Optimization of Highway Emergency Lane Control Based on Kriging Genetic Algorithm

doi:10.16182/j.issn1004731x.joss.23-0090

Abstract

Abstract:

To address the issue of how to effectively improve the highway operational efficiency and reduce the safety risks under different traffic flow conditions, this study proposed a genetic algorithm based on Kriging agent model is proposed to optimize the emergency lane control strategy. A mathematical optimization model is designed by combining the spatial and temporal characteristics of the emergency lane opening strategy. By introducing Kriging agent model, combining the genetic algorithm to build the optimization framework, and using simulation software to obtain data to train the agent model, the problem of minimizing the total travel time and the total exposed time-to-collision with both time and space constraints is solved. The change frequency of the emergency lane control at time and space dimension is constrained. The effect of the change of weights for efficiency and safety indicators in the objective function on the optimization results. Comparison in experiments show that the proposed optimization method reduces the total travel time of the road network by 14.9% and the total time exposed time-to-collision by 44.2%.

Key words: smart highway, emergency lane, Kriging agent model, genetic algorithm, space-time constraints, simulation of urban mobility(SUMO)

CLC Number:

TP391.9

Tang Jinjun, Hu Lipeng, Li Mingyang, Zhang Xuan. Optimization of Highway Emergency Lane Control Based on Kriging Genetic Algorithm[J]. Journal of System Simulation, 2024, 36(5): 1165-1178.

Figures/Tables 10

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

References 28

1	李月姝, 李平, 王少飞, 等. 高速公路数字化基础设施分级方法研究[J]. 公路, 2022, 67(8): 302-305.
2	杜豫川, 刘成龙, 吴荻非, 等. 新一代智慧高速公路系统架构设计[J]. 中国公路学报, 2022, 35(4): 203-214.
	Du Yuchuan, Liu Chenglong, Wu Difei, et al. Framework of the New Generation of Smart Highway[J]. China Journal of Highway and Transport, 2022, 35(4): 203-214.
3	赵祥模, 高赢, 徐志刚, 等. IntelliWay-变耦合模块化智慧高速公路系统一体化架构及测评体系[J]. 中国公路学报, 2023, 36(1): 176-201.
	Zhao Xiangmo, Gao Ying, Xu Zhigang, et al. IntelliWay: An Integrated Architecture and Testing Methodology for Intelligent Highway Using Varied Coupling Modularization[J]. China Journal of Highway and Transport, 2023, 36(1): 176-201.
4	孙超, 黄愉文, 张永捷. 数字时代全球智慧高速公路发展趋势及建设思考[J]. 公路, 2022, 67(4): 237-242.
	Sun Chao, Huang Yuwen, Zhang Yongjie. Trend Analysis and Development Thinking of Global Smart Expressway in Digital Age[J]. Highway, 2022, 67(4): 237-242.
5	沙爱民. 高速公路客货系统分置建设对策建议与智慧运行模式探讨[J]. 中国公路学报, 2020, 33(5): 1-7.
	Sha Aimin. Discussion on Countermeasures and Intelligent Operation Mode of Division Construction for the Expressway Passenger and Freight Transport System[J]. China Journal of Highway and Transport, 2020, 33(5): 1-7.
6	Arora K, Kattan L. Operational and Safety Impacts of Integrated Variable Speed Limit with Dynamic Hard Shoulder Running[J]. Journal of Intelligent Transportation Systems, 2023, 27(6): 769-798.
7	Ma Jiaqi, Hu Jia, Hale D K, et al. Dynamic Hard Shoulder Running for Traffic Incident Management[J]. Transportation Research Record, 2016, 2554(1): 120-128.
8	Kononov J, Hersey S, Reeves D, et al. Relationship Between Freeway Flow Parameters and Safety and Its Implications for Hard Shoulder Running[J]. Transportation Research Record, 2012, 2280(1): 10-17.
9	Geistefeldt Justin. Operational Experience with Temporary Hard Shoulder Running in Germany[J]. Transportation Research Record, 2012, 2278(1): 67-73.
10	Coffey S, Park S. Operational Evaluation of Part-time Shoulder Use for Interstate 476 in the State of Pennsylvania[J]. Advances in Civil Engineering, 2018, 2018: 1724646.
11	Li Duo, Lasenby J. Mitigating Urban Motorway Congestion and Emissions via Active Traffic Management[J]. Research in Transportation Business & Management, 2023, 48: 100789.
12	Choi Jaisung, Tay R, Kim Sangyoup, et al. Safety Effects of Freeway Hard Shoulder Running[J]. Applied Sciences, 2019, 9(17): 3614.
13	Guerrieri Marco, Mauro Raffaele. Capacity and Safety Analysis of Hard-shoulder Running (HSR). A Motorway Case Study[J]. Transportation Research Part A: Policy and Practice, 2016, 92: 162-183.
14	Coffey S, Park S. Part-time Shoulder Use Operational Impact on the Safety Performance of Interstate 476[J]. Traffic Injury Prevention, 2020, 21(7): 470-475.
15	Dutta N, Boateng R A, Fontaine M D. Safety and Operational Effects of the Interstate 66 Active Traffic Management System[J]. Journal of Transportation Engineering, Part A: Systems, 2019, 145(3): 04018089.
16	李瑞敏, 叶朕, 李斌. 高速公路临时路肩使用措施优化控制与仿真[J]. 系统仿真学报, 2018, 30(3): 1036-1045.
	Li Ruimin, Ye Zhen, Li Bin. Optimal Control and Simulation of Hard Shoulder Running on Highways[J]. Journal of System Simulation, 2018, 30(3): 1036-1045.
17	Zhou Weiyi, Yang Mofeng, Lee M, et al. Q-learning-based Coordinated Variable Speed Limit and Hard Shoulder Running Control Strategy to Reduce Travel Time at Freeway Corridor[J]. Transportation Research Record, 2020, 2674(11): 915–925.
18	Li Ruimin, Ye Zhen, Li Bin, et al. Simulation of Hard Shoulder Running Combined with Queue Warning During Traffic Accident with CTM Model[J]. IET Intelligent Transport Systems, 2017, 11(9): 553-560.
19	Li Ye, Li Zhibin, Wang Hao, et al. Evaluating the Safety Impact of Adaptive Cruise Control in Traffic Oscillations on Freeways[J]. Accident Analysis & Prevention, 2017, 104: 137-145.
20	Ward J R, Agamennoni Gabriel, Worrall S, et al. Extending Time to Collision for Probabilistic Reasoning in General Traffic Scenarios[J]. Transportation Research Part C: Emerging Technologies, 2015, 51: 66-82.
21	Li Ye, Wang Hao, Wang Wei, et al. Evaluation of the Impacts of Cooperative Adaptive Cruise Control on Reducing Rear-end Collision Risks on Freeways[J]. Accident Analysis & Prevention, 2017, 98: 87-95.
22	P C Kleijnen Jack. Kriging Metamodeling in Simulation: A Review[J]. European Journal of Operational Research, 2009, 192(3): 707-716.
23	van Beers W C M, Kleijnen J. Kriging for Interpolation in Random Simulation[J]. Journal of the Operational Research Society, 2003, 54(3): 255-262.
24	Mirjalili S. Evolutionary Algorithms and Neural Networks: Theory and Applications[M]. Cham: Springer International Publishing, 2019.
25	Zhang Zhigang, Peng Rui, Qiao Jiangang. Analysis of Traffic Characteristics of Dynamic Open Hard Shoulder Road Based on SUMO[C]//2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI). Piscataway, NJ, USA: IEEE, 2022: 100-104.
26	田丽萍, 朱弘戈, 朱晓东, 等. 面向高速公路匝道合流区通行效率的车路协同限速方法[J]. 公路, 2019, 64(8): 310-316.
27	李志斌, 王炜, 李晓伟, 等. 高速公路车辆排队尾部交通事故时空分布特征[J]. 交通运输工程学报, 2014, 14(4): 80-85, 108.
	Li Zhibin, Wang Wei, Li Xiaowei, et al. Spatial and Temporal Distribution Characteristics of Traffic Accident for Highway Vehicle Queue Tail[J]. Journal of Traffic and Transportation Engineering, 2014, 14(4): 80-85, 108.
28	Yang Hao, Rakha H, Ala M V. Eco-cooperative Adaptive Cruise Control at Signalized Intersections Considering Queue Effects[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(6): 1575-1585.

[1]	Xiao Peng, Xie Feng, Ni Haihong, Zhang Min, Tang Zhili, Li Ni. Research on Collaborative Optimization Method of Multi-UAV Task Allocation and Path Planning [J]. Journal of System Simulation, 2024, 36(5): 1141-1151.
[2]	Wan Yuanpeng, Liang Chengji, Wang Sihong, Wang Yu. Joint Distribution-Inventory Optimization and Simulation for Cold Chain Logistics Considering Order Substitution [J]. Journal of System Simulation, 2024, 36(3): 578-594.
[3]	Yan Shiliang, Wang Yinling, Lu Dandan, Pan Xiaoqin. Simulation and Optimization of Permanent Magnet Linear Machine Based on Deep Neural Network [J]. Journal of System Simulation, 2024, 36(3): 713-725.
[4]	Zhang Hongli, Deng Jingshuang. Research on Artificial Population Generation and Application Based on Genetic Algorithm [J]. Journal of System Simulation, 2023, 35(9): 1965-1974.
[5]	Yuwen Wu, Zhiyue Niu, Zhenping Li. Picking Path Planning of Container Robots Based on Improved Genetic Algorithm [J]. Journal of System Simulation, 2023, 35(5): 1086-1097.
[6]	Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu. Dual Resource Constrained Flexible Job Shop Energy-saving Scheduling Considering Delivery Time [J]. Journal of System Simulation, 2023, 35(4): 734-746.
[7]	Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma. Research on Unmanned Swarm Combat System Adaptive Evolution Model Simulation [J]. Journal of System Simulation, 2023, 35(4): 878-886.
[8]	Hucheng Zhang, Jingyu Yang. Research on Intelligent Optimization Method of Combat SoS Based on GABC Algorithm [J]. Journal of System Simulation, 2023, 35(1): 221-227.
[9]	Jia Xu, Fengqing Han, Qixin Liu, Xiaoxia Xue. Bioinformation Heuristic Genetic Algorithm for Solving TSP [J]. Journal of System Simulation, 2022, 34(8): 1811-1819.
[10]	Meng Yu, Zhenli Xu, Tianjiao Tan. Scheduling Optimization and Comparative Analysis of Twin 40 Feet Yard Crane Based on SAGA [J]. Journal of System Simulation, 2022, 34(8): 1885-1898.
[11]	Miao Yu, Manru Li, Yu Zhao. Joint Shift Scheduling Method for Call Center with Mechanism of Delay Information [J]. Journal of System Simulation, 2022, 34(7): 1651-1661.
[12]	Zhijie Li, Haoqi Shi, Changhua Li, Jie Zhang. Image Center Layout Optimization Method Based on Improved Genetic Algorithm [J]. Journal of System Simulation, 2022, 34(6): 1173-1184.
[13]	Jianlin Fu, Guofu Ding, Jian Zhang, Haifan Jiang, Peipei Guo. Multi-Objective Optimization Configuration of AGV System Based on Response Surface and NSGA-II [J]. Journal of System Simulation, 2022, 34(5): 994-1002.
[14]	Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma. Simulation of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering [J]. Journal of System Simulation, 2022, 34(10): 2303-2311.
[15]	Wang Yutong, Ma Shiwei, Yang Yuanrui, Chen Chaoyu. Optimization and Prediction for Multi-robot Combination Maximum Coverage Area [J]. Journal of System Simulation, 2022, 34(1): 86-92.