The Influences of the Built Environment and Residential Self-Selection on Pedestrian Behavior: Evidence from Austin, TX

Pedestrian travel offers a wide range of benefits to both individuals and society. Planners and public health officials alike have been promoting policies that improve the quality of the built environment for pedestrians: mixed land uses, interconnected street networks, sidewalks and other facilities. Whether such policies will prove effective remains open to debate. Two issues in particular need further attention. First, the impact of the built environment on pedestrian behavior may depend on the purpose of the trip, whether for utilitarian or recreational purposes. Second, the connection between the built environment and pedestrian behavior may be more a matter of residential location choice than of travel choice. This study aims to provide new evidence on both questions. Using 1368 respondents to a 1995 survey conducted in six neighborhoods in Austin, TX, two separate negative binomial models were estimated for the frequencies of strolling trips and pedestrian shopping trips within neighborhoods. We found that although residential self-selection impacts both types of trips, it is the most important factor explaining walking to a destination (i.e. for shopping). After accounting for self-selection, neighborhood characteristics (especially perceptions of these characteristics) impact strolling frequency, while characteristics of local commercial areas are important in facilitating shopping trips.     

组织行为学在城市交通管理中的应用

城市交通管理中的工作特点决定着其管理的手段和方式。各个职能部门如果忽略了城市交通管理中人的因素,在管理中简单的以规章制度和各种法律条款来解决问题,将取不到良好的效果。因此,借鉴当代管理学中组织行为学方法,遵循人的特有行为规律,从而掌握城市交通管理的一些基本原则,来改善城市交通管理中现有状况,达到有效的管理。     

中学生不良健康行为及其相关因素分析

目的　了解青少年多种不良行为现状及其影响因素。方法　对西乡县两所中学高中一、二年级的学生进行问卷调查。结果　①学生吸烟率 2 1 8% ,吸烟的主要原因是“心情不好” ,其影响因素有性别、学校类型、生源地、学习成绩、父母婚姻状况及校外朋友的多少 ;②饮酒率5 2 1 % ,饮酒的主要原因是“庆贺高兴的事情” ,影响饮酒的因素有性别、年龄、父母的管教、学习成绩及校外朋友的多少 ;③ 3 9 9%学生曾有过离家出走的行为或念头 ,主要是因为“家长误解” ;④ 2 6 5 %学生曾有过自杀的念头 ,4 4%有过自杀的行为 ,主要是因为“学习压力太大” ,影响自杀念头的因素有性别和人际关系 ,影响自杀行为的因素有学习成绩和学校类型 ;⑤ 3 5 %的学生报告曾有过性行为 ,主要原因是“一时冲动” ,影响性行为的因素有年龄和校外朋友的多少 ;⑥除吸烟、饮酒与自杀念头无关 ,离家出走的行为或念头与自杀行为无关外 ,其余各行为之间均有显著的相关性。结论　该地区青少年的不良健康行为比较严重 ,应引起有关部门的重视。     

电子执法环境下驾驶行为与事故特征分析

针对我国电子执法环境下驾驶行为特性、交通流运行特性等研究缺乏,无法制定安全保障措施的问题,借助交通调查、资料分析等方法,对有无电子执法时交通违法行为特征、变速行为特征和交通事故特征的差异及原因进行了分析. 结果表明：电子执法有助于减少交通违法行为,但会增加刮撞行人的交通事故并加剧交通事故的严重程度;电子执法环境下,营运车辆交通违法的比重明显上升、低龄驾驶员构成了道路交通违法的主体,信号交叉口绿灯末期存在严重的交通事故隐患;公路电子执法存在无法根治超速行驶的问题,同样存在交通事故隐患. 鉴于此,从执法前的宣传、教育到执法过程中的安全保障设施建设提出了较完善的解决方案,以确保电子执法环境下的行车安全.     

弹性停车激励机制下驾车者竞价行为演化机理研究

在获取通勤驾车者个体活动出行轨迹及停车竞价数据的基础上，构建基于生存分析理论的驾车者竞价行为演化模型，解析不同因素对停车竞价行为的影响机理；应用灵敏度分析方法，研究激励方案及职住区位设施供给对竞价持续时长的作用规律.结果表明：弹性停车激励机制使原本为“耐用品”的停车泊位转变为“消耗品”，可以通过竞价激励方式降低驾车者的小汽车依赖性，提高城市停车泊位利用率；在弹性停车激励机制作用下，驾车者的泊位共享积极性不仅受自身社会经济属性影响，还受职住区位特征及竞价激励方案的影响；随着通勤驾车者停车泊位共享积极性的增强，参与停车竞价的次数越多，竞价行为的持续时间越长.     

Applying the Value-Belief-Norm Theory to Marine Contexts: Implications for Encouraging Pro-Environmental Behavior

Encouraging pro-environmental behavior among protected area visitors and other stakeholders has become a priority for marine resource managers. However, there exists a lack of understanding of the human dimensions of resource management regarding the perceptions and attitudes of stakeholders. Using the value-belief-norm theory of environmentalism (VBN) as a framework, the purposes of this investigation were to: 1) test a model of variables that influence stakeholders' intentions to adopt pro-environmental behavior in two marine protected areas (i.e., the Great Barrier Reef Marine Park and the Florida Keys National Marine Sanctuary); and 2) using the relevant literature and information gleaned from the model, suggest techniques that managers can use to encourage pro-environmental intentions. Acceptable goodness-of-fit indices for both of the structural equation models (one for each protected area) provided empirical support for the usefulness of the VBN framework to guide both research in marine contexts and marine protected area management efforts to encourage stakeholders' intentions to engage in pro-environmental behavior. Specific suggestions include increasing stakeholders. knowledge about impacts via environmental education strategies, increasing their awareness of their impacts and their efficacy in mitigating those impacts (e.g., workshops), and developing interpersonal relationships among managers and stakeholders (e.g., implementation intention and follow-up strategies).     

A study of traveler behavior under traffic information-provided conditions in the Beijing area

ABSTRACT

The quality of traffic information has become one of the most important factors that can affect the distribution of urban and highway traffic flow by changing the travel route, transportation mode, and travel time of travelers and trips. Past research has revealed traveler behavior when traffic information is provided. This paper summarizes the related study achievements from a survey conducted in the Beijing area with a specially designed questionnaire considering traffic conditions and the provision of traffic information services. With the survey data, a Logit model is estimated, and the results indicate that travel time can be considered the most significant factor that affects highway travel mode choice between private vehicles and public transit, whereas trip purpose is the least significant factor for private vehicle usage for both urban and highway travel.     

Modeling the charging and route choice behavior of BEV drivers

Due to the limited cruising range of battery electric vehicle (BEV), BEV drivers show obvious difference in travel behavior from gasoline vehicle (GV) drivers. To analyze BEV drivers’ charging and route choice behaviors, and extract the differences between BEV and GV drivers’ travel behavior, two multinomial logit-based and two nested logit-based models are proposed in this study based on a stated preference survey. The nested structure consists of two levels: the upper level represents the charging decision, and the lower level shows the route choices corresponding to the charging and no-charging situations respectively. The estimated results demonstrate that the nested structure is more appropriate than the multinomial structure. Meanwhile, it is observed that the initial state of charge (SOC) at origin of BEV is the most important factor that affects the decision of charging or not, and the SOC at destination becomes an important impact factor affecting BEV drivers’ route choice behavior. As for the route choice behavior when BEV has charging demand, the charging station attributes such as charging time and charging station’s location have significant influences on BEV drivers’ decision-making process. The results also show that BEV drivers incline to choose the routes with charging station having less charging time, being closer to origin and consistent with travel direction. Finally, based on the proposed models, a series of numerical analysis has been conducted to verify the effect of range anxiety on BEV charging and route choice behavior and to reveal the variation of comfortable initial SOC at origin with travel distance. Meanwhile, the effects of charging time and distance from origin to charging station also have been discussed.     

Modeling of individual vehicle safety and fuel consumption under comprehensive external conditions

This research intends to explore external factors affecting driving safety and fuel consumption, and build a risk and fuel consumption prediction model for individual drivers based on natural driving data. Based on 120 taxi drivers’ natural driving data during 4 months, driving behavior data under various conditions of the roadway, traffic, weather, and time of day are extracted. The driver's fuel consumption is directly collected by the on-board diagnostics (OBD) unit, and safety index is calculated based on Data Threshold Violations (DTV) and Phase Plane Analysis with Limits (PPAL) considering speed, longitudinal and lateral acceleration. By using a linear mixed model explaining the fixed effect of the external conditions and the random effect of the driver, the influences of various external factors on fuel consumption and safety are analyzed and discussed. The prediction model lays a foundation for drivers' fuel consumption and risk prediction in different external conditions, which could help improve individual driving behavior for the benefit of both fuel consumption and safety.