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Joint Analysis of the Commuting Departure Time and Travel Mode Choice: Role of the Built Environment

机译:通勤出发时间和出行方式选择的联合分析:建筑环境的作用

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摘要

This paper aims to conduct an empirical study to evaluate the influence of built environment features and socioeconomic factors on commuters' simultaneous choice of departure time and travel mode. Using Kunming, China, as the study region, the 2015 Regional Household Travel Survey and 2016 Point of Interest data are used in the analysis. The results show that, in addition to socioeconomic factors, built environment, such as the density of residential building, employment, and service facility are correlated with joint choice behavior. Moreover, there exist differences regarding the influence of built environment and socioeconomic factors on departure time and travel mode choice. The dissimilarity parameters show that commuters prefer to shift travel mode than departure time generally when travel condition alters. In order to examine the policy measures' potential performance, the paper conducts simulation tests based on the Monte Carlo method. The simulation results show that congestion pricing of car travel during peak hours can reduce the number of commuting trips, and reducing travel time of public transit would be a better strategy to attract more passengers during peak hours. Moreover, reasonable land use planning, such as building more bus stops around commuters' home location, would be a long term and fundamental approach to reduce mobile-source emissions and attract more public transit passengers.
机译:本文旨在进行实证研究,以评估建筑环境特征和社会经济因素对通勤者同时选择出发时间和出行方式的影响。以中国昆明为研究区域,进行了2015年地区家庭出行调查和2016年兴趣点数据分析。结果表明,除社会经济因素外,住宅环境的密度(如住宅建筑物的密度,就业和服务设施)还与共同选择行为相关。此外,在建筑环境和社会经济因素对出发时间和出行方式选择的影响方面也存在差异。差异性参数表明,通勤条件发生变化时,通勤者通常比起出发时间更喜欢改变行驶模式。为了检查政策措施的潜在绩效,本文基于蒙特卡洛方法进行了模拟测试。仿真结果表明,高峰时段汽车出行拥堵定价可以减少通勤次数,减少公共交通出行时间将是吸引更多高峰时段乘客的更好策略。此外,合理的土地使用规划,例如在通勤者家附近建立更多的公交车站,将是减少移动源排放并吸引更多公共交通乘客的长期和基本方法。

著录项

  • 来源
    《Journal of Advanced Transportation》 |2018年第6期|4540832.1-4540832.13|共13页
  • 作者单位

    Beihang Univ Sch Transportat Sci & Engn Beijing Key Lab Cooperat Vehicle Infrastruct Syst Beijing 100191 Peoples R China|Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Beijing 100191 Peoples R China;

    Beihang Univ Sch Transportat Sci & Engn Beijing Key Lab Cooperat Vehicle Infrastruct Syst Beijing 100191 Peoples R China;

    Beijing Urban Construct Grp Co Ltd Beijing 100037 Peoples R China;

    Kunming Urban Transport Inst Kunming 650200 Yunnan Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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