基于排序二叉树的摘挂列车编组钩计划自动编制方法

根据摘挂列车编组调车作业原理,将摘挂列车下落问题抽象为排序问题,提出一种基于排序二叉树的编组钩计划自动编制方法.根据待编列车序列构造排序二叉树;利用排序二叉树的有序性快速搜索出有序车组序列,将其作为下落方案的可选集.考虑邻组、暂合列内收编固定组组别和空闲组别、端组等因素,从可选集中筛选出较优的下落方案.通过定义收编固定组简化列车收编过程,实现列车收编过程的计算机自动编制.通过实例验证,采用该方法降低了选择下落方案的复杂性,减少了列车编组钩计划的调车钩数,而且可根据实际调车线数灵活调整方案.     

基于客流变化的行车组织分析

阐明客流变化时的行车调整策略,即在地铁运营过程中产生突发客流时,行车人员运用抽线、加开列车以及在信号系统中加入设备干预等措施进行相应的行车调整,并针对性地提出数据分析、客流曲线生成软件的开发以及时刻表编制分析等方面的问题和建议。     

Neighborhood services,trip purpose,and tour-based travel

Communities are increasingly looking to land use planning strategies to reduce drive-alone travel. Many planning efforts aim to develop neighborhoods with higher levels of accessibility that will allow residents to shop closer to home and drive fewer miles. To better understand how accessible land use patterns relate to household travel behavior, this paper is divided into three sections. The first section describes the typical range of services available in areas with high neighborhood accessibility. It explains how trip-based travel analysis is limited because it does not consider the linked (chained) nature of most travel. The second section describes a framework that provides a more behavioral understanding of household travel. This framework highlights travel tours, the sequence of trips that begin and end at home, as the basic unit of analysis. The paper offers a typology of travel tours to account for different travel purposes; by doing so, this typology helps understand tours relative to the range of services typically offered in accessible neighborhoods. The final section empirically analyzes relationships between tour type and neighborhood access using detailed travel data from the Central Puget Sound region (Seattle, Washington). Households living in areas with higher levels of neighborhood access are found to complete more tours and make fewer stops per tour. They make more simple tours (out and back) for work and maintenance (personal, appointment, and shopping) trip purposes but there is no difference in the frequency of other types of tours. While they travel shorter distances for maintenance-type errands, a large portion of their maintenance travel is still pursued outside the neighborhood. These findings suggest that while higher levels of neighborhood access influences travel tours, it does not spur households to complete the bulk of their errands close to home.     

Daily activity and travel sequences of students,faculty and staff at a large Canadian university

This paper examines the activity engagement, sequencing and timing of activities for student, faculty and staff commuter groups at the largest university in the Maritime Provinces of Canada. The daily activity patterns of all university community groups are modeled using the classification and regression tree classifier algorithm. The data used for this study are derived from the Environmentally Aware Travel Diary Survey (EnACT) conducted in spring 2016 at Dalhousie University, Nova Scotia. Results show that there are significant differences in activity and travel behavior between university population segments and the general population in the region, and between campus groups. For example, students participate in more recreation activities compared to faculty and staff. They also take more trips to and from campus, and are more flexible in their scheduling of trips. The insights gained from this study will provide helpful information for promoting sustainability across university campuses, and for development of campus-based travel demand management strategies.     

公路城际出行链模式划分及其形成机制

为划分公路城际出行链模式并分析其形成机制,本文考虑城市内部换乘过程,解析了公路旅客城际出行过程.利用昆明市1 757份公路旅客出行调查问卷数据,提取了公路城际出行链结构特征.通过测算出行链结构值,提出了公路城际出行链模式的划分方法,将公路客运城际出行链模式划分为Ⅰ、Ⅱ、Ⅲ类并分别获取了其形成机制.结果表明:昆明市公路城际通道的平均运距为237.95 km,公共交通是公路城际出行过程中城市内部换乘的主要交通方式;昆明市公路城际出行链的3类模式占比为13.9∶6.4∶4.7,整体结构较合理;其中,Ⅱ类出行链模式最能体现均衡、稳定的形成机制.对公路城际出行链的形成机制分析发现,收入因素是促使出行链结构合理化的重要动力;造成出行链结构不合理的重要因素是市内出行延误,而非城际通道出行过程.     

An algorithm for finding reasonable paths in transit networks

In this paper, reasonable paths in transit networks are defined as possible paths that satisfy the acceptable time criterion and transfer‐walk criterion. A recursive algorithm for finding all of the reasonable paths in a transit network that does not involve a rapid increase in program run‐time with network size is presented. Realistic transit networks in Hong Kong and Guangzhou were selected as case studies of the different phases of the development of a trip planning system. Transport planning practitioners and potential users were invited to test the system to evaluate its performance. The results of the prototype evaluation were satisfactory, and the viability of the system as a useful tool for supporting decision‐making has been confirmed by the positive feedback that was obtained from survey questionnaires.     

城市出租车交通分布预测模型

现有交通需求预测方法以居民出行分析为基础,预测得出的出租车交通分布量实质上是载客出租车的交通分布量,因此其预测值比实际值偏小.基于出租车的运行规律,提出了出租车出行概念,将系统中出租车总出行量分解为载客出租车出行量和空驶出租车出行量,并运用Logit概率选择模型,建立了载客出租车出行量与空驶出租车出行量之间的关系,从而得出了总体出租车的交通分布预测方法.该方法既可以模拟城市现状的出租车交通分布状况,也可以对规划年出租车的交通分布进行预测,避免了传统分析方法对空驶出租车交通量的疏漏.     

Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences

Transportation system capacity and performance, urban form and socio-demographics define the influences and constraints conditioning the preferences of urban residents for different transport modes. Changes in characteristics of urban areas are likely to lead to changes in preferences for alternative modes of transport over time; as a consequence, statistical models to forecast mode choice need to be sensitive to both purposeful changes to urban systems as well as exogenous shocks. We make use of the 1996, 2001 and 2006 household surveys conducted in the Greater Toronto and Hamilton Area to study mode preference evolution and model forecasting performance. These repeated cross-sectional household surveys provide an opportunity to investigate aggregate structural changes in commuting mode preferences over time, in a manner sensitive to changes in the urban area. We focus on commuting mode choices because these trips are prime determinants of peak period congestion and peak spreading. We then address how to combine the three cross-sections econometrically in a robust way that allows for use of a single mode choice model across the entire period. Using independent data from 2012, we are able to compare the individual year and combined models in terms of forecasting performance to demonstrate the combined model’s more robust forecasting performance into the future.     

Trip Chain's Activity Type Recognition Based on Support Vector Machine

This paper focuses on support vector machine (SVM) based trip chain's activity type recognition. First, the time-series location information of person trip is processed to obtain the trip chain elements including moving processes and activities, and the activity options are extracted from the geographic information system (GIS) around the activity sites. Second, the activity features are drawn from spatio-temporal factors of trip chain to serve as the input feature vector of classifier. A SVM based one-to-one classifier is established and the method of one-to-one classifier voting is adopted to decide the most likely activity type from the activity options. Finally, the classifiers are trained with simulation data based on the Gaussian radial basis (RBF) kernel function and the multilayer perception (MLP) kernel function respectively, and then examined by cross validation. The result shows that in the one-to-one classifying scheme, the highest and lowest right recognition rate with RBF are 99% and 62%, and the corresponding results with MLP are 97% and 54%, respectively.     

基于出行方式链的城市轨道交通客流分析方法

传统"四阶段"法预测流程无法准确预测与轨道交通接驳的交通方式及换乘客流.借鉴基于活动的交通需求模型中利用出行链来解释人的出行行为的方法,提出了基于出行方式链的轨道交通客流分析方法.使用三层的Nested-Logit模型来模拟出行者选择轨道交通为主要出行方式接驳其他交通方式和预测各种方式的客流,建立了轨道交通出行方式链模...