[1]景立竹,李群善,许金良,等.基于v/C比和载重汽车混入率的高速公路基本路段车辆平均行程时间预测模型[J].长安大学学报(自然科学版),2018,38(05):106-113.
　JING Li zhu,LI Qun shan,XU Jin liang,et al.Average travel time prediction model in basic expresswaysections based on v/C ratio and truck percentage[J].Journal of Chang’an University (Natural Science Edition),2018,38(05):106-113.
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基于v/C比和载重汽车混入率的高速公路基本路段车辆平均行程时间预测模型()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第38卷
期数:
2018年05期
页码:
106-113
栏目:
交通工程
出版日期:
2018-09-30

文章信息/Info

Title:
Average travel time prediction model in basic expresswaysections based on v/C ratio and truck percentage
作者:
景立竹; 李群善; 许金良; 贾兴利; 刘江; 韩跃杰
1. 长安大学 公路学院，陕西 西安 710064； 2. 青海省交通建设工程造价管理站，青海 西宁 810003；3. 中国电建集团西北勘测设计研究院有限公司，陕西 西安 710065）
Author(s):
JING Lizhu1;  LI Qunshan2;  XU Jinliang1;  JIA Xingli1;  LIU Jiang3;  HAN Yuejie1
关键词:
交通工程; 行程时间; 预测模型; 高速公路基本路段; v/C比; 载重汽车混入率; 通行效率
Keywords:
traffic engineering;  travel time;  prediction model;  basic expressway section;  v/C ratio;  truck percentage;  traffic efficiency
文献标志码:
A
摘要:
为了研究高速公路交通流状态对车辆通行时间的影响，以路段交通流饱和度v/C比（v为路段交通量，C为通行能力）和载重汽车混入率P作为综合反映交通流状态的基本指标。在P保持一致的前提下，在西安绕城高速公路选择满足特定几何条件的基本路段作为试验路段，采用基于媒体访问控制（MAC）地址的交通数据采集设备开展行程时间测定试验，采集小客车和两轴轻型载重汽车在不同v/C比下的行程时间数据。在此基础上，提出单位距离平均行程时间概念，采用SPSS回归分析法，分别建立适用于小客车和载重汽车的单位距离平均行程时间随v/C比呈指数变化的关系模型，并通过对比试验，对模型在不同线形条件下的适用性和预测结果准确性进行检验。以参数敏感性分析为依据，利用正交试验对VISSIM软件中的最小车头时距、平均停车距离、驾驶人期望车头时距3个仿真参数进行校准与修正，在此基础上开展不同P条件下的车辆平均行程时间仿真试验。结果表明：当P不同时，车辆单位距离平均行程时间预测模型中的3个修正系数也不相同；在P∈［0%,50%］、v/C∈［0.15,1.25］条件下，P越大，同一车型在同一v/C比状态下的单位距离平均行程时间也越大；与载重汽车相比，v/C比改变对小客车单位距离平均行程时间的影响更显著。研究结论可以为降低出行者时间成本、提高区域交通运行效率提供指导。
Abstract:
To reveal how traffic flow conditions influence travel time, traffic flow volume to capacity (v/C) ratios （where, v and C is traffic volume and capacity of road section） and truck percentages P were selected as indices to reflect traffic flow status. Several basic expressway sections that met specific geometric requirements were chosen as test sections along the Xian Loop Expressway. Traffic travel time data for both passenger cars and twoaxle lightduty trucks with different v/C ratios were collected using MACaddressbased equipment. Based on this, the concept of average travel time per kilometer was proposed, and SPSS regression analysis was used to establish prediction models of the exponential travel time that could be applied to trucks and passenger cars. The accuracies of the prediction models and their applicability under different geometric conditions were also tested and verified through comparative experiments. Based on parameter sensitivity analysis, the values of minimum headway, average stopping distance, and drivers expected headway in VISSIM were calibrated using the method of orthogonal experimental design. The results show that the values of the 3 correction factors in travel time prediction models are different with respect to different truck percentages. The greater the P, the longer the average travel time per kilometer for a given v/C ratio. The change in v/C ratio has a greater influence on a passenger cars average travel time per kilometer than on a trucks. Based on the simulation experiments, travel time prediction models were proposed for v/C ratios from 0.15 to 1.25 and truck percentages from 0% to 50%. The results of this study contribute toward saving travel time and improving traffic efficiency. 3 tabs, 4 figs, 23 refs.

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更新日期/Last Update: 2018-10-23