Attitude toward physical activity as a determinant of bus use intention: A case study in Asuke,Japan

This study examines the effect of people's attitudes toward physical activity on their bus use intentions in rural areas in Japan. We utilized the theory of planned behavior and designated three variables—attitude toward bus use, subjective norms, and perceived behavioral control—as mediators for the hypothesized effect. Analysis results showed that attitude toward physical activity had a significant effect on bus use intention. For transport policy, this implies that improving attitudes toward physical activity can increase bus use and reduce physical inactivity, partly caused by car dependence. Results from a multiple-group analysis, for the hypothesized model, revealed that this finding is particularly valid for young people, car drivers, and people living within five minutes of the nearest bus stop. Finally, the effect of attitude toward physical activity on bus use intention is higher with the presence of mediators; these mediators help to increase the model's predictability for the variance of bus use intention from 8.6% to 64.4%.     

Multimode trip information detection using personal trajectory data

Handheld global positioning system (GPS) devices can serve as a new tool to collect an individual's trip information with advantages of low cost, accurate data, and intensive spatial coverage. Various machine learning algorithms have been explored to detected trip train information in previous studies; however, few of them focused on the evaluation and comparison of the performance and applicability of different models. Meanwhile, according to previous studies, car and bus mode detection is a thorny issue due to their similar travel characteristics, and algorithms still need to be well explored and improved to solve this problem. In this article, an innovative method is proposed to detect trip information, including trip modes, mode-changing time and location, and other attributes, from personal trajectory data. The method is a two-step process. A machine learning algorith-based module (including artificial neural network, support vector machine, random forests, and Bayesian network) is firstly used to identify walk, bicycle, and motorized trip modes (bus or car); we thoroughly compared the performance of these four algorithms. Then a second module, using critical points on the GPS trajectories, is further developed to distinguish car and bus mode, incorporated with GIS map information. Field test results show that the proposed machine learning models can all be applied for walk, bicycle, and motorized mode detection with high detection rates exceeding 90%; however, the algorithms work relatively poorly for bus and car mode detection, with results mostly below 75%. The proposed two-step method can greatly improve bus and car mode detection accuracy by 14–30%. As a result, the average mode detection rates for all the four modes are above 90%. Compared with mode detection results by using only the machine learning algorithm, the proposed two-step method has much better performance in both accuracy and consistency.     

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.     

智能型手机应用程序对运具选择行为之影响

因应资通信技术发展,智能型手持设备逐渐普遍,应用程序蓬勃发展改变人类传统行为模式甚巨.其中,运输相关之应用程序多样化发展,功能包含地理信息系统的应用、交通信息的提供、车辆派遣的预约、交通票证的订定、观光游程的设计等.依据台北市交通局统计2013年民众透过智能型手机应用程序查询次数,每月已高达6 000万次以上,实有必要针对运输类应用程序所衍生之效果进行探究.论文主要研讨智能型手机应用程序所提供的交通运输信息对用户旅运行为之运具选择影响,透过问卷调查,进行个体运具选择模式之构建,以分析台北市旅运者在受智能型手机应用程序提供的实时交通信息对于运具选择行为转变之影响,期能了解ITS结合智能型手机应用程序的交通信息服务对于提高公共运输便利性之效益.      

基于RMA方法的汽车车身CAN总线优化设计

针对汽车车身控制信息的高实时性和车身CAN系统扩充的高灵活性等特殊要求,介绍用于实时系统分析的速率单调分析(RMA)方法,在原总线利用率、信息最坏响应时间等实时性指标基础上引入总线扩展灵活性因子进行车身CAN总线方案的寻优设计,并以典型汽车车身控制系统为例,对单信号方案和信号组合方案进行实时性和扩展灵活性对比分析,在线试验结果验证了理论分析数据的正确性。     

关于公交票价与私家车出行关系的研究方法

该文针对研究城市公交票价与私家车出行量之间关系的需要,提出了一种理论方法。该方法用多元线性回归模型分析了城镇居民家庭人均可支配收入、私家车出行成本等因素对私家车出行需求的影响,并在此基础上结合交叉弹性理论进一步得到公交票价和私家车出行需求之间的弹性关系。通过该方法可以量化公交票价与私家车出行需求两者之间的关系,为城市采用低价公交来制约私家车出行的政策提供一些理论依据。     

公交专用道设置前后无港湾公交停靠站特性研究

对有无公交专用道的路段上非公交车和公交车以及无港湾停靠站区域的非公交车分别提出车速模型公式,并考虑交叉口间距和车道宽度的影响。其中在无公交专用道的路段上采用美国联邦公路局路阻函数转化成线性模型,定义停靠度指标。根据在南京市和深圳市采集的实测数据回归,标定各模型参数,并通过F检验和t检验。同时研究无港湾停靠站区域的影响范围,从时间和空间上反映影响变化规律,得到一些有价值的结论。     

大型营运客车在高速公路的换道安全性辨识

为了给大型营运客车换道预警系统设计提供参考,采用毫米波雷达、激光雷达、车道线识别传感器、GPS、视频监控系统以及控制器局域网（CAN）总线数据采集仪等设备,基于小型乘用车搭建浮动车采集平台。通过在试验线路上进行1.5×10⁴ km的驾驶试验,获取1 200余次营运客车的真实换道数据。以Jula提出的换道安全性模型为基础,结合营运客车的换道行为特征,通过分析换道进程结束后客车需要与周围车辆保持的安全距离,建立适合于营运客车的3类换道安全性识别模型（客车与自车道前方车辆、目标车道前方车辆、目标车道后方车辆）,并利用真实数据对3类模型进行验证。研究结果表明：客车换道持续时间均值为10.4 s,换道起始时刻与目标车道后方车辆的距离为10.0~40.0 m;所有换道样本中,73.3%的换道过程中客车速度要高于目标车道后方车辆,且超过90%的换道过程是由前方慢车引起;不同的速度区间下,车速和航向角联合变化情况下,驾驶人控制营运客车的横向偏移速度保持稳定,可认为客车驾驶人的心理预期换道进程存在固定经验模式,这与小型车换道的研究结论存在较大差异,传统的TTC预警算法识别率较低,在不同速度区间情况下,所提出的模型对客车与自车道前方车辆、目标车道前方车辆、目标车道后方车辆的换道安全识别评价准确率均超过了90%。     

快速公交客流量影响因素解释结构模型构建与应用

针对当前交通拥堵、能源紧张、尾气污染等一系列问题,为加快快速公共交通的发展、提高公共交通利用率,本文找出了影响快速公交客流的主要因素,利用系统工程学中的ISM方法,构建了快速公交客流系统解释结构模型,通过分析探讨快速公交客流的主要影响因素,进而明确了各因素间的清晰结构,得到影响快速公交客流量的5级递阶结构;最后找出影响快速公交客流因素的各影响因素.通过影响因素,建立了多元回归模型,从影响程度、影响方向、影响时期分别归类分析.通过分析各层级因素对快速公交客流量的影响,可引导更多居民选择快速公交出行,对缓解交通压力提供了一定方法指导和决策支持.并通过合理分析为快速公交运输服务提出了建议.     

汽车PEPS系统诊断测试的应用与研究

随着汽车技术的不断提高,汽车PEPS系统也对其诊断测试结果的速度、准确性、连续性提出了更高的要求,利用Vector公司开发的CANoe总线仿真软件,对各种车身电子模块进行模拟,建立具有改进AES算法认证加密的汽车PEPS系统的测试仿真环境。实际测试结果表明,该系统不仅可以在虚拟节点下进行模拟仿真测试,也可以在真实节点下进行实时测试,灵活有效地反映出汽车PEPS系统中各种电子模块的总线通信情况,同时保证了故障诊断测试连续性和有效性。     

公交车驾驶人组织认同感和工作倦怠对不良驾驶行为的影响

公共交通是城市道路交通运输系统中的重要组成部分，公交车驾驶人存在的不良驾驶行为已经成为影响交通安全的最大制约因素之一，由其引发的道路交通事故给个人和社会都造成了严重损失，探索更为安全的公共交通环境显得极为重要。以公交车驾驶人为对象，探究影响公交车驾驶人驾驶行为特征的个人心理因素和组织环境因素，及其对不良驾驶行为的内在影响机制。选用工作倦怠量表（MBI-GS）、组织认同感问卷（OIQ）及驾驶行为问卷（DBQ）对844名城市公交车驾驶人展开问卷调查研究，并使用回归分析和中介检验来探究工作倦怠和组织认同感对驾驶行为的影响机制。结果表明：①32.8%的公交车驾驶人存在不良驾驶行为，错误驾驶行为显著高于违法驾驶行为。其中，在违法维度中，侵略性违法显著高于普通违法。②公交车驾驶人存在较高的组织认同感，组织认同感对不良驾驶行为具有显著的负向预测作用，对工作倦怠程度具有显著的负向预测作用；工作倦怠程度对不良驾驶行为具有显著的正向预测作用。③公交车驾驶人的工作倦怠水平在组织认同感对不良驾驶行为的影响中起到部分中介作用。该结果厘清了公交车驾驶人的工作倦怠和组织认同感对不良驾驶行为的影响机制，为进一步探究不良驾驶行为的心理干预方法提供了思路，从而达到改善城市道路公共交通安全环境的目标。     

基于MOST总线的车载网络系统分析

MOST总线在车载音频、视频等系统的控制中越来越多地应用。但在使用中,由于缺乏该系统的知识和技术,从而影响了系统功能的发挥和使用性能。通过对MOST总线的结构、工作原理的分析表明,MOST总线不仅传送速率快,而且还具有衰减少、重量轻、抗电磁波干扰能力强等优点;同时本文也为MOST总线系统的正确使用提供了理论参考。     

探究客车侧围结构接头焊缝间距的疲劳分析

客车在使用过程中,运行的安全性是人们最为关注的内容,同时也是保证交通运输的重要因素。而客车骨架的接头焊缝,对客车的使用质量具有重要影响。文章通过对客车侧围结构接头局部模型进行分析,提供了多种焊缝间距的疲劳性能对比结果,对焊缝间距和疲劳之间的关系进行了初步的分析判断。     

居民出行方式选择非集计模型的建立

基于非集计离散选择模型的基本理论与建模方法,结合2003年北京居民出行调查数据,对影响居民出行方式选择的因素进行了分析,选择包括公交车、出租车、私人小汽车等在内的5种日常生活中较为常用的交通方式作为居民出行的方式选择肢,确定了影响居民出行方式选择的特性变量及相应的取值方法,建立了交通方式选择MNL模型。应用Matlab优化工具箱中的无约束最优化函数对所建的MNL模型的参数进行了标定,并通过命中率的计算验证了模型的有效性。结果表明,非集计建模方法能够较全面的考虑居民出行选择的各方面影响因素,尤其是将出行者的个人特性影响因素引入模型,提高了模型的预测精度和实用性。     

Mixité sociale et choix modal : importance des dimensions symboliques dans l’attrait des transports collectives

Our understanding of transport mode choice is largely based upon functional attributes, such as travel time, cost or accessibility. It is important, however, to also look at symbolic and affective attributes. Indeed, one of the main differences between mass transit and private car use is strongly symbolic: public transport compels users to confront social diversity. Given a hypothetical choice between those modes, 200 residents of the Parisian region were asked five times to evaluate (measuring usage intention on a six point scale: ?3 meaning never and +3 meaning always, with no neutral point) the attractiveness of bus versus car-based transport, according to relative travel time and bus users’ population type. The results show that the symbolic dimension (the social mix) strongly contributes to the desirability of a transport mode, as does the functional dimension (travel time).     

Starting sliding mode variable structure that coordinates the control and real-time optimization of dry dual clutch transmissions

This paper researches the coordination of control between an engine and clutch at the system level to adequately reflect a driver’s intention and improve the starting performance of a vehicle equipped with a dry dual clutch transmission (DCT). Four-degree-of-freedom (DOF) starting dynamic equations are established for a dry DCT with a single intermediate shaft, and a two-DOF model of the sliding friction process and a single-DOF in-gear model of stable operation are obtained after simplifying these equations. Taking advantage of predictive control and a genetic algorithm, target tracing curves of the engine’s speed and the vehicle’s velocity are optimally specified online, and the starting sliding mode variable structure (SMVS) coordinating control strategy is designed to track these curves. The starting performance of a prototype car equipped with a dry DCT is simulated under different starting cases on the MATLAB/Simulink software platform. The simulation results show that the designed SMVS coordinating controller not only embodies driver intention and effectively improves the dry DCT car’s starting performance but is also highly robust when subjected to variations in the vehicle parameters.     

基于巢式Logit模型的航空港集疏运方式选择研究

为研究航空旅客出行方式选择行为,在航空港集疏运系统需求描述的基础上,介绍并运用巢式Logit模型原理,以广州白云国际机场为实例,建立适用于白云机场集疏运系统的方式选择模型(NL模型),分析确定各相关影响因素项的影响机理,运用最大似然估计法对虚拟选择枝的共性和相异部分的参数进行修正和标定,从而获取各种集疏运方式的选择概率.结合调查选取的20份样本数据,运用模型编程计算得出私人小汽车、出租车、机场巴士、城际巴士和城市轨道共5种集疏运方式的方式选择概率分布结果,结果显示私人小汽车和出租车二者占比大于45%,机场巴士和城际巴士占比约40%,城市轨道仅占比15%.因此,为大力发展城市的公共交通,需要对白云机场提出具有参考性集疏运系统改进方案,为今后航空港集疏运系统的发展和航空旅客交通方式选择行为研究提供一定的借鉴.      

快速公交运行特性的关键影响因素分析

为研究快速公交系统运行特征与其制约因素之间的内在关系和潜在规律,选取包含有多段不同专用道形式的济南市BRT-3运行线路为研究对象。综合选取了可全面描述BRT 运行特性的车辆平均行驶速度、平均行程速度、平均运营速度以及停靠站平均延误和交叉口平均延误5个基本参数,以及8个凸显运行特征的组合式参数作为评价指标;基于数理统计方法和多元分析理论,综合运用多元统计学中的因子分析法,分析影响快速公交运行特性的关键因素,挖掘不同运行特征与影响因素(或因子)间潜在的关系,探索改善快速公交运行特性的方法与途径。综合分析表明:影响快速公交系统运行的关键影响因素是交叉口影响因子、站台停靠影响因子和车路综合影响因子,针对定量分析的结果提出了改进与完善的意见和建议。      

西安市私家车合乘现状调查与分析——以西安市雁塔区为例

针对西安市私家车合乘的现状进行调查.采用非等比例分层抽样法选取西安市雁塔区内车主及乘客各1 000名作为研究对象进行问卷调查,研究西安市私家车合乘的现状及其影响因素.调查结果表明,目前西安市参与私家车合乘的乘客比例仅占2.7%,比例较低,但双方有合作意愿及合作基本条件.通过对调查结果的分析与讨论得出影响私家车合乘的主要因素有:人身安全、额外耗时、经济条件、年龄、性别等.给出几点促进私家车合乘的建议:确保合乘双方的安全、加大对合乘车辆的扶持力度、对通勤合乘进行有力引导、出租车停靠点同时作为合乘候车点及合理利用公交专用道等.      

基于强化敏感性理论的电动自行车风险骑行行为影响因素

从交通管理的奖惩机制角度,探究电动自行车骑行人的奖惩反应性对其风险骑行行为的影响机理.采用改进强化敏感性理论构建风险骑行行为的心理认知模型.在改进强化敏感性理论框架下,引入风险感知和风险骑行意向,同时考虑性别、年龄和骑行次数的影响,采用结构方程模型评估影响风险骑行行为的主要心理因素.通过问卷调查,共获取402个有效样本...