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Average travel time prediction model in basic expresswaysections based on v/C ratio and truck percentage(PDF)

长安大学学报(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2018年05期
Page:
106-113
Research Field:
交通工程
Publishing date:

Info

Title:
Average travel time prediction model in basic expresswaysections based on v/C ratio and truck percentage
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
Keywords:
traffic engineering travel time prediction model basic expressway section v/C ratio truck percentage traffic efficiency
PACS:
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DOI:
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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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Last Update: 2018-10-23