基于潜在类别-Logit模型的共享自动驾驶汽车使用意向

自动驾驶技术和共享经济融合产生的共享自动驾驶汽车(SAV)可为人们提供优质的出行服务.为探究出行者选择SAV的行为特性,对受访者的社会经济属性、历史出行特性、行为态度特征进行调查,并采用正交试验设计出行方式选择意向调查问卷,收集到311份有效数据.为充分考虑个体异质性,利用潜在类别分析探究SAV使用者的潜在类别,并将所...     

常态化疫情防控阶段旅客中长距离城际出行联合选择行为建模

新冠肺炎疫情对旅客中长距离的城际交通出行影响巨大,现有研究侧重疫情暴发初期疫情对城际交通出行的影响,针对常态化疫情防控阶段旅客城际出行选择行为的研究相对较少,因此,本文旨在研究常态化疫情防控阶段旅客中长距离城际出行选择行为。针对民航、高铁、普铁和自驾等方式分别建立包含4种城际出行方式的多指标多因果出行选择模型（MIMIC）,模型中引入感知防疫安全程度、防疫策略、乘车体验与出行习惯4个潜变量,探究潜变量与观测变量的因子载荷并辨识模型参数,求取各潜变量的拟合值;在此基础上建立考虑出行方式特性、旅客社会经济属性与潜变量的多出行方式联合选择行为模型（MIMIC-Logit）,探究常态化疫情防控阶段旅客出行心理对其出行决策的影响;假设出行费用、时间与距离等变量的随机系数服从正态分布,采用抽样1000次的Halton序列对随机系数进行仿真求解,得到随机系数的回归分析结果。以2021年4月—6月到达西安旅客的调查数据为例进行实证研究,结果发现：所提MIMIC-Logit模型的拟合优度与命中率分别为43.621%与83.312%,均高于多项Logit模型与随机系数Logit模型;旅客对不同方式的出行费...     

无人驾驶汽车对中短距离市际出行方式选择行为的影响

研究了无人驾驶汽车对中短距离市际间出行选择行为的影响.基于计划行为理论,通过建立结构方程模型,构建出行者对无人驾驶汽车的感知行为控制、主观规范、行为态度和行为意向心理潜变量.然后将这些心理潜变量纳入到随机系数Logit模型建立混合选择模型.以武汉市为例进行实证研究,结果表明:在效用函数中,车内时间、出入站和候车时间,以...     

山地城市建成环境对居民小汽车拥有影响研究——以贵阳市为例

为分析山地城市建成环境对居民小汽车拥有的影响，探究不同坡度下居民地形感知对小汽车拥有影响的差异，采用贵阳市中心城区不同坡度下的小区居民调研数据，引入3个观测变量来评价居民的地形感知，将结构方程模型（SEM）计算出的潜变量适配值融入Logit模型中，构建包含潜变量和显变量的SEM-Logit模型来研究主客观建成环境与小汽车拥有的关系。结果表明:坡度对小汽车拥有产生积极影响，但不同坡度下的地形感知对小汽车拥有的影响有所不同。在地形条件相对较好的环境中，当小区坡度小于8%，居民对地形感知并不强烈，并认为从小区步行到公共交通站点的距离和时间花费在其承受范围内。因此，地形感知并未对小汽车拥有造成显著影响；在小区坡度为8%~15%时，地形感知对小汽车拥有产生显著负效应。生活在该小区类型的居民，尤其是收入相对偏低的居民，更喜欢选择电动自行车出行，削弱了小汽车拥有量；当小区坡度大于15%时，小区坡度与小汽车拥有量具有正相关性。该小区类型的道路坡度大，居民出行过程中通常会经历频繁的上下坡，造成出行时间花费长，继而形成强烈的地形感知。这严重降低了居民出行选择步行或骑行的可能性，转而提升了小汽车拥有的概率。同时，在SEM-Logit模型中也证明了除地形因素外，家庭年收入、到地铁站最近距离、土地利用混合度、目的地可达性、出行态度对小汽车拥有具有较大影响。      

计划行为理论视角下基于出行行为的公交防疫策略影响效果研究

疫策略对居民公交出行决策行为和出行偏好有着关键作用, 直接关系到公交优先策略的长期实施效果。从居民出行行为的角度, 在计划行为理论的框架下, 基于调查数据研究了居民公交出行影响因素及作用路径, 在此基础上对公共交通防疫策略进行了分析。研究发现了疫情期间公交出行行为影响因素中的1条显著作用路径, 即“风险感知、防疫策略→出行态度→出行意向→出行行为”, 验证了疫情风险感知和各项防疫管控策略对居民出行方式选择行为和出行偏好上有着深刻的长期影响, 需要更加慎重的使用停运等严格策略。通过进一步地观测变量分析, 驾驶员和车内环境消杀等信息对相应潜变量的路径系数最高, 均达到0.9以上, 说明已实施的防疫策略的信息公开对乘客出行态度极其重要, 这在当前是普遍被忽略的。在分析结果的基础上提出了信息公开、分散就坐等具体策略建议。      

Motorcycle fatalities in Malaysia

Malaysia has the highest road fatality risk (per 100,000 population) among the ASEAN countries and more than 50% of the road accident fatalities involve motorcyclists. This study has collected and analysed data from the police, government authorities, and national and international research institutes. Only fatality data are used due to the severe underreporting of severe injuries (up to 600%) and slight injuries (up to 1400%). The analysis reveals that the highest numbers of motorcycle fatalities occur in rural locations (61%), on primary roads (62%) and on straight road sections (66%). The majority are riders (89%), 16 to 20 years old (22.5%), and 90% of the motorcycles are privately owned. Of those involved in fatal accidents, 75% of the motorcyclists wear helmets, and 35% do not have proper licences. The highest number of fatalities by type of collision is ‘angular or side’ (27.5%). Although fatal motorcyclist crashes mostly involve ‘passenger cars’ (28%), motorcyclists are responsible for 50% of the collisions either by crashing singly (25%) or with other motorcyclists (25%). While male motorcyclists predominate (94% of fatalities), female motorcyclists aged 31 to 70, possessing ‘no licence’, not wearing helmets and travelling during the day, account for a higher percentage than male motorcyclists. Malaysia must acquire more motorcycle exposure data and establish an injury recording system and database based on hospital-records. To reduce motorcycle fatalities, it first has to understand why young male motorcyclists are prone to fatal crashes in the evenings and on weekends on rural primary roads, especially on straight road sections.     

Estimation of delay variability at signalized intersections for urban arterial performance evaluation

Urban arterial performance evaluation has been broadly studied, with the major focus on average travel time estimation. However, in view of the stochastic nature of interrupted flow, the ability to capture the characteristics of travel time variability has become a critical step in determining arterial level of service (LOS). This article first presents a stochastic approach that integrates classic cumulative curves and probability theories in order to investigate delay variability at signalized intersections, as a dominant part of the link travel time variability. This serves as a basis for arterial travel time estimation, which can be obtained through a convolution of individual link travel time distributions. The proposed approach is then applied in the estimation of travel time along one arterial in Shanghai, China, with abundant automatic vehicle identification (AVI) data sources. The travel time variability is evaluated thoroughly at 30-min intervals, with promising results achieved in comparison to the field measurements. In addition, the estimated travel time distributions are utilized to illustrate the probability of multiple LOS ranges, namely, reliability LOS. The results provide insights into how we might achieve a more reliable and informative understanding of arterial performance.     

重大疫情对乘客公共交通依赖性的影响

深入探究重大疫情对乘客公共交通使用行为和依赖性的影响,有助于针对性地改善公共交通服务质量和供需平衡情况.结合前景理论与计划行为理论,开展重大疫情时期SP/RP出行调查,从出行行为表现维度选取3个指标并利用k-means算法标定公共交通出行群体,从7个层面筛选公共交通依赖性内外部影响指标,采用结构方程模型构建重大疫情对乘...     

新冠疫情对居民休闲出行影响研究

为了就新冠疫情对疫情结束后居民休闲出行的影响展开调查研究,把握疫情后居民休闲出行偏好的变化,分析休闲出行意愿的影响因素和影响机制,并量化分析各因素的影响,基于计划行为理论和收益-风险分析构建结构方程模型,量化感知风险、感知正效用、出行态度、主观规范、感知行为控制等影响因素与疫情后休闲出行意愿的相互影响机制,并利用单因素...     

Motorcyclists' beliefs of compliance with the Malaysian school zone speed limit (SZSL)

Many road crashes that occur in school zones involve child pedestrians. Research has identified three contributing factors to road crashes, namely child behaviour, driver behaviour, and the environment. This study aims to identify critical beliefs that influence motorcyclist's intention to comply with the Malaysian school zone speed limit (SZSL). 159 Malaysian motorcyclists who have travel experience in school zones during school hours and non-school hours were recruited by using purposive sampling. Participants responded to a survey distributed by enumerators in public places and house-to-house survey conducted in Kedah, Malaysia. Step-by-step correlation and regression analysis were used to identify the motorcyclists' critical beliefs. The results identified that motorcyclists' beliefs of the community expectation for them to comply and that complying with the speed limit in school zones may reduce risk of crashes with school children were the critical beliefs. In addition, the observation of many motorcyclists in the school zone was also identified as critical beliefs influencing motorcyclists' intention to comply with the SZSL. The practical relevance of this study is to combine a public awareness campaign and safety education for the motorcyclists together with an enforcement method to reinforce motorcyclists' compliance with the SZSL. Additionally, to increase the awareness level among motorcyclists, traffic control devices, such as flashing lights and yellow lines could be implemented.     

基于大数据的出行方式分配预测研究

随着城镇化及城市交通机动化的进程加快，在城镇化和机动化的共同作用下，交通拥挤问题已经成为制约城市发展和影响居民生活质量的主要问题之一。居民出行行为研究在交通管理和控制中有着非常重要的作用。结合多元大数据，构建出行方式选择的概率模型，有助于不同小区的出行方式分担率的预测，对缓解城市交通压力、提升运营管理能力有直接作用。本文基于小区出行分配、公共交通和非公共交通以及公交和轨道出行三个层级，分别得出出行分配预测模型，并形成计算机程序。利于实际应用，对识别城市出行特征、缓解城市交通压力提供有效措施。     

Clarifying multiple-mode decision making in conventional psychological models: A consideration of the influential mechanism of car use's characteristics on the behavioral use of public transportation

The existence of the multiple-mode decision making process challenges the existing psychological theories those predict travel behaviors because the theories were mainly to explain the relationship between travelers' perceived attributes of a targeted mode, not to make choices between modes. A review of related literatures showed a lack of focus on the mechanism of one mode influencing other mode in psychological models. The present study investigates how car-related factors affect the establishment of bus use intention in a psychological investigation. It is hypothesized that single car use factors do not directly influence bus use intention, rather than that; they indirectly influence bus use intention through an overall factor of car use. Results from a dataset of 270 samples investigating three types of daily trips in the Japanese context showed support to the mediating effect of the overall car use factor. As such, an arbitrary inclusion of car-related factors to psychological models of public transportation may not be recommended.     

基于联合模型的机场航站楼寻路影响因素

为解决旅客感知对机场航站楼寻路影响缺乏定量描述的问题,使用个人素质能力、感知信息有效性、感知设施布局分散程度这3个潜变量作为旅客在寻路过程中的感知影响变量。结合个人属性、出行特征、机场状况等变量,构建融合旅客感知影响的机场航站楼寻路SEM-Logit联合模型,并运用问卷调查数据进行实证分析。结果表明,感知因素潜变量对航站楼内的寻路过程具有重要影响作用。个人素质能力（0.107）、感知信息有效性（0.379）对寻路便捷程度具有正向影响,感知设施布局分散程度（-0.330）具有负向影响;旅客的年龄、性别也是影响航站楼寻路的关键因素。联合模型比基础回归模型考虑因素更全面、解释能力更强。      

考虑心理潜变量的城市电动自行车用户出行决策行为

为探究电动自行车用户对不同城市电动自行车规范管理政策的行为响应机理,采用问卷调查方法收集用户的社会人口特征、出行特征、心理特征以及在不同政策下的决策,基于心理接受度等潜变量构建了多指标多因素模型,得出了潜变量的拟合值,将潜变量作为解释变量引入到行为决策模型中,构成了混合选择模型来分析社会人口变量、出行特征变量和心理潜变...     

A framework for travel time variability analysis using urban traffic incident data

This study aims to develop a framework to estimate travel time variability caused by traffic incidents using integrated traffic, road geometry, incident, and weather data. We develop a series of robust regression models based on the data from a stretch in California's highway system during a two-year period. The models estimate highway clearance time and percent changes in speed for both downstream and upstream sections of the incident bottleneck. The results indicate that highway shoulder and lane width factor adversely impact downstream highway clearance time. Next, travel time variability is estimated based on the proposed speed change models. The results of the split-sample validation show the effectiveness of the proposed models in estimating the travel time variability. Application of the model is examined using a micro-simulation, which demonstrates that equipping travelers with the estimated travel time variability in case of an incident can improve the total travel time by almost 60%. The contribution of this research is to bring several datasets together, which can be advantageous to Traffic Incident Management.     

Recognising customers' patterns of bus service patronage using a loyalty framework

With the aim of identifying typical characteristics of travellers, traditional segmentation approaches were based on socio-demographic variables. However, the approaches could not reveal the factors motivating individual behaviour. This result led to an emerging interest in psychological research models that are adhered to the decision-making process. Among various related theories, the concept of loyalty was attractive because the major purpose of establishing a loyalty concept is to recognise a customer's pattern towards a given service. However, there were few efforts aimed at determining market segments based on a loyalty framework. In addition, there was no consensus achieved on theoretical loyalty typology due to different empirical findings in different market contexts. This study aims to be the first loyalty-based attempt to provide an operational method of segmenting bus service market. Seeking practical implementation, another focus of this study is to determine typical characteristics of the market segments. Analyses that included cluster techniques were conducted on questionnaire data collected from 333 respondents in Hidaka city, Japan. A cross-classification between relative attitude and service patronage was successfully established, dividing the market into four segments. Segments of loyalty and no-loyalty were observed to be dominant over the remaining market. In contrast, the spurious loyalty segment was small and insignificant. An expansion of the latent loyalty segment was also observed when moving from the intention phase to the actual behaviour phase. Notably, not only demographic factors but also social awareness variables including environmental concern and elderly support were observed to be significant in distinguishing customer segments from one another.     

城市居民使用共享单车意向研究——以合肥为例

为了探究共享单车使用意向的影响因素和因素间的作用关系,基于计划行为理论(TPB)构建了关于态度、主观规范、感知愉悦、灵活便捷和行为意向等潜变量的计划行为理论扩展模型.通过对问卷调查数据的信度和效度的分析,构建了共享单车使用意向的结构方程模型(SEM),得到各影响因素间的关系路径.结果表明,TPB理论可以很好地解释居民使用共享单车的行为意向,在共享单车的使用意向影响因素中,主观规范的影响最为显著,态度居其次,再次是感知愉悦,而灵活便捷对行为意向的影响作用相对较弱.      

Fostering partnerships towards sustainable urban mobility from the national to local level: Matsuyama,Japan and Yogyakarta,Indonesia

This paper analyzes the implementation of Japan's and Indonesia's national frameworks aiming to promote sustainable urban mobility by placing transport policy coordination as pre-requisites under the decentralization regime. It takes two cities, Matsuyama and Yogyakarta, as the case studies. The analytical framework developed here highlights multi-level government coordination, coordination among local stakeholders, and regulator–operator coordination. The analysis is based on policy documents review, field observation, hearing and a questionnaire survey. The study shows some good practices as well as drawbacks of the schemes and produces lessons-learned from Japan's ‘omnibus town scheme’ to improve Indonesia's public transport program and for other cities in developing countries.     

Travel time statistical modeling with the Halphen distribution family

ABSTRACT

This article introduces the Halphen distribution family for modeling travel time distributions and their reliability on single road links. This probability family originally used in hydrology has a set of relevant characteristics. It is composed of three probability distribution functions for which the mathematical properties are described here. The article uses a graphical representation, the δ-Moment Ratio Diagram (δ-MRD). This tool allows characterizing travel time reliability as well as selecting best distribution candidates within the fitting processes, by considering empirical data sets. A systematic methodology is developed to take advantage of both aspects. From maximum log-likelihood estimation, it is shown that Halphen distributions are among the best state-of-the-art solutions for the travel time modeling purpose. This global framework is validated using two empirical data sets: an urban data set gathered in Portland, Oregon (USA), and a periurban data set from Lyon (France). The model calibration is eased through the use of the δ-MRD; this property opens new research directions about the mapping between traffic states and statistical modeling. It comes from all these considerations that the Halphen family is suitable to describe accurately the travel time dynamics on single links. Therefore, it could be part of a decision support system for practitioners interested in travel time variability.     

Psychological perspectives on changing driver attitude and behaviour

From a psychological viewpoint, several behaviour change techniques may be used to change unsate driver behaviour, e.g. informing, persuading rewarding, punishing etc. The motivation underlying the behaviour determines to a large degree how successful these behaviour change strategies may be. In the article, three broad classes of explanation for driver behaviour are distinguished: reasoned or planned behaviour, impulsive or emotional behaviour and habitual behaviour. Reasoned behaviour is under voliitional control of the driven and is determined by intention to commit the behaviour, which is in turn dependent on attitudes and subjective norms. Emotional behaviour may take range of expressive forms, varying from impulsive reactions to unexpected traffic situations to aggressive driving behaviours elicited by perceived norm-violations of other road users. Habitual behaviour occurs mindlessly, without forethought or conscious information-processing. The transfer of objective knowledge, the cornerstone of persuasive road safety campaigns and road safety education, may be useful in itself in changing reasoned driver behaviour, but may be amiss in changing unplanned, emotionally or habitually driven behaviours. For addressing these types of behaviour, other or additional strategies are considered.