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http://hdl.handle.net/10397/92754
Title: | Autonomous intersection management for connected and automated vehicles : a lane-based method | Authors: | Wu, W Liu, Y Liu, W Zhang, F Dixit, V Waller, ST |
Issue Date: | Sep-2022 | Source: | IEEE transactions on intelligent transportation systems, Sept 2022, v. 23, no. 9, p. 15091-15106 | Abstract: | Most existing studies on autonomous intersection management (AIM) often focus on algorithms to accommodate conflicts among vehicles by assuming that the entrance lane and the exit lane of vehicles are exogenous inputs. This paper shows that allowing entrance lanes and exit lanes to be optimized can significantly improve traffic efficiency. In particular, this paper proposes ``all-direction'' lanes, where left-turn, through, and right-turn traffic is all allowed at the same lane. We develop two methods for optimizing entering time (i.e., when to enter the intersection) and route choice decisions (i.e., entrance lane and exit lane), including the sliding-time-window-based global optimum (GO-STW) and the first-come-first-served method with optimal route choices (FCFS-R). The developed lane-based methods can be formulated as mixed integer linear programming (MILP) problems, which can be solved using the CPLEX solver. A heuristic is further adopted to solve the MILP model in a timely manner, which illustrates the potential real-time applicability of the proposed method. Numerical analysis is conducted to examine performance and effectiveness of the proposed methods and heuristic. We found that the optimization of lane/route choices is often more critical than entering time. | Keywords: | Autonomous intersection Connected and autonomous vehicles Lane-based method Sliding time window |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on intelligent transportation systems | ISSN: | 1524-9050 | EISSN: | 1558-0016 | DOI: | 10.1109/TITS.2021.3136910 | Rights: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for Publishedertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication W. Wu, Y. Liu, W. Liu, F. Zhang, V. Dixit and S. T. Waller, "Autonomous Intersection Management for Connected and Automated Vehicles: A Lane-Based Method," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9, pp. 15091-15106, Sept. 2022 is available at https://dx.doi.org/10.1109/TITS.2021.3136910. |
Appears in Collections: | Journal/Magazine Article |
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