Journal of Transportation Systems Engineering and Information Technology ›› 2022, Vol. 22 ›› Issue (2): 91-108.DOI: 10.16097/j.cnki.1009-6744.2022.02.009
Special Issue: 2022年英文专栏
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XU Meng* 1 , LIU Tao2 , ZHONG Shao-peng3 , JIANG Yu4
Received:
2021-12-04
Revised:
2022-01-21
Accepted:
2022-02-11
Online:
2022-04-25
Published:
2022-04-23
Supported by:
徐猛* 1,刘涛2,钟绍鹏3,姜宇4
作者简介:
徐猛(1976- ),男,湖北松滋人,教授,博士
基金资助:
CLC Number:
XU Meng , LIU Tao , ZHONG Shao-peng , JIANG Yu. Urban Smart Public Transport Studies: A Review and Prospect[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 91-108.
徐猛, 刘涛, 钟绍鹏, 姜宇. 城市智慧公交研究综述与展望[J]. 交通运输系统工程与信息, 2022, 22(2): 91-108.
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URL: http://www.tseit.org.cn/EN/10.16097/j.cnki.1009-6744.2022.02.009
[1] 彭宏勤, 张国伍. 新技术对“十四五”及2035年交通运输系统发展的影响:“交通7+1论坛”第五十七次会议 [J]. 交通运输系统工程与信息, 2021, 21(4): 1- 5. [PENG H Q, ZHANG G W. Influence of new technologies on development of transportation in the 14thfive years and 2035[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 1-5.] [2] 王庆云,毛保华. 科技进步对交通运输系统发展的影响[J]. 交通运输系统工程与信息, 2020, 20(6): 1-8. [WANG Q Y, MAO B H. Impacts of science and technology on transportation[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(6): 1-8.] [3] 亿欧智库. 2019年中国智慧城市发展研究报告[R]. 亿欧智库, 2019. [EqualOcean Intelligence. 2019 Chinese smart city development research report[R]. EqualOcean Intelligence, 2019.] [4] 陆化普, 孙智源, 屈闻聪. 大数据及其在城市智能交通系统中的应用综述[J]. 交通运输系统工程与信息, 2015, 15(5): 45-52. [LU H P,SUN Z Y,QU W C. Big data and its applications in urban intelligent transportation system[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(5): 45-52.] [5] WELCH T F, WIDITA A. Big data in public transportation: A review of sources and methods[J]. Transport Reviews, 2019, 39(6): 795-818. [6] YAP M, MUNIZAGA M. Big data in the digital age and how it can benefit public transport users[J]. Research in Transportation Economics, 2018, 69: 615-620. [7] 吴存钱,陈利强,俞峥嵘,等. 基于公交数据大脑的云调度平台建设[J]. IT经理世界, 2021(2): 1-2. [WU C Q, CHEN L Q, YU Z R, et al. Cloud scheduling platform construction based on bus data brain[J]. CEO & CIO, 2021(2): 1-2.] [8] 百度百科. 智慧公交[OL]. (2021-09-21) [2021-12- 15]. https://baike.baidu.com/item/% E6% 99% BA% E6% 85% A7% E5% 85% AC% E4% BA% A4/13212511?fr= aladdin. [Baidu Encyclopedia. Smart transit[OL]. (2021- 09- 21) [2021- 12- 15]. https://baike.baidu.com/item/% E6%99%BA%E6%85%A7%E5%85%AC%E4%BA% A4/13212511?fr=aladdin.] [9] ZENG X. Evaluation of bus service capability based on IC card and GPS data[D]. Xi'an: Chang' an University, 2019. [10] CHAPLEAU R, CHU K, ALLARD B. Synthesizing AFC, APC, GPS and GIS data to generate performance and travel demand indicators for public transit[C]// Transportation Research Board Meeting, 2011. [11] AGARD B, MORENCY C, TRÉPANIER M. Mining public transport user behaviour from smart card data[J]. IFAC Proceedings Volumes, 2006, 39(3): 399-404. [12] LEE S G, HICKMAN M D. Travel pattern analysis using smart card data of regular users[C]. TRB 2011 Annual Meeting, 2011. [13] KURAUCHI F, SCHMÖCKER J D, SHIMAMOTO H, et al. Variability of commuters' bus line choice: An analysis of oyster card data[J]. Public Transport, 2014, 6 (1/2): 21-34. [14] MA X, LIU C, WEN H, et al. Understanding commuting patterns using transit smart card data[J]. Journal of Transport Geography, 2017, 58: 135-145. [15] BRIAND A S, CÔME E, TRÉPANIER M, et al. Analyzing year-to-year changes in public transport passenger behaviour using smart card data[J]. Transportation Research Part C: Emerging Technologies, 2017, 79: 274-289. [16] GAO S C. Study on bus passenger flow analysis and shortterm prediction based on multi-source data[D]. Huhhot: Inner Mongolia University of Technology, 2020. [17] FAROQI H, MESBAH M, KIM J. Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data[J]. Transportation Research Procedia, 2020, 48: 2621-2637. [18] 黄益绍, 韩磊. 基于改进极限学习机的公交站点短时客流预测方法[J]. 交通运输系统工程与信息, 2019, 19(4): 115-123. [HUANG Y S, HAN L. Short-term passenger flow prediction method on bus stop based on improved extreme learning machine[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(4): 115-123.] [19] LI Y. Feature analysis and optimization discriminant method of ultra-long bus routes based on intelligent bus data[D]. Chengdu: Southwest Jiaotong University, 2019. [20] XIANG Y. Research on customized bus route optimization based on BUS IC card data driven by passenger flow demand[D]. Beijing: Beijing Jiaotong University, 2020. [21] HUAN N, YAO E J, ZHANG J M. Demand-responsive passenger flow control strategies for metro networks considering service fairness and passengers' behavioural responses[J]. Transportation Research Part C: Emerging Technologies, 2021, 131: 103335. [22] 庞明宝, 陈茂林, 张宁. 基于 MAST 的智慧公交优化调度研究[J]. 交通运输系统工程与信息, 2017, 17(1): 143-149. [PANG M B, CHEN M L, ZHANG N. Scheduling optimization of intelligent public transport system based on MAST[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(1): 143-149.] [23] 马晓磊, 丁川, 于海洋, 等. 公共交通大数据挖掘与分析[M]. 北京: 人民交通出版社, 2017. [MA X L, DING C, YU H Y, et al. Public transportation big data mining and analysis[M]. Beijing: China Communications Press, 2017. ] [24] GUIDO G, ROGANO D, VITALE A, et al. Big data for public transportation: A DSS framework[C]//2017 5th IEEE International Conference on Models andTechnologies for Intelligent Transportation Systems (MTITS), IEEE, 2017: 872-877. [25] WEPULANON P, SUMALEE A, LAM W HK. Temporal signatures of passive Wi-Fi data for estimating bus passenger waiting time at a single bus stop[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(8): 3366-3376. [26] BIE Y, GONG X, LIU Z. Time of day intervals partition for bus schedule using GPS data[J]. Transportation Research Part C: Emerging Technologies, 2015, 60: 443- 456. [27] QI G, HUANG A, GUAN W, et al. Analysis and prediction of regional mobility patterns of bus travellers using smart card data and points of interest data[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(4): 1197-1214. [28] WU W, LIU R, JIN W, et al. Stochastic bus schedule coordination considering demand assignment and rerouting of passengers[J]. Transportation Research Part B: Methodological, 2019, 121: 275-303. [29] 杨信丰, 李引珍, 何瑞春. 基于服务水平的区域公交协调调度优化研究[J]. 系统工程, 2017, 35(6): 89-96. [YANG X F, LI Y Z, HE R C. Research on regional public transit coordinated scheduling optimization based on service level[J]. Systems Engineering, 2017, 35(6): 89-96. ] [30] JIN J G, TEO, K M, et al. Optimizing bus bridging services in response to disruptions of urban transit rail networks[J]. Transportation Science, 2016, 50(3): 790- 804. [31] XIONG J, CHEN B, HZ Z, et al. Optimal design of community shuttles with an adaptive- operator-selectionbased genetic algorithm[J]. Transportation Research Part C: Emerging Technologies, 2021, 126: 103109. [32] KANG L, LI H, SUN H, et al. First train timetabling and bus service bridging in intermodal bus-and-train transit networks[J]. Transportation Research Part B: Methodological, 2021, 149: 443-462. [33] LIU T, CATS O, GKIOTSALITIS K. A review of public transport transfer coordination at the tactical planning phase[J]. Transportation Research Part C: Emerging Technologies, 2021, 133: 103450. [34] 邬群勇, 万云鹏. 基于多指标协同的公交大站快车站点推荐方法[J]. 交通运输系统工程与信息, 2021, 21(1): 162-168. [WU Q Y, WAN Y P. Stop selection of limited-stop bus services based on multi-criteria collaboration[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(1): 162-168.] [35] WU W, LIU R, JIN W. Designing robust schedule coordination scheme for transit networks with safety control margins[J]. Transportation Research Part B: Methodological, 2016, 93: 495-519. [36] 胡笳, 罗书源, 赖金涛, 等. 自动驾驶对交通运输系统规划的影响综述[J]. 交通运输系统工程与信息, 2021, 21(5): 52-65. [HU J, LUO S Y, LAI J T, et al. A review of the impact of autonomous driving on transportation planning[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 52-65.] [37] WU J, KULCSÁR B, QU X. A modular, adaptive, and autonomous transit system (MAATS): A in-motion transfer strategy and performance evaluation in urban grid transit networks[J]. Transportation Research Part A: Policy and Practice, 2021, 151: 81-98. [38] LIU T, Ceder A. Analysis of a new public-transportservice concept: Customized bus in China[J]. Transport Policy, 2015, 39: 63-76. [39] QIU G, SONG R, HE S, et al. Clustering passenger trip data for the potential passenger investigation and line design of customized commuter bus[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(9): 3351-3360. [40] WANG J, YAMAMOTO T, LIU K. Key determinants and heterogeneous frailties in passenger loyalty toward customized buses: An empirical investigation of the subscription termination hazard of users[J]. Transportation Research Part C: Emerging Technologies, 2020, 115: 102636. [41] WANG J, YAMAMOTO T, LIU K. Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models [J]. Transport Policy, 2021, 105: 166-180. [42] HUANG D, GU Y, WANG S, et al. A two-phase optimization model for the demand-responsive customized bus network design[J]. Transportation Research Part C: Emerging Technologies, 2020, 111: 1-21. [43] GUO R, ZHANG W, GUAN W, et al. Time- dependent urban customized bus routing with path flexibility[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(4): 2381-2390. [44] DOU X, MENG Q, LIU K. Customized bus service design for uncertain commuting travel demand[J]. Transportmetrica A: Transport Science, 2021, 17(4): 1405-1430. [45] CHEN X, WANG Y, MA X. Integrated optimization for commuting customized bus stop planning, routing design, and timetable development with passenger spatialtemporal accessibility[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(4): 2060- 2075. [46] WANG Z, et al. Joint optimization of running route and scheduling for the mixed demand responsive feedertransit with time- dependent travel times[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(4): 2498-2509. [47] 王健, 曹阳, 王运豪. 考虑出行时间窗的定制公交线路车辆调度方法[J]. 中国公路学报, 2018, 31(5): 143- 150. [WANG J, CAO Y, WANG Y H. Customized bus route vehicle schedule method considering travel time windows[J]. China Journal of Highway and Transport, 2018, 31(5): 143-150.] [48] 马昌喜, 王超, 郝威, 等. 突发公共卫生事件下应急定制公交线路优化[J]. 交通运输工程学报, 2020, 20(3): 89-99. [MA C X, WANG C, HAO W, et al. Emergency customized bus route optimization under public health emergencies[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 89-99.] [49] 李瑞敏. 出行即服务(MaaS)概论[M]. 北京: 人民交通出版社, 2020. [LI R M. Introduction to mobility as a service (MaaS) [M]. Beijing: China Communications Press, 2020. ] [50] 刘向龙. 出行即服务(MaaS)研究与探索[M]. 北京: 人民交通出版社, 2021. [LIU X L. Research on mobility as a service (MaaS) [M]. Beijing: China Communications Press, 2021.] [51] 周里捷, 姚振平. 大型活动地面公共交通运营组织与调度系统[M]. 北京: 电子工业出版社, 2011. [ZHOU L J, YAO Z P. Road surface public transportation operations organization and scheduling systems for large events[M]. Beijing: Publishing House of Electronics Industry, 2011.] [52] WANG F Y, TANG S, SUI Y, et al. Toward intelligent transportation systems for the 2008 Olympics[J]. IEEE Intelligent Systems, 2003, 18(6): 8-11. [53] ZHU F, CHEN S, MAO Z H, et al. Parallel public transportation system and its application in evaluating evacuation plans for large-scale activities[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(4): 1728-1733. [54] GU W, YU J, JI Y, et al. Plan-based flexible bus bridging operation strategy[J]. Transportation Research Part C: Emerging Technologies, 2018, 91: 209-229. [55] LIANG J, WU J, QU Y, et al. Robust bus bridging service design under rail transit system disruptions[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 132: 97-116. [56] 何祖勇, 郭茜, 吴刚. 考虑时间容忍度的轨道交通应急接驳公交蓄车点选址研究[J]. 交通运输工程与信息学报, 2022, 20(1): 80-88. [HE Z Y, GUO Q, WU G. Depot location of emergency bridging bus for urban rail transit considering time tolerance[J]. Journal of Transportation Engineering and Information, Available Online, 2022, 20 (1): 80-88.] [57] LEE Y J, VUCHIC V R. Transit network design with variable demand[J]. Journal of Transportation Engineering, 2005, 131(1): 1-10. [58] OWAIS M, OSMAN M K. Complete hierarchical multiobjective genetic algorithm for transit network design problem[J]. Expert Systems with Applications, 2018, 114: 143-154. [59] YAO B, HU P, LU X, et al. Transit network design based on travel time reliability[J]. Transportation Research Part C: Emerging Technologies, 2014, 43: 233-248. [60] FENG X, ZHU X, QIAN X, et al. A new transit network design study in consideration of transfer time composition [J]. Transportation Research Part D: Transport and Environment, 2019, 66: 85-94. [61] KOUTSOPOULOS H N, ODONI A, WILSON N H M. Determination of headways as function of time varying characteristics on a transit network[J]. Computer Scheduling of Public Transport, 1985, 2(1): 391-413. [62] GKIOTSALITIS K. Coordinating feeder and collector public transit lines for efficient MaaS services[R]//100th Transportation Research Board (TRB) Annual Meeting, 2021. [63] DAKIC I, YANG K, MENENDEZ M, et al. On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram[J]. Transportation Research Part B: Methodological, 2021, 148: 38-59. [64] JHA S B, JHA J K, TIWARI M K. A multi-objective metaheuristic approach for transit network design and frequency setting problem in a bus transit system[J]. Computers & Industrial Engineering, 2019, 130(4): 166- 186. [65] CHAI S, LIANG Q. An improved NSGA-II algorithm for transit network design and frequency setting problem[J]. Journal of Advanced Transportation, 2020, 2020(4): 1- 20. [66] LIU Y, FENG X, DING C, et al. Electric transit network design by an improved artificial fish-swarm algorithm[J]. Journal of Transportation Engineering Part A: Systems, 2020, 146(8): 04020071. [67] HATZENBUHLER J, CATS O, JENELIUS E. Network design for line-based autonomous bus services[J/OL]. Transportation, 2021:1-36. [68] QUAK C B. Bus line planning: A passenger-oriented approach of the construction of a global line network and an efficient timetable [D]. Delft: Delft University, 2004. [69] GUDEN H, KEECI B, KARATAS M, et al. Inter-city bus scheduling with central city location and trip selection[J]. International Journal of Industrial Engineering: Theory, Applications and Practice, 2021, 27(6): 959-970. [70] VERBAS F C, MAHMASSANI H S, CHAN R. Stretching resources: Sensitivity of optimal bus frequency allocation to stop-level demand elasticities[J]. PublicTransport, 2015, 7(1): 1-20. [71] TIAN Q, WANG D Z W, LIN Y H. Service operation design in a transit network with congested common lines [J]. Transportation Research Part B: Methodological, 2021, 144: 81-102. [72] PARBO J, NIELSEN O A, PRATO C G. User perspectives in public transport timetable optimization [J]. Transportation Research Part C: Emerging Technologies, 2014, 48: 269-284. [73] TENG J, CHEN T, FAN W D. Integrated approach to vehicle scheduling and bus timetabling for an electric bus line[J]. Journal of Transportation Engineering, 2020, 146(2): 04019073. [74] 吴玲玲,黄正东. 基于多样性的大城市公共交通服务水平研究[J]. 交通运输系统工程与信息, 2019, 19(1): 222-227. [WU L L, HUANG Z D. Diversity as an indicator of urban public transit service quality[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(1): 222-227.] [75] 杨晓光, 安健, 刘好德, 等. 公交运行服务质量评价指标体系探讨[J]. 交通运输系统工程与信息, 2010, 10 (4): 13- 21. [YANG X G, AN J, LIU H D, et al. Evaluation architecture discussion of route-level transit service quality[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(4): 13-21] [76] GU Z Y. Analysis and evaluation method of operation characteristics of conventional bus system[D]. Chengdu: Southeast University, 2015. [77] HUO Y, LI W, CHEN Q. Modeling customer satisfaction for bus rapid transit in Changzhou, China[J]. Journal of Southeast University, 2016, 32(2): 233-239. [78] ZHOU Y Y, YAO L, CHEN Y Y, et al. Bus arrival time calculation model based on smart card data[J]. Transportation research Part C: Emerging Technologies, 2017, 74: 81-96. [79] KIM J, CORCORAN J. PAPAMANOLIS M. Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data [J]. Transportation Research Part C: Emerging Technologies, 2017, 83: 146-164. [80] WANG H. Research on bus passenger flow analysis and bus operation evaluation based on big data[D]. Lanzhou: Lanzhou Jiaotong University, 2018. [81] SHI Q, ZHANG K, WENG J, et al. Evaluation model of bus routes optimization scheme based on multi-source bus data[J]. Transportation Research Interdisciplinary Perspectives, 2021, 10(1): 100342. [82] ELTVED M, LEMAITRE P, PETERSEN N C. Estimation of transfer walking time distribution in multimodal public transport systems based on smart card data[J]. Transportation Research Part C, 2021, 132: 103332. [83] ZHANG X. Research on evaluation of intelligent behavior of unmanned vehicle through special region [D]. Beijing: Beijing Institute of Technology, 2015. [84] LI L, LO H K, XIAO F, et al. Mixed bus fleet management strategy for minimizing overall and emissions external costs[J]. Transportation Research Part D: Transport and Environment, 2016, 60: 104-118. [85] SHEN Y, ZHANG H, ZHAO J. Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore[J]. Transportation Research Part A: Policy and Practice, 2018, 113: 125-136. [86] BERTSIMAS D, SIAN N Y, YAN J. Joint frequencysetting and pricing optimization on multimodal transit networks at scale[J]. Transportation Science, 2020, 54(3): 839-853. [87] 毛保华. 公共交通服务能力是交通强国战略的重要标志[J]. 北京交通大学学报(社科版), 2018, 17(3): 1-8. [MAO B H. Public transport capacity is an important indicator of national strength in transport[J]. Journal of Beijing Jiaotong University (Social Science Edition), 2018, 17(3): 1-8.] [88] 毛保华, 孟冉, 陈海波. 城市轨道交通中信息技术的应 用与规范化管理[J]. 北京交通大学学报(社科版), 2020, 19(4): 15-22. [MAO B H, MENG R, CHEN H B. Application and standardized management of information technologies in urban rail transit[J]. Journal of Beijing Jiaotong University (Social Science Edition), 2020, 19(4): 15-22.] [89] 王庆云, 毛保华, 张国伍. 我国交通运输系统工程的演化[J]. 交通运输系统工程与信息, 2021, 21(5): 2-11. [WANG Q Y, MAO B H, ZHANG G W. Evolution of transportation systems engineering in China[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 2-11.] [90] 毛保华, 王敏, 何天健, 等. 城市公共交通服务水平研究回顾和展望[J]. 交通运输系统工程与信息, 2022, 22 (1): 2-13. [MAO B H , WANG M, HO T K , et al. A review and prospect of urban public transit level-ofservice research[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 2- 13.] |
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