基于元胞自动机模型的路侧停车行为对交通流的影响研究

张月; 孙立山; 孔德文; 张鑫

doi:10.3963/j.jssn.1674-4861.2022.03.016

基于元胞自动机模型的路侧停车行为对交通流的影响研究

doi: 10.3963/j.jssn.1674-4861.2022.03.016

张月^{1, 2,},
孙立山^2, ,,
孔德文²,
张鑫³

1.
广州市城市规划勘测设计研究院广州 510060
2.
北京工业大学北京市交通工程重点实验室北京 100124
3.
北京市交通委员会政务服务中心（北京市船舶检验所）北京 100124

基金项目:

国家自然科学基金项目 52002008

北京市自然科学基金项目 9214022

北京市自然科学基金项目 L201008

详细信息

作者简介:
张月（1996—），硕士研究生. 研究方向：交通规划与管理. E-mail：1477804214@qq.com

通讯作者:
孙立山（1976—），博士，教授. 研究方向：交通规划与管理. E-mail：lssun@bjut.edu.cn

中图分类号: U491.7
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出版历程
- 收稿日期: 2021-12-30
- 网络出版日期: 2022-07-25

Accessing the Impacts of Curb Parking Behavior on Traffic Flows Through Cellular Automata Models

ZHANG Yue^{1, 2
,},
SUN Lishan^{2
, ,},
KONG Dewen²,
ZHANG Xin³

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

摘要

摘要: 针对路侧停车带来的进出停车位排队延误、低速巡游降低通行效率、过量停车加剧交通负荷等问题，研究了路侧停车对路段动态交通流的影响分析方法。基于视频识别算法，提取路侧停车车辆在驶入车位过程中的运行轨迹和速度波动数据，解析路侧停车过程中的驶入行为特性，并按照行为差异将停车车辆停车全过程细分为进入路段、寻找车位、找到车位、驶入车位、静止停放、驶离车位、汇入路段和错失车位8类状态；分别依据停车车辆和通行车辆的实际驾驶行为，从跟驰特征、速度矫正、换道规则和位置更新等方面对路侧停车元胞自动机模型进行了改进；在选择目标车位时综合考虑了步行至目的地时间和驶入车位耗时2个要素。与常规通行车辆相比，深入分析了停车车辆提前换道和停车完后汇入路段行为对后车的影响。基于实际交通流数据对仿真模型进行参数标定，经验证，模型拟合度为77.6%；仿真分析了在差异化的停车需求强度下，巡游速度对道路通行能力和延误时间的影响规律。结果表明：固定的巡游速度和停车需求强度下，道路延误时间随道路交通量先增加后减少；在低停车需求强度下，巡游速度对道路通行能力影响微弱，在高停车需求强度下，当巡游速度从30 km/h降低至20 km/h，外侧车道饱和流量降低500 veh/h，最高延误时间增加105 s。
- 城市交通 /
- 路侧停车 /
- 交通影响评价 /
- 微观仿真 /
- 元胞自动模型
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.
- urban traffic /
- curb parking /
- traffic impact assessment /
- microscope simulation /
- cellular automatic model

HTML全文

图 1 道路示例

Figure 1. The road sample of one-way two lane road

下载: 全尺寸图片幻灯片

图 2 车辆驶入单一空位时驾驶状态解析

Figure 2. Parking status analysis of vehicles entering the parking space of only one space

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图 3 路侧停车仿真场景示意图

Figure 3. The schematic of curb parking simulation

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图 4 车辆巡游轨迹图

Figure 4. Trajectories of cruising vehicles

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图 5 车辆驶入车位轨迹图

Figure 5. Trajectories of entering space vehicles

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图 6 巡游速度对道路交通流量的影响

Figure 6. Traffic flow under different input flow and cruise speed

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图 7 巡游速度对延误时间的影响

Figure 7. Average travel delay under different input flow and cruise speed

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表 1 车辆驶入单一空位时的关键点与时长

Table 1. Parking entry key points and usage time of only one space

车辆特征	正在换道	开始摆正	开始旋转	后退进入	静止停车
坐标	（-14，-4）	（-2.5，-2.5）	（10，-5）	（2，-5）	（0.5，-0.5）
时间/mm：ss	00：01	00：03	00：07	00：17	00：37
时间/s		未知	4	10	20

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表 2 路侧停车车辆状态划分

Table 2. Curb parking vehicle status division

具体特征	序号
具体特征	1	2	3	4	5	6	7	8
驾驶状态	进入路段	寻找车位	找到车位	驶入车位	静止停放	驶离车位	汇入车流	错失车位
速度特征	正常	低速	减速	静止	静止	加速	正常	正常
车辆位置	路段上游	停车路段	车位上游	车位内	车位内	车位内	车位下游	路段下游

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表 3 仿真模型中的参数取值

Table 3. Model parameters of rules used in simulation

名称	值	名称	值
dec /(m/s²)	3	t₀ /s	5
l_max^v/m	20	^pmin	0.5
l_max^c/m	40	^pmax	0.95

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表 4 速度平均相对误差

Table 4. Mean relative error of speed

实际数据		仿真数据		相对误差/%
流量（/veh/h）	速度（/km/h）	流量（/veh/h）	速度（/km/h）	相对误差/%
96	39	96	37.9	2.82
172	40	172	37.7	5.75
260	36.5	260	37.3	2.19
440	39.4	440	36.1	8.38
288	36.7	288	37.1	1.09
476	38.5	476	35.9	6.75
600	35.6	600	35.5	0.28
520	36.3	520	35.8	1.38
700	33.4	700	34.9	4.49
880	28	880	32.7	16.79
800	30.1	800	33.7	11.96
1 160	23.2	1 160	25	7.76
拟合度				77.6%

下载: 导出CSV

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