北京市旅游交通方式选择行为研究

为防止北京市旅游高峰期间景区周边交通混乱以及城市交通路网负荷增加，选取北京市三 处景点进行问卷调查，将游客的年龄、是否有车、月收入、同行人数及同伴类型等数据作为影响游客交通方式选择的因素。与此同时，对所需数据进行有效性检验，进而分析不同游客的出行方 式特性，利用非集计模型对游客的交通方式选择行为进行研究。结果显示：游客的年龄、是否有车、月收入、同行人数以及同伴类型这几类因素对游客的交通方式选择的影响均显著，并得到游 客对私家车、出租车、地铁及公交车这四类交通方式选择的比例，分别为17%, 7%, 54%, 22%。研究表明，北京市旅游交通方式的需求以公共交通为主，尤其是对轨道交通的需求，为此建议进 一步加大北京市旅游公共交通系统建设，提高旅游交通的服务质量。     

基于混合选择模型的汽车共享选择行为研究

为了深入分析出行者的汽车共享选择行为,首先以技术接受模型和计划行为理论为框架,将对汽车共享选择行为具有影响的心理因素整合到传统的离散选择模型之中,形成混合选择模型.然后,基于南京市的实证调查数据,运用混合选择模型对出行者的汽车共享选择行为进行研究.结果表明,出行者对于汽车共享的感知有用性、感知易用性、行为态度、知觉行为控制等心理态度潜变量对其选择行为产生显著的正向影响,混合选择模型比传统不带潜变量MNL模型对实证数据具有更高的拟合度.     

Tradable credits for managing car travel: a review of empirical research and relevant behavioural approaches

Recently, there has been a surge of interest in Tradable Credits (TC) as an alternative measure to manage the growth of personal car use. This paper summarises the results and methodologies of studies that have sought to anticipate the behavioural responses to several proposed TC schemes that target personal travel. In a critical reflection on this work and in an attempt to inspire future research, we argue that future empirical studies on TC behaviours can greatly benefit from insights from the fields of behavioural economics and cognitive psychology. Therefore, in the second part of the paper, we bring together behavioural concepts from these fields that are relevant in a TC decision-making context. Based on observations from current TC studies and the behavioural mechanisms identified in the second part of the paper, we propose promising directions for future research on understanding the impact of TC on personal car travel.     

Driving cycle prediction model based on bus route features

Bus fuel economy is deeply influenced by the driving cycles, which vary for different route conditions. Buses optimized for a standard driving cycle are not necessarily suitable for actual driving conditions, and, therefore, it is critical to predict the driving cycles based on the route conditions. To conveniently predict representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route features, which supports bus optimization. The relations between 27 inter-station characteristics and bus fuel economy were analyzed. According to the analysis, five inter-station route characteristics were abstracted to represent the bus route features, and four inter-station driving characteristics were abstracted to represent the driving cycle features between bus stations. Inter-station driving characteristic equations were established based on the multiple linear regression, reflecting the linear relationships between the five inter-station route characteristics and the four inter-station driving characteristics. Using kinematic segment classification, a basic driving cycle database was established, including 4704 different transmission matrices. Based on the inter-station driving characteristic equations and the basic driving cycle database, the driving cycle prediction model was developed, generating drive cycles by the iterative Markov chain for the assigned bus lines. The model was finally validated by more than 2 years of acquired data. The experimental results show that the predicted driving cycle is consistent with the historical average velocity profile, and the prediction similarity is 78.69%. The proposed model can be an effective way for the driving cycle prediction of bus routes.     

Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.     

Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

上游静止柱体对圆柱体结构尾激振动的影响

文章运用半隐式特征线分裂算子有限元算法对串列布置的静止上游柱体和下游圆柱的尾激振动问题进行了数值模拟研究。数值结果表明:上游柱体结构的形状、尺寸比(d/D)和折减速度(Ur)三个参数对下游圆柱体结构的动力响应、运动轨迹与涡脱落模态有着显著的影响,且与单圆柱工况相比存在明显区别;随着尺寸比的增大,上/下游柱体结构之间的互扰作用会由流致效应逐渐转变为尾流效应,使得频率特性发生变化,并会导致下游圆柱体结构的振动响应增强;当d/D=0.5和1.0时,下游圆柱体结构的运动轨迹主要为“8”字形;当d/D=1.5时,除了“8”字形外,运动轨迹还会呈现双弯刀形、“双8”字形和不规则形状。通过对流体力系数与位移时程曲线及位移PSD曲线特性进行分析,揭示了其相互作用的内在机理。另外,下游圆柱体结构的尾流场特性也会随参数的变化而变化,其涡脱落模态主要为2S、P+S和2P三种。     

基于KENTRACK的铁路沥青混凝土底砟层疲劳特性评价

重复动载疲劳损伤是沥青混凝土底砟层的破坏形式之一。本文建立了沥青混凝土底砟层的三维有限元分析模型,分析其在列车荷载作用下的受力变形特性。采用KENTRACK设计方法分析了沥青混凝土底砟层的疲劳寿命。结果表明:沥青混凝土底砟层等厚度替代基床表层的路基结构形式在列车荷载作用下基床表层的竖向动变形和振动加速度明显减小;沥青混凝土底砟层的层底拉应变在10×10^-6~90×10^-6,处于较低水平;沥青混凝土底砟层具有良好的疲劳耐久性,可用于工程实践。     

基于Q-learning 的定制公交跨区域路径规划研究

考虑城市大客流通勤者跨区域出行需求，结合城市公交线网中乘客出行密集、客流走向规律等特点，提出一种跨区域定制公交的搭乘方案. 通过改进的Q-learning 模型对公交线路进行优化，为城市通勤者提供更加便捷和高效的出行服务. 通过综合路段拥堵状态、乘客需求及居民小区位置，设定了Q-learning 强化学习的奖惩函数，提升定制公交区域路径的直线系数、满载率、通行时间. 结果表明，所提出的改进方法能够降低通勤者跨区域通行的旅行时间，有效提高髙峰时段定制公交线网的通行效率.     

基于行程时间影响的关键路段识别与查找

从路段实际功能出发，提出基于路段与路径行程时间序列的相关性识别关键路段的方法.借鉴蒙特卡洛思想，以真实数据构造10万条随机路径验证该方法的可行性，并识别出对上海市路网行程时间有关键影响的路段集合.以上述集合为参照，利用模糊聚类及迭代累计平方和算法提取路段行程时间序列特征并构造两个新变量，结合基础属性建立二项Logit模型，从而主动查找关键路段.比较该模型与基础模型、随机分类器查找效果表明：基于最大归一化行程时间曲线聚类，其结果对关键路段识别模型的性能有提升效用；行程时间对数差分序列的结构性变点在路网和路段级别均有明显时间聚集特性，虽然其个数与路段关键性无明显关系，但其与常见波动程度指标相关性小，可保留用于描述行程时间波动常发性和聚集性.