Multiple Emergency Vehicle Priority in a Connected Vehicle Environment: A Cooperative Method

被引:9
作者
Lin, Peiqun [1 ]
Chen, Zemu [1 ]
Pei, Mingyang [1 ]
Ding, Yida [2 ]
Qu, Xiaobo [2 ]
Zhong, Lingshu [3 ]
机构
[1] South China Univ Technol, Sch Civil Engn & Transportat, Guangzhou 510640, Peoples R China
[2] Tsinghua Univ, Sch Vehicle & Mobil, Beijing 100084, Peoples R China
[3] Chalmers Univ Technol, Dept Architecture & Civil Engn, S-41296 Gothenburg, Sweden
基金
中国国家自然科学基金;
关键词
Emergency vehicle priority; connected vehicles; trajectory; lane-changing; acceleration and deceleration; TRAJECTORY OPTIMIZATION; MODEL; ALGORITHM;
D O I
10.1109/TITS.2023.3306588
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Since emergency vehicles (EMVs) in urban transit systems play a crucial role in responding to time-critical events, the quick response of EMVs is essential for improving the success rate of rescue operations and minimizing property loss. Booming connected vehicle (CV) technology provides a new perspective to further enhance the effectiveness of EMV priority. Based on this CV technology, we propose a cooperative multiple EMV priority model in which the speed, acceleration, and lane changing actions of both the EMVs and surrounding ordinary vehicles (OVs) are set as decision variables. This proposed model is rigorously formulated in integer linear programming to maximize the EMV traffic efficiency and find a trade-off between the interference with normal traffic flows and the smoothness of the EMV driving trajectories. Two customized algorithms are developed to reduce the number of decision variables and constraints to obtain the better feasible solution in an acceptable computational time. A numerical experiment based on real-world data is proposed to further verify the utility and effectiveness of the aforementioned mathematical model. The customized algorithms achieve near-exact solutions with significantly faster computation compared to the benchmark solver. The robustness of the proposed model is tested with different parameter settings in the sensitivity analysis.
引用
收藏
页码:173 / 188
页数:16
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