大伦敦职住空间关系及通勤交通研究

超大城市的职住空间关系和庞大的通勤交通需求是构建高效综合交通系统面临的严峻挑战。以大伦敦地区为例,面对中心区人口增速回归和就业密度攀升,职住空间分布圈层化、走廊化的发展趋势,大伦敦构建了多模式、多层次的综合交通体系来应对日益增长的通勤压力,可为我国超大城市提供经验借鉴。     

深圳不同收入家庭居住地选择特征及影响因素

居住地选择分析是职住空间关系研究的重要内容,有助于深刻理解职住演化的机理。基于深圳2020年居民出行调查数据,采用Moran’s I检验方法对街道尺度不同收入家庭占比的空间相关性进行评估,采用多项Logit模型检验了交通小区尺度城市建成环境对高收入、中低收入家庭居住地选择的影响。结果表明：高收入、中低收入家庭居住地选择在空间上整体呈圈层分布,中收入家庭在全市分布较均衡;商品住房用地与教育用地的高密度建设有利于吸引更多高收入家庭入住,城中村、工业建筑密度较高地区,中低收入家庭选择居住的概率更高;主干路及以上等级道路网密度的增加吸引更多高收入家庭居住;土地利用混合程度提高降低高收入家庭选择概率。     

基于多项Logit模型的游客组合出行方式选择行为研究

交通与旅游融合发展已成为新趋势,单方式出行无法满足旅游出行需求,研究旅游的组合出行方式选择,对扩大旅游公共交通服务、提升旅游交通管理水平十分重要。为剖析个人属性、家庭属性、出行特征对游客组合出行方式选择的影响,以京江浙居民RP调查数据为基础,构建多项logit模型。结果显示,年龄、职业、家庭结构和出行时间等属性对组合出行方式的选择有显著影响,学生、年轻及低收入群体市内游时更倾向于“公共交通为主的方式”,单人及跨市旅行时更偏好“城际铁路为主的方式”,江苏居民相对京浙居民有更高概率选择“停车换乘”。针对不同公共交通旅游出行群体,提出旅游公共交通服务的政策建议,为促进旅游公共交通服务水平的提升奠定理论基础。     

交通信息影响下出行者出行选择行为特征的实验研究

近年来,交通拥堵已成为困扰我国各大城市的难题。随着信息技术的高速发展,不少学者提出构建出行者信息系统(ATIS)来解决城市交通问题。然而ATIS能否切实改善城市交通状况,以及出行者接收ATIS提供的信息后会做出怎样的反应依然是现阶段亟待研究的问题。实验室实验具有良好的可控性,因此本文通过真人对照实验来探究上述问题。实验结果显示,交通信息的反馈对于出行者群体行为并无显著的影响,但对个体策略改变行为的影响较为明显。进一步地,本文对出行者的策略响应模式进行分析,发现交通信息在一定程度上会增加个体选择行为的复杂性。     

新型拥车方式选择行为的影响因素研究

由于电动汽车和汽车共享都与传统拥车方式存在较大差异,同时现有的汽车共享平台多使用电动汽车,故将购买电动汽车或参与汽车共享作为一种新型的拥车方式。采用意向调查的方法,研究上海市年轻群体对这种新型拥车方式选择行为的影响因素,问卷设计的角度分为个人社会经济属性、家庭特征、交通认知和拥车情况。对调查数据进行离散选择分析,建立新型拥车方式的二项Logit离散选择模型。结果表明:30岁以上人群、女性、家中没有小孩需要接送、居住在外环以内、了解牌照拍卖政策、家庭已经有私家车的消费者更倾向于选择新型拥车方式。并据此提出了相应的政策导向措施。     

基于多分类Logistic模型的城市轨道交通接驳方式选择研究

城市轨道交通适用于主干性运输,可达性相对较低,通过与步行、自行车、公交车等其它交通方式的有效接驳,才能充分发挥城市轨道交通系统的运输服务能力。本文对城市轨道交通接驳方式选择进行研究,以轨道交通出行者的性别、年龄、收入、月通勤费用、接驳距离等作为影响因素,以成都市地铁2号线犀浦站为例,对选择结果的影响因素进行定量研究,结果表明模型具有可行性及正确性,为多分类logistic模型用于轨道交通车站接驳方式的选择预测提供了理论支持。     

气象灾害下公共交通乘客的出行方式选择

随着全球气候变暖,近几年气象灾害频发,对以公共交通出行为主的大城市交通系统影响严重。以城市常见的台风、暴雨为研究背景,建立多元Logit模型,对公共交通乘客的出行选择行为进行预测,得出费用、途中时间和换乘次数三个决策变量对出行选择行为有负效应,其中,途中时间是最主要的影响因素,乘客倾向于选择时间和速度有保证性的地铁方式出行。同时为公共交通管理部门在应急预警方案的制定方面,提供了理论支持,具有较强的现实意义。     

出行方式选择:机器学习方法与多项Logit模型比较研究

在交通出行预测中,多项Logit模型（MNL）的应用十分广泛,但是同时也存在很大的缺陷。模型假定各选择枝不可观测的随机效用部分相互独立且服从二重指数分布,但是这在很多情况下都与实际不符。本文采用机器学习方法中的决策树（Decision Tree）和支持向量机（SVM）模型与多项Logit模型进行对比分析,找出对于居民出行方式选择预测最准确的模型。本文采用的数据来源于2016年12月安顺市的居民出行调查数据,通过三个模型对比可得,SVM模型的预测精度最高,其次是决策树模型,MNL模型的预测精度相对较低。     

The relationship between land use and intrazonal trip making behaviors: Evidence and implications

This paper addresses the relationship between land use, destination selection, and travel mode choice. Specifically, it focuses on intrazonal trips, a sub-category of trip making where both trip origin and trip destination are contained in the same geographic unit of analysis, using data from the 1994 Household Activity and Travel Diary Survey conducted by Portland Metro. Using multinomial logit and binary logistic models to measure travel mode choice and decision to internalize trips, the evidence supports the conclusions that (1) intrazonal trips characteristics suggest mode choice for these trips might be influenced by urban form, which in turn affects regional trip distribution; (2) there is a threshold effect in the ability of economic diversity/mixed use to alter travel behavior; and (3) greater emphasis to destinations within the area where an individual’s home is located needs to be given in trip distribution models.     

Comparative analysis of traveler destination choice models by method of sampling alternatives

In a destination choice model, it is important to introduce alternatives that have been adequately aggregated into traffic analysis zone levels based on spatial similarities and feasibility of analysis, because considering every spatial location possible for the traveler as an elemental alternative is intractable in terms of data management and analysis. In this study, we derive strata for alternative sets through simple random sampling and stratified importance sampling based on the concept of Moran’s I. As a result of comparative analysis, we are able to reduce errors by drawing an adequate number of samples for the destination choice model’s choice alternative sets based on measures of spatial similarity.     

An activity pattern – destination land use choice model of low income households of informal settlements – Case study of Delhi

Various transportation studies carried out in India, while estimating the travel demand, do not take into consideration the travel characteristics of different income groups. The conventional transportation travel demand model lacks the ability to address the travel needs of the urban poor. This paper explores the factors influencing the travel destinations of urban poor living in informal settlements and finds that travel times have a significant negative impact on the choice to travel and influences the choice of the destinations. The study also finds that the inhabitants of informal settlements are adversely affected by urban policies that displace them and rehabilitate them far from their employment opportunities and that the travel characteristics of low income households living in informal settlements are significantly different from higher income households.     

The attraction of countryside sites

The distribution of car trips to countryside sites, though primarily dependent upon accessibility, is also a function of the site attraction. This paper describes an attempt to assess attraction in numerical terms drawing upon techniques used by the geographer and the transportation planner. It is based on a behavioural model in which excursion rates and travel times of visitors to countryside sites were obtained by questionnaire surveys in the West Midlands region.

A method is established for determining sequentially the relative attraction of pairs of sites through plotting excursion rate ratios and the respective travel time ratios for common visitor origins; therefrom, for a travel time ratio of unity, the relative excursion rates can be found. Further investigation suggested that site extensiveness contributes to attraction in proportion to the square root of the area. Relative intrinsic attractiveness—essentially land form and mantle—can be determined using a points scoring system. These two components when combined with the accessibility component enables a site distribution factor to be obtained.

The application of distribution factors is demonstrated in relation to an existing attractor system and one origin zone; the effects of the introdction of a new site into this system is postulated; both cases above having real life parallels. Agreement between observed and synthesized excursion rates was within the range ±10 to 20 percent.     

Sampling of alternatives for route choice modeling

This paper presents a new paradigm for choice set generation in the context of route choice model estimation. We assume that the choice sets contain all paths connecting each origin–destination pair. Although this is behaviorally questionable, we make this assumption in order to avoid bias in the econometric model. These sets are in general impossible to generate explicitly. Therefore, we propose an importance sampling approach to generate subsets of paths suitable for model estimation. Using only a subset of alternatives requires the path utilities to be corrected according to the sampling protocol in order to obtain unbiased parameter estimates. We derive such a sampling correction for the proposed algorithm.Estimating models based on samples of alternatives is straightforward for some types of models, in particular the multinomial logit (MNL) model. In order to apply MNL for route choice, the utilities should also be corrected to account for the correlation using, for instance, a path size (PS) formulation. We argue that the PS attribute should be computed based on the full choice set. Again, this is not feasible in general, and we propose a new version of the PS attribute derived from the sampling protocol, called Expanded PS.Numerical results based on synthetic data show that models including a sampling correction are remarkably better than the ones that do not. Moreover, the Expanded PS shows good results and outperforms models with the original PS formulation.