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.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。     

铁矿尾矿砂在公路基层中的应用研究

对铁尾矿砂及尾矿砂加入石灰水泥后的物理力学性能进行了试验研究,并与石灰土进行对比。结果表明：铁尾矿砂掺加石灰、水泥后,其强度随着龄期而增长,具有半刚性材料的特性,用石灰、水泥稳定尾矿砂作为路面基层材料具有很好的路用性能,同时用石灰和水泥稳定的效果更佳。     

城市轨道交通线网规划可实施性探讨

在对城市轨道交通线网规划概述的基础上,研究了其可实施性的一些制约因素,并以武汉和昆明的线网规划为例,分析了线网规划可实施性的重要性,提出了树立绿色综合交通规划和大轨道交通网络系统的理念、加强现场踏勘和收集与分析基础资料、建立城市建设资料以及规划成果集中管理和共享机制的结论和建议。     

武汉市过长江交通流量特征分析

武汉市过长江交通是武汉市最主要的交通流向之一。根据流量观测数据分析长江交通流量特征,表明武汉市区过长江交通饱和,交通需求总量大,出行目的种类多。过长江交通没有明显、固定的高峰日和高峰小时,除通勤交通外。还有公务等大量非通勤交通。其中武昌与汉口之间交通是主流向,需要适当新增通道缓解过江难问题。     

基于神经网络的道路通行能力与交通需求匹配度判别研究

交通的供需是否匹配关系到城市和枢纽的发展前景。文中在探讨道路通行能力与需求匹配特性的基础上,用BP神经网络理论建立一种交通匹配预测模型。该模型发挥神经网络的优势,对数据并行处理和分布存储,通过训练、学习产生一个非线性映射,自适应地对数据进行预测。通过相关数据实验证明,该神经网络模型有较高的精度,并有较好的适用性。     

一条专用车道双向运营BRT/轻轨的可行性

为有效满足BRT或轻轨系统的运行需求,提出在带有固定左转车道的繁忙通勤走廊中央设置一条BRT或轻轨专用车道用于双向运营的概念。由此产生了车辆相交问题,其相交空间设置于由左转车道产生的未利用或未被充分利用的道路中央隔离带。提供了公交车站和相交空间的概念设计可选方案和几何布局示意图,并考虑运行速度、发车间隔、相邻相交空间的距离及相交空间数量等条件,分析系统性能。为确保具有实用性,研究了系统在现有交通走廊上的可实施性。由于该系统具有利于TOD发展的潜力,也可作为未来发展两条专用车道系统的中间步骤。