Electric Bus Area Driving Plan Preparation Considering Charging Constraints

被引:0
作者
Yao E. [1 ]
Lu M. [1 ]
Liu Y. [1 ,2 ]
Yuan L. [1 ,3 ]
机构
[1] School of Traffic and Transportation, Beijing Jiaotong University, Beijing
[2] Beijing Institute of Transportation Development, Beijing
[3] Guizhou Urban and Rural Planning and Design Institute, Guiyang, 550004, Guizhou
来源
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2019年 / 47卷 / 09期
关键词
Charging constraint; Compound solution algorithm; Electric bus; Operation plan model; Regional scheduling; Urban traffic;
D O I
10.12141/j.issn.1000-565X.180553
中图分类号
学科分类号
摘要
Electric vehicles are widely used for their excellent characteristics such as low pollution and high comfort with the increasing environmental pollution of fuel vehicles and the increasing emphasis on passenger comfort by public transportation. However, due to the limitation of cruising range and charging demand, electric vehicles driving plan is rather complicated. Under the premise of multi-station regional scheduling mode, this study fully considered the occurrence and execution of charging tasks, and the optimization of total fixed cost and total opera-ting cost including electric bus and its supporting facilities. The regional driving plan was modeled, and a compound solving algorithm was designed based on genetic algorithm and greedy algorithm to solve the model. Finally, the ope-ration plan model was verified by taking some line operations in Daxing District of Beijing as an example, and compared with the traditional bus planning method. The results show that the total operating cost is reduced by 18.20%. © 2019, Editorial Department, Journal of South China University of Technology. All right reserved.
引用
收藏
页码:68 / 73
页数:5
相关论文
共 10 条
[1]  
Shen Y., Xia J., Initial research on applying the multi-routes model for bus operations in China, Science & Technology Progress and Policy, 8, pp. 88-90, (2004)
[2]  
Yu L., Study on simulated annealing and genetic algorithm in regional bus scheduling, Journal of Langfang Teachers College (Natural Science Edition), 14, 2, pp. 16-21, (2014)
[3]  
Lawrence B., Bruce G., Classification in vehicle routing and scheduling, Networks, 11, 2, pp. 97-108, (1981)
[4]  
Liu Z.-G., Shen J.-S., Yang W., Regional bus scheduling model based on taboo search, Journal of Transportation Engineering and Information, 15, 4, pp. 63-67, (2007)
[5]  
Benoit L., Hao J., Iterated local search for the multiple depot vehicle scheduling problem, Computers & Industrial Engineering, 57, 1, pp. 277-286, (2009)
[6]  
Marc N., Leena S., Stefan K., A stochastic programming approach for robust vehicle scheduling in public bus transport, Procedia-Social and Behavioral Sciences, 20, 20, pp. 826-835, (2011)
[7]  
Yang Y., Guan W., Ma J., Battery electric transit bus scheduling problem based on column generation approach, Journal of Transportation Systems Engineering and Information Technology, 16, 5, pp. 198-204, (2016)
[8]  
Freling R., Wagelmans A.P.M., Pinto Pazxao Jose M., Models and algorithms for single-depot vehicle scheduling, Transportation Science, 35, 2, pp. 165-180, (2001)
[9]  
Haghani A., Banihashemi M., Heuristic approaches for solving large-scale bus transit vehicle scheduling problem with route time constraints, Transportation Research Part A, 36, 4, pp. 309-333, (2002)
[10]  
Wei M., Jin W., Sun B., Reliability of regional bus scheduling problem, Journal of South China University of Technology (Natural Science Edition), 40, 2, pp. 50-56, (2012)