Volume 40 Issue 3
Jun.  2022
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Article Navigation >  Journal of Transport Information and Safety  > 2022  >  40(3): 154-162
ZHANG Yue, SUN Lishan, KONG Dewen, ZHANG Xin. Accessing the Impacts of Curb Parking Behavior on Traffic Flows Through Cellular Automata Models[J]. Journal of Transport Information and Safety, 2022, 40(3): 154-162. doi: 10.3963/j.jssn.1674-4861.2022.03.016
Citation: ZHANG Yue, SUN Lishan, KONG Dewen, ZHANG Xin. Accessing the Impacts of Curb Parking Behavior on Traffic Flows Through Cellular Automata Models[J]. Journal of Transport Information and Safety, 2022, 40(3): 154-162. doi: 10.3963/j.jssn.1674-4861.2022.03.016
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Accessing the Impacts of Curb Parking Behavior on Traffic Flows Through Cellular Automata Models

doi: 10.3963/j.jssn.1674-4861.2022.03.016
  • 1.

    Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China

  • 2.

    Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China

  • 3.

    Government Service Center of Beijing Municipal Transport Commission (Beijing Boats Inspection Center), Beijing 100124, China

  • Received Date: 2021-12-30
    Available Online: 2022-07-25
    Abstract
  • Curb parking may lead to several traffic issues, such as queue delay, slow traffic due to low-speed cruising, and reduced road capacity because of excessive parking spaces. In order to mitigate these issues, the impacts of curb parking on traffic flows are studied. Data of vehicle trajectory and speed is collected based on video recognition technique. Then, the characteristics of driving behaviors of the vehicles which use curb parking are analyzed. According to differences of driving behaviors, the process of curb parking is divided into eight steps: driving into the road, cruising for a parking space, finding a parking space, entering the space, parking, leaving the space, merging into traffic, and missing a parking space. Based on extracted data of parking and cruising behaviors of curb parking vehicles, a cellular automata model is proposed by taking multiple features into consideration, including their characteristics of car following, speed correcting, lane changing, and position updating. Time costs of both parking a vehicle and walking to destination are also considered for searching a target parking space. Compared with other vehicles, the impacts of behaviors of curb parking on the following vehicles, i.e., lane changing and lane merging, are analyzed. Besides, parameters of a simulation model are calibrated based on observed data of traffic flow, and the result shows that the degree of fit is 77.6%. Moreover, the influences of cruising speed on road capacity and delay time are analyzed by a simulation under differentiated parking intensities. The results show that delay time first increases, then decreases with the rise of traffic volume at a fixed cruising speed and parking intensity. At a low parking intensity, the impact of cruising speed on road capacity is small. In a scenario of high-volume traffic, when cruising speed declines from 30 km/h to 20 km/h, the saturation flow of outer lanes decreases by 500 veh/h, and the maximum delay time increases by 105 s.

     

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