Zhao De

Email Address
ceezde@nus.edu.sg


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    Publication
    Recognizing Metro-Bus Transfers from Smart Card Data
    (Taylor & Francis, 2018-11-05) De Zhao; Wei Wang; Chenyang Li; Yanjie Ji; Xiaojian Hu; Wenfu Wang; CIVIL AND ENVIRONMENTAL ENGINEERING
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    Publication
    Evaluating the Impacts of Bus Stop Design and Bus Dwelling on Operations of Multitype Road Users
    (Hindawi Limited, 2018) Zhang, J.; Li, Z.; Zhang, F.; Qi, Y.; Zhou, W.; Wang, Y.; Zhao, D.; Wang, W.; CIVIL AND ENVIRONMENTAL ENGINEERING
    On urban streets with bus stops, bus arrivals can disrupt traffic flows in the neighboring areas. Different stop designs have distinct influences on the road users. This study aims to evaluate how different types of bus stops affect the operations of vehicles, bicycles, and buses that pass by. Four types of stops that differ in geometric layout are examined. They are termed the shared bike/bus (Type 1), separated shared bike/bus (Type 2), vehicle/bus with inboard bike lane (Type 3), and bus bay with inboard bike lane (Type 4). Data are collected from eight sites in two cities of China. Results of data analysis show that different bus stop designs have quite different impacts on the neighboring traffic flows. More specifically, Type 3 stops create the least bicycle delay but the largest vehicle delay. Type 4 stops have the least impact on bicycle and vehicle operations, but occupy the most road space. Traffic operations are less affected by Type 1 stops than by Type 2 stops. Policy suggestions are discussed regarding the optimal design of bus stops that minimizes the total vehicle delay of all modes. © 2018 Jian Zhang et al.
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    Publication
    An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis
    (Hindawi Limited, 2018) Zhao, D; Wang, W; Ong, G.P; Ji, Y; CIVIL AND ENVIRONMENTAL ENGINEERING
    Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain. © 2018 De Zhao et al.