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 pro-gramming (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.