针对站点人流爆发的公交运营策略优化研究
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摘要
为应对公交大力发展情形下涌现的公交供需不平衡问题,重点关注公交站点爆发性人流问题的解决,考虑供需严重失衡下的公交运营策略改进,以扩充线路公交运力,减轻站点爆发性人流对公交系统的冲击。所提人流爆发站点主要包括大型集会场所、商场及景区周边等具有预知性人流爆发可能的站点。运营策略改进方法主要是通过在原有公交线路基础上,布设区间小线路的方式,与大线路形成协调运营关系,共同完成线路站点的爆发性人流疏散,具体包括公交大线路运营优化、区间小线路规划及前二者的结合3种。为获得研究区域内全面、有效的线路运营策略,以社会福利最大化为目标建立非线性整数规划模型,求解大、小线路最优发车间隔及增配车辆数,并引进系统弹复性指数作为模型求解结果良莠的评价指标。为证明该运营策略优化方法的有效性,以哈尔滨市中心城区为研究区域,解决该区域站点人流爆发问题。通过模型构建、求解及结果评价,发现经策略改进后,区域爆发线路弹复性指数较优化之前提高35%,运营策略改进后的社会福利值较不优化情况提高2倍,所提运营策略优化方法在不同乘客规模及不同限制条件下均能够起到一定的系统维稳作用,运营策略改进方法能够缓解站点爆发性人流。
With the rapid development of public transit,an imbalance in supply and demand occurs more frequently. This study focused on the issue of explosive passenger flows at bus stations and endeavored to optimize the bus operational strategy for addressing the high imbalance in demand and supply. The study further aimed to find a universal method for expanding the capacity of the bus line to accommodate explosive passenger flows at stations and reduce the adverse impact on the bus system. Stations investigated in this study were mainly in the vicinity of large-scale gathering places, such as shopping malls and scenic spots. Optimization of the operational strategy involved building a shuttle line based on the normal bus line, and coordinating the evacuation of explosive passenger flows with the normal line operation. The strategy included a combination of normal line operation optimization and shuttle line planning. In order to obtain a comprehensive and effective line operational strategy in the study area, a nonlinear integer programming model was developed with the aim of maximizing social welfare to determine the best headway and the optimal number of additional vehicles. System resilience was used as the evaluation index of the model. In order to prove the effectiveness of the optimization model, Harbin city center was chosen as the research area for solving the explosive passenger flow problem. A model was constructed, solved, and evaluated. After optimization of the bus operational strategy, the resilience of the line that carries explosive passenger flows increases by 35% and the social welfare doubles. The operational strategy mentioned above can enhance system management for varying passenger numbers and different constraints. The proposed method can alleviate explosive passenger flows at bus stations.
With the rapid development of public transit,an imbalance in supply and demand occurs more frequently. This study focused on the issue of explosive passenger flows at bus stations and endeavored to optimize the bus operational strategy for addressing the high imbalance in demand and supply. The study further aimed to find a universal method for expanding the capacity of the bus line to accommodate explosive passenger flows at stations and reduce the adverse impact on the bus system. Stations investigated in this study were mainly in the vicinity of large-scale gathering places, such as shopping malls and scenic spots. Optimization of the operational strategy involved building a shuttle line based on the normal bus line, and coordinating the evacuation of explosive passenger flows with the normal line operation. The strategy included a combination of normal line operation optimization and shuttle line planning. In order to obtain a comprehensive and effective line operational strategy in the study area, a nonlinear integer programming model was developed with the aim of maximizing social welfare to determine the best headway and the optimal number of additional vehicles. System resilience was used as the evaluation index of the model. In order to prove the effectiveness of the optimization model, Harbin city center was chosen as the research area for solving the explosive passenger flow problem. A model was constructed, solved, and evaluated. After optimization of the bus operational strategy, the resilience of the line that carries explosive passenger flows increases by 35% and the social welfare doubles. The operational strategy mentioned above can enhance system management for varying passenger numbers and different constraints. The proposed method can alleviate explosive passenger flows at bus stations.
引文
[1] 郭闯.大型活动公交系统优化调度研究[D].哈尔滨:哈尔滨工业大学,2012. GUO Chuang. Optimal Scheduling of Public Transit for Large Special Events[D]. Harbin: Harbin Institute of Technology, 2012.
[2] 蔡培.大型活动地面公交调度优化研究[D].北京:北京交通大学, 2011. CAI Pei. Operation Optimization Study of Bus Transit System for Large Special Events[D]. Beijing: Beijing Jiaotong University, 2011.
[3] 龚晓岚, 魏中华.大型活动地面公交组织的仿真[J].华南理工大学学报:自然科学版,2008,36(10):51-56. GONG Xiao-lan, WEI Zhong-hua. Simulation of Ground Public Transportation Organization for Large-scale Public Activity[J]. Journal of South China University of Technology: Natural Science Edition, 2008, 36 (10): 51-56.
[4] 滕靖, 陈宇毅.大型活动下配合城轨交通客流集散的公交调度[J].系统工程理论与实践, 2012, 32(4):895-902. TENG Jing, CHEN Yu-yi. Bus Dispatching Method for Associating with Urban Rail Transit to Transport Passengers During Large-scale Events[J]. Systems Engineering - Theory & Practice, 2012, 32 (4): 895-902.
[5] 张迪.面向大型活动的公交专线设计方法研究[D].沈阳:东北大学, 2013. ZHANG Di. Public Special Transit Network Design in Mega-events[D]. Shenyang: Northeastern University, 2003.
[6] JERBY S, CEDER A. Optimal Routing Design for Shuttle Bus Service[J]. Transportation Research Record, 2006 (1971): 14-22.
[7] CEDER A, YIM Y. Integrated Smart Feeder/Shuttle Bus Service [J]. Journal of Advanced Transportation, 2013, 47 (6): 595-618.
[8] 邓连波, 高伟, 赖天珍.基于换乘网络的城市轨道交通关联公交接驳线网优化[J].铁道科学与工程学报,2012,9(6):77-83. DENG Lian-bo, GAO Wei, LAI Tian-zhen, et al. Optimal Design of Feeder-bus Network Related to Urban Rail Transit Based on Transfer Network[J]. Journal of Railway Science and Engineering, 2012, 9 (6): 77-83.
[9] ZHANG H, ZHAO S, LIU H, et al. Design of Integrated Limited-stop and Short-turn Services for a Bus Route[J]. Mathematical Problems in Engineering, 2016, 2016 (2): 1-9.
[10] QU H Z, CHIEN S I J, LIU X B, et al. Optimizing Bus Services with Variable Directional and Temporal Demand Using Genetic Algorithm[J]. Journal of Central South University, 2016, 23 (7): 1786-1798.
[11] TANG Chun-yan, CEDER A, GE Ying-en. Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand[J]. Journal of Advanced Transportation, 2017, 2017: 1-15.
[12] 孙传姣, 周伟, 王元庆.快速公交车辆调度组合及发车间隔优化研究[J].交通运输系统工程与信息, 2008,8(5):61-67. SUN Chuan-jiao, ZHOU Wei, WANG Yuan-qing. Scheduling Combination and Headway Optimation of Bus Rapid Transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2008, 8 (5): 61-67.
[13] 明洁, 张贵军, 刘玉栋.多模式公交组合优化调度模型[J].计算机科学, 2015,42(9):263-267. MING Jie, ZHANG Gui-jun, LIU Yu-dong. Combinatorial Optimization Model of Multi-modal Transit Scheduling[J]. Computer Science, 2015, 42 (9): 263-267.
[14] 郑喆, 韩印, 赵靖.基于发车和运营时刻表的单线公交组合调度模型[J].物流科技, 2017, 40(7):86-90. ZHENG Zhe, HAN Yin, ZHAO Jing. A Single Line Transit Mixed Scheduling Model Based on Vehicle Departure and Operation Timetable [J]. Logistics Sci-Tech, 2017, 40 (7): 86-90.
[15] 詹静.低需求区域发展需求响应式公交运营模式及适应性研究[D].重庆:重庆交通大学, 2016. ZHAN Jing. Study on the Operating Mode and Adaptability of Demand Responsive Transport Develop in Low Demand Area [D]. Chongqing: Chongqing Jiaotong University, 2016.
[16] LIU Z, YAN Y, QU X, et al. Bus Stop-skipping Scheme with Random Travel Time [J]. Transportation Research Part C, 2013, 35 (9): 46-56.
[17] AN S, ZHANG X. Real-time Hybrid In-station Bus Dispatching Strategy Based on Mixed Integer Programming [J]. Information, 2016, 7 (3): 1-12.
[18] 宋瑞,何世伟,杨永凯,等.公交时刻表设计与车辆运用综合优化模型[J].中国公路学报,2006,19(3):70-76. SONG Rui, HE Shi-wei, YANG Yong-kai, et al. Integrated Optimization Model of Transit Scheduling [J]. China Journal of Highway and Transport, 2006, 19 (3): 70-76.
[19] 杨金顺,孙洪运,李林波,等.道路交通系统恢复力研究进展综述[J].交通信息与安全,2014,32(3):87-92. YANG Jin-shun, SUN Hong-yun, LI Lin-bo, et al. Review of Road Transportation System Resilience Research [J]. Journal of Transport Information and Safety, 2014, 32 (3): 87-92.
[20] MILLER-H E, ZHANG X, FATURECHI R. Measuring and Maximizing Resilience of Freight Transportation Networks[J]. Compute & Operations Research, 2012, 39: 1633-1643.
[21] FATURECHI R, MILLER-H E. Travel Time Resilience of Roadway Networks Under Disaster[J]. Transportation Research Part B, 2014, 70: 47-64.
[22] JIN J G, TANG L C, SUN L, et al. Enhancing Metro Network Resilience via Localized Integration with Bus Services[J]. Transportation Research Part E, 2014, 63 (2): 17-30.
[23] 吕慎,陶流洋,莫一魁.通勤出行公交候车时间的服务等级划分和度量[J].交通运输系统工程与信息,2015,15(3):190-195,221. Lü Shen, TAO Liu-yang, MO Yi-kui. Level of Service Classification and Quantification for Bus Waiting Time on Commuting Trip [J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15 (3): 190-195, 221.
[2] 蔡培.大型活动地面公交调度优化研究[D].北京:北京交通大学, 2011. CAI Pei. Operation Optimization Study of Bus Transit System for Large Special Events[D]. Beijing: Beijing Jiaotong University, 2011.
[3] 龚晓岚, 魏中华.大型活动地面公交组织的仿真[J].华南理工大学学报:自然科学版,2008,36(10):51-56. GONG Xiao-lan, WEI Zhong-hua. Simulation of Ground Public Transportation Organization for Large-scale Public Activity[J]. Journal of South China University of Technology: Natural Science Edition, 2008, 36 (10): 51-56.
[4] 滕靖, 陈宇毅.大型活动下配合城轨交通客流集散的公交调度[J].系统工程理论与实践, 2012, 32(4):895-902. TENG Jing, CHEN Yu-yi. Bus Dispatching Method for Associating with Urban Rail Transit to Transport Passengers During Large-scale Events[J]. Systems Engineering - Theory & Practice, 2012, 32 (4): 895-902.
[5] 张迪.面向大型活动的公交专线设计方法研究[D].沈阳:东北大学, 2013. ZHANG Di. Public Special Transit Network Design in Mega-events[D]. Shenyang: Northeastern University, 2003.
[6] JERBY S, CEDER A. Optimal Routing Design for Shuttle Bus Service[J]. Transportation Research Record, 2006 (1971): 14-22.
[7] CEDER A, YIM Y. Integrated Smart Feeder/Shuttle Bus Service [J]. Journal of Advanced Transportation, 2013, 47 (6): 595-618.
[8] 邓连波, 高伟, 赖天珍.基于换乘网络的城市轨道交通关联公交接驳线网优化[J].铁道科学与工程学报,2012,9(6):77-83. DENG Lian-bo, GAO Wei, LAI Tian-zhen, et al. Optimal Design of Feeder-bus Network Related to Urban Rail Transit Based on Transfer Network[J]. Journal of Railway Science and Engineering, 2012, 9 (6): 77-83.
[9] ZHANG H, ZHAO S, LIU H, et al. Design of Integrated Limited-stop and Short-turn Services for a Bus Route[J]. Mathematical Problems in Engineering, 2016, 2016 (2): 1-9.
[10] QU H Z, CHIEN S I J, LIU X B, et al. Optimizing Bus Services with Variable Directional and Temporal Demand Using Genetic Algorithm[J]. Journal of Central South University, 2016, 23 (7): 1786-1798.
[11] TANG Chun-yan, CEDER A, GE Ying-en. Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand[J]. Journal of Advanced Transportation, 2017, 2017: 1-15.
[12] 孙传姣, 周伟, 王元庆.快速公交车辆调度组合及发车间隔优化研究[J].交通运输系统工程与信息, 2008,8(5):61-67. SUN Chuan-jiao, ZHOU Wei, WANG Yuan-qing. Scheduling Combination and Headway Optimation of Bus Rapid Transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2008, 8 (5): 61-67.
[13] 明洁, 张贵军, 刘玉栋.多模式公交组合优化调度模型[J].计算机科学, 2015,42(9):263-267. MING Jie, ZHANG Gui-jun, LIU Yu-dong. Combinatorial Optimization Model of Multi-modal Transit Scheduling[J]. Computer Science, 2015, 42 (9): 263-267.
[14] 郑喆, 韩印, 赵靖.基于发车和运营时刻表的单线公交组合调度模型[J].物流科技, 2017, 40(7):86-90. ZHENG Zhe, HAN Yin, ZHAO Jing. A Single Line Transit Mixed Scheduling Model Based on Vehicle Departure and Operation Timetable [J]. Logistics Sci-Tech, 2017, 40 (7): 86-90.
[15] 詹静.低需求区域发展需求响应式公交运营模式及适应性研究[D].重庆:重庆交通大学, 2016. ZHAN Jing. Study on the Operating Mode and Adaptability of Demand Responsive Transport Develop in Low Demand Area [D]. Chongqing: Chongqing Jiaotong University, 2016.
[16] LIU Z, YAN Y, QU X, et al. Bus Stop-skipping Scheme with Random Travel Time [J]. Transportation Research Part C, 2013, 35 (9): 46-56.
[17] AN S, ZHANG X. Real-time Hybrid In-station Bus Dispatching Strategy Based on Mixed Integer Programming [J]. Information, 2016, 7 (3): 1-12.
[18] 宋瑞,何世伟,杨永凯,等.公交时刻表设计与车辆运用综合优化模型[J].中国公路学报,2006,19(3):70-76. SONG Rui, HE Shi-wei, YANG Yong-kai, et al. Integrated Optimization Model of Transit Scheduling [J]. China Journal of Highway and Transport, 2006, 19 (3): 70-76.
[19] 杨金顺,孙洪运,李林波,等.道路交通系统恢复力研究进展综述[J].交通信息与安全,2014,32(3):87-92. YANG Jin-shun, SUN Hong-yun, LI Lin-bo, et al. Review of Road Transportation System Resilience Research [J]. Journal of Transport Information and Safety, 2014, 32 (3): 87-92.
[20] MILLER-H E, ZHANG X, FATURECHI R. Measuring and Maximizing Resilience of Freight Transportation Networks[J]. Compute & Operations Research, 2012, 39: 1633-1643.
[21] FATURECHI R, MILLER-H E. Travel Time Resilience of Roadway Networks Under Disaster[J]. Transportation Research Part B, 2014, 70: 47-64.
[22] JIN J G, TANG L C, SUN L, et al. Enhancing Metro Network Resilience via Localized Integration with Bus Services[J]. Transportation Research Part E, 2014, 63 (2): 17-30.
[23] 吕慎,陶流洋,莫一魁.通勤出行公交候车时间的服务等级划分和度量[J].交通运输系统工程与信息,2015,15(3):190-195,221. Lü Shen, TAO Liu-yang, MO Yi-kui. Level of Service Classification and Quantification for Bus Waiting Time on Commuting Trip [J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15 (3): 190-195, 221.