Analysing the relationship between weather, built environment, and public transport ridership (English)
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- New search for: Lin, Pengfei
- New search for: Weng, Jiancheng
- New search for: Brands, Devi K.
- New search for: Qian, Huimin
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In:
IET Intelligent Transport Systems
;
14
, 14
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1946-1954
;
2021
- Article (Journal) / Electronic Resource
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Title:Analysing the relationship between weather, built environment, and public transport ridership
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Contributors:Lin, Pengfei ( author ) / Weng, Jiancheng ( author ) / Brands, Devi K. ( author ) / Qian, Huimin ( author ) / Yin, Baocai ( author )
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Published in:IET Intelligent Transport Systems ; 14, 14 ; 1946-1954
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Publisher:
- New search for: The Institution of Engineering and Technology
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Publication date:2021-02-22
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Size:9 pages
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:weather conditions , built environment variables , sustainable public transport system , smart cards , interaction effects , adverse weather , rain , geophysics computing , weather information , public transport ridership , smart card data , nonlinear relationship , ridership fluctuations , road traffic , traffic engineering computing , daily ridership , influence mechanisms , Light Gradient Boosted Machine , traffic analysis zone level , environment separately , threshold effects , scheduling service frequency , regression analysis , public transport networks
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Source:
Metadata by IET is licensed under CC BY 3.0
Table of contents – Volume 14, Issue 14
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1935
-
Robust fault-tolerant H∞ output feedback control of active suspension and dynamic vibration absorber with finite-frequency constraintZhang, Yuanzhi / Liu, Mingchun / Zhang, Caizhi et al. | 2021
- 1946
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Analysing the relationship between weather, built environment, and public transport ridershipLin, Pengfei / Weng, Jiancheng / Brands, Devi K. / Qian, Huimin / Yin, Baocai et al. | 2021
- 1955
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Vehicles robust scheduling of hazardous materials based on hybrid particle swarm optimisation and genetic algorithmMa, Changxi / Liu, Pengfei / Xu, Xuecai et al. | 2020
- 1967
-
Energy-efficient approach combining train speed profile and timetable optimisations for metro operationsRan, Xin-Chen / Chen, Shao-Kuan / Liu, Ge-Hui / Bai, Yun et al. | 2021
- 1978
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Short-term traffic congestion prediction with Conv–BiLSTM considering spatio-temporal featuresLi, Tao / Ni, Anning / Zhang, Chunqin / Xiao, Guangnian / Gao, Linjie et al. | 2021
- 1987
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Hybrid model for predicting anomalous large passenger flow in urban metrosZheng, Zhihao / Ling, Ximan / Wang, Pu / Xiao, Jianhe / Zhang, Fan et al. | 2021
- 1997
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Multi‐step traffic speed prediction model with auxiliary features on urban road networks and its understandingGuo, Jinlong / Song, Chunyue / Zhang, Hao / Wang, Hui et al. | 2020
- 2010
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Novel mathematical model to determine geo-referenced locations for C-ITS communications to generate dynamic vehicular gapsBhargava, Kushagra / Wah Choy, Kum / Jennings, Paul A. / Higgins, Matthew D. et al. | 2021
- 2021
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Powered‐two‐wheelers and smart cities: the case of variable message signsSpyropoulou, Ioanna / Impersimi, Eriola et al. | 2020
- 2030
-
Adaptive traffic signal control system using composite reward architecture based deep reinforcement learningJamil, Abu Rafe Md / Ganguly, Kishan Kumar / Nower, Naushin et al. | 2021
- 2042
-
Sequence-based centrality measures in maritime transportation networksLi, Jing / Wang, Xuantong / Zhang, Tong et al. | 2021
- 2052
-
Deep learning enabled vehicle trajectory map‐matching method with advanced spatial–temporal analysisLiu, Zhijia / Fang, Jie / Tong, Yingfang / Xu, Mengyun et al. | 2020
- 2064
-
Lane‐changing decision method based Nash Q‐learning with considering the interaction of surrounding vehiclesZhou, Xiaochuan / Kuang, Dengming / Zhao, Wanzhong / Xu, Can / Feng, Jian / Wang, Chunyan et al. | 2020
- 2073
-
Efficient deep learning based method for multi‐lane speed forecasting: a case study in BeijingLu, Wenqi / Yi, Ziwei / Liu, Wan / Gu, Yuanli / Rui, Yikang / Ran, Bin et al. | 2020
- 2083
-
Predicting driver behaviour at intersections based on driver gaze and traffic light recognitionRahman, Md. Junaedur / Beauchemin, Steven S. / Bauer, Michael A. et al. | 2021
- 2092
-
Multi‐model adaptive predictive control for path following of autonomous vehiclesLiang, Yixiao / Li, Yinong / Khajepour, Amir / Zheng, Ling et al. | 2020
- 2102
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Multi‐mode switching‐based model predictive control approach for longitudinal autonomous driving with acceleration estimationQu, Ting / Zhao, Junwu / Gao, Huihua / Cai, Kunyang / Chen, Hong / Xu, Fang et al. | 2020
- 2113
-
Analysis on cruising process for on-street parking using an spectral clustering methodQin, Huanmei / Pang, Qianqian / Yu, Binhai / Wang, Zhongfeng et al. | 2021
- 2122
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Coordinated control of steer‐by‐wire and brake‐by‐wire for autonomous emergency braking on split‐μ roadsXue, Zhongjin / Li, Chenfeng / Wang, Xiangyu / Li, Liang / Zhong, Zhihua et al. | 2020
- 2133
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Dynamic motion planner with trajectory optimisation for automated highway lane-changing drivingLiu, Xiao / Liang, Jun / Zhang, Hua et al. | 2021
- 2141
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FRAC: a flexible resource allocation for vehicular cloud systemPradhan, Srikanta / Tripathy, Somanath et al. | 2021
- 2151
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Localisation algorithm for security access control in railway communicationsLi, Jing / Wu, Hao et al. | 2020