交通信息服务条件下的出行选择分析

首先 ,探讨了出行者的出行心理、行为以及信息之间的相互关系 ,在此基础上 ,简要分析了出行者的出行选择。其次 ,考虑在交通信息服务条件下 ,由于出行者本身以及信息方面的原因 ,出行选择可能出现过激反应、集聚反应等问题。最后 ,针对上述问题 ,提出应该加以重视的或有待进一步研究的几个问题。     

混合动力--未来城市公交的明星动力

本文阐述了目前国内外混合动力总成常用的几种方案,介绍了一种适合康明斯发动机的混合动力方案,展望了该动力总成的开发前景。     

城市公交客车发展趋势

本文从未来十年城市社会经济和文化发展的角度分析了公交客车发展的趋势:即动力设计环保化、形体设计大型化、技术配置多样化、性能选择人本化、信息沟通智能化、外观设计艺术化、操作系统自动化、应急设置可靠化、总成寿命同步缩短化、车身结构轻型化。     

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.     

Introduction: Habitual travel choice

In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.     

Habitual travel behaviour: Evidence from a six-week travel diary

This paper introduces different methods to measure similarity of travel behaviour addressing the question of how repetitious travel behaviour actually is. It compares empirical results of the different methods based on the data from a six-week travel diary. In general, the results show that the day-to-day behaviour is more variable if measured with trip-based methods instead of methods based on time budgets. Furthermore, it is confirmed that the similarity declines if the method captures more of the complexity of the travel pattern. It is also shown that travel behaviour is neither totally repetitious nor totally variable. Even for the whole observation period, it is demonstrated that two days always have some common elements. Additionally, it is found that the different methods yield the same pattern of variability for different types of day. Travel behaviour is clearly more stable on work days. Similar results for all methods are also obtained concerning the question of how long the minimum period of observation should be. All measures show that the period should not be less than two weeks if one aims at measuring variability.     

Time windows in workers' activity patterns: Empirical evidence from the Netherlands

This paper assumes that activities at the home and work location are important determinants of individuals' paths through time and space. Fixed activities at these locations determine to a large extent the duration and timing of time windows – blocks of time available for participation in travel and out-of-home non-work activities. Taking the time spent at home and at the workplace as a starting point, this paper classifies activity patterns on workdays into six groups with distinct home- and work-stay patterns. For this, data are used from the 1998 Netherlands National Travel Survey. The six clusters vary in terms of the duration and timing of time windows and some of the differences can be explained by commute characteristics, types of non-work activities performed, workers' sociodemographic attributes, and their spatiotemporal environment. However, the impact of sociodemographic and spatiotemporal variables on cluster membership is shown to be weak.     

Bus Priority Using pre-signals

The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controlled junctions, including the concept of pre-signals, where traffic signals are installed at or near the end of a with-flow bus lane to provide buses with priority access to the downstream junction. Although a number of pre-signals have now been installed in the U.K., particularly in London, there has been very little published research into their design, operation and optimisation. This paper addresses these points through the development of analytical procedures which allow pre-implementation evaluation of specific categories of pre-signals. The paper initially sets out three categories of pre-signal, which have different operating characteristics, different requirements for signalling and different impacts on capacity and delay. Key issues concerning signalling arrangements for these categories are then discussed, together with a summary of the analytical approach adopted and the assumptions required. Equations are developed to allow appropriate signal timings to be calculated for pre-signalised intersections. Further equations are then developed to enable delays to priority and non-priority traffic, with and without pre-signals, to be estimated with delay being taken here as the key performance criterion. The paper concludes with three application examples illustrating how the equations are applied and the impacts of pre-signals in different situations.The analyses confirm the potential benefits of pre-signals, where these signals apply to non-priority traffic only. Where buses are also subject to a pre-signal, it is shown that disbenefits to buses can often occur, unless bus detectors are used to gain priority signalling.     

公共交通系统营运可靠性研究

优先发展公共交通是大城市解决交通拥堵,实现城市交通可持续发展的一项重要措施,然而,公交营运水平的低下制约着公交的发展。本文借鉴可靠性理论对公共交通营运可靠性进行定义,并对公交营运时间和乘客服务可靠性分别进行了描述,据此建立起公交系统营运可靠性模型,然后采用随机模拟技术(即Monte Carlo模拟)进行求解,通过算例说明模型的可行性,最后通过分析可靠性模型得出大型活动期间改善公交营运的途径。     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.