Evaluation of the effectiveness of accident information on freeway changeable message signs: A comparison of empirical methodologies

In this paper, we study the effectiveness of accident messages that are displayed on freeway changeable message signs (CMS). Motivated by the lack of empirical studies and the mixed results reported in the limited empirical studies, this paper focuses on the comparison of different aggregate analysis methodologies and their corresponding results, using the same empirical data set. We have two major findings. First, we find that the CMS accident messages do not seem to have any significant immediate effect on driver diversion based on our empirical data. Visible congestion, on the other hand, seems to be an important factor for driver diversion. Second, we show how the conclusion could have been if wrong methodologies were to be adopted. Methods that rely on correlation alone but not the timing of events (what we call correlation method) yield high correlation between CMS accident messages and driver diversion, which is typically and incorrectly interpreted as CMS accident messages being effective.     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.     

港口竞争的市场结构与竞争行为分析

目前，港口竞争研究已成为一个热点问题。为此，本文首先对港口竞争的范围作了界定，在此基础上，剖析了两种不同类型的港口竞争的市场结构，最后对不同市场结构下的港口竞争行为进行了分析。     

螺旋匝道和螺旋桥的小客车行驶速度特征

为明确螺旋匝道和螺旋桥处的驾驶行为模式和汽车运行特征，在涪陵长江一桥、乌江二桥、重庆融侨大道和涪陵金凯环形高架4处地点开展螺旋匝道实车试验，用车载仪器采集自然驾驶状态下的汽车连续行驶轨迹、速度以及周围行驶环境等信息。基于自然驾驶数据，研究螺旋匝道范围内的速度变化模式、幅值特性以及影响因素。研究结果表明：单车道螺旋匝道的速度变化模式多样化，双车道螺旋匝道的行驶速度在整体上维持稳定，匝道范围内的连续升坡和降坡并未导致速度出现趋势性衰减和趋势性升高；螺旋匝道并入主线时，驾驶人在合流鼻之前有明显的、共性的减速行为，这与现行设计标准中的设计假定相反；除涪陵长江一桥之外，其余3处都是下行速度低于上行速度；螺旋匝道设计速度越低，实测速度与设计速度之间的偏离越严重，并且速度幅值离散化，因此不建议使用20 km·h^-1的匝道设计速度；螺旋匝道运行速度与匝道半径成正相关。     

Does habitual car use not lead to more resistance to change of travel mode?

An experiment examined the effects of an intervention (combination of information and a free public transport ticket) in a changed decision context (moving to a new residence) on travel mode choice by car users. If past frequency of car use has resulted in an automatic response to goal-related cues, one should expect resistant to change of travel mode. However, the results failed to show this. Neither past behavior or a direct habit measure predicted future travel behavior. Instead, the intervention influenced attitude, subjective norm, and perceived behavioral control, and consistent with Ajzen's theory of planned behavior, these were the main causes of the change of travel mode.     

交叉口行人过街心理及交通行为分析

行人与机动车的冲突是影响交叉口运行效率的重要因素。研究交叉口行人过街心理及行为的意义,分析行人过街过程及心理特征,总结行人过街等待时间、穿行速度特征、可接受间隙、违章行为及道路交通环境对行人心理和行为的影响,对行人的违章心理进行论述,并提出减少行人违章的措施。     

Deconstructing development density: Quality, quantity and price effects on household non-work travel

Smart growth and transit-oriented development proponents advocate increasing the density of new land development and infill redevelopment. This is partly in order to reduce auto use, by reducing distances between trip origins and destinations, creating a more enjoyable walking environment, slowing down road travel, and increasing the market for transit. But research investigating how development density influences household travel has typically been inadequate to account for this complex set of hypotheses: it has used theoretically unjustified measures, has not accounted for spatial scale very well, and has not investigated potentially important combinations of measures. Using data from a survey of metropolitan households in California, measures of development density corresponding to the main hypotheses about how density affects travel—activity density affecting distance traveled, network load density affecting the speed of auto travel, and built form density affecting the quality of walking—are tested as independent variables in models of auto trip speed and individual non-work travel. Residential network load density is highly negatively correlated with the speed of driving, and is also highly correlated with non-work travel, both singly and in combination with other measures. Activity density and built form density are not as significantly related, on their own. These results suggest that denser development will not influence travel very much unless road level-of-service standards and parking requirements are reduced or eliminated.     

Immigration, residential location, car ownership, and commuting behavior: a multivariate latent class analysis from California

Using latent class cluster analysis, this paper investigates the spatial, social, demographic, and economic determinants of immigrants’ joint distribution among travel time, mode choice, and departure time for work using the 2000 Census long form data. Through a latent tree structure analysis, age, residential location, immigration stage, gender, personal income, and race are found to be the primary determinants in the workplace commute decision-making process. By defining several relatively homogeneous population segments, the likelihood of falling into each segment is found to differ across age groups and geography, with different indicators affecting each group differentially. This analysis complements past studies that used regression models to investigate socio-demographic indicators and their impact on travel behavior in two distinct ways: (a) analysis is done by considering travel time, mode choice, and departure time for work simultaneously, and (b) heterogeneity in behavior is accounted for using methods that identify different groups of behavior and then their determinants. Conclusively the method here is richer than many other methods used to study the ethnically diverse population of California and shows the addition of geographic location and latent segment identification to greatly improve our understanding of specific behaviors. It also provides evidence that immigrants are as diverse as the non-immigrant population and transportation policies need to be defined accordingly.

基于单调关联系统的驾驶行为可靠度计算方法

为合理评估驾驶员驾驶行为的可靠性,提出了驾驶行为可靠度计算方法,将人机系统可靠性理论与驾驶行为链相结合,构建了基于感知、判断、操作元件及模块组的驾驶行为可靠性框图,确定了单项器官元件可靠度测试与计算方法,运用单调关联系统理论给出了功能模块可靠度及驾驶行为系统可靠度的量化模型,计算了模型中各生理、心理元件概率重要度,分析了其对驾驶行为的影响度。计算结果表明:事故组与非事故组间行为可靠性存在明显差异,非事故组的可靠性整体大于事故组,但整体可靠性呈下降趋势,事故组驾驶员整体操作稳定性较差;生理因素对驾驶行为可靠度影响度前期较大后期较小,而心理因素则相反。     

Travel Behavior Analysis of the Females in Beijing

In urban life, compared with the same age group of male contrast, the statistical indicators of female travel behavior show significant differences. According to the sample data of Beijing 2005 travel survey, the paper analyzes the female travel behavior in the travel rate, travel consumption, trip purpose, and travel mode. Furthermore, the paper introduces the concept of the trip chain, to construct a female morning commuter trip chain choice behavior model with noncollection theories and methods, to analyze 10 factors that influence a female individual's choice of a trip chain from the source. Subsequently, model parameters are estimated, to calculate the incidents that can help to quantitatively understand the impact of each factor on a female's choice of the trip chain. The results show that the travel rate of elderly women is far lower than that of elderly men. Female travel proportion in shopping and social activities is obviously higher than that of male travelers, and factors related to the structure of families create important constraints in their average travel time consumption. The main travel mode of the female is walking, which is far more than that of a male. Age, whether they hold licenses, monthly income, and transport ownership are dominant factors for the female's choice of the trip chain.