Congestion and pollution consequences of driving-to-school trips: A case study in Beijing

Parents compete for high-quality education for their children by enrolling them in good schools. However, in a Chinese mega-city like Beijing, three factors jointly lead to the spatial separation between schools and homes: the centralized public goods provision mechanism, the historical dependency in school location, and the constrained supply of housing in downtown. Without an adequate number of school buses, this spatial separation of schools and homes triggers the numerous long-distance driving-to-school trips by private vehicle during workday morning rush hours in Beijing. We use the start and end dates of “school holiday” as exogenous repeated shocks to the aggregate traffic congestion, and employ the two-stage least squares (2SLS) regression approach to examine the congestion and pollution consequences of such driving-to-school trips in Beijing. We find that, all else being equal, workdays during school holidays have a traffic congestion index 20% lower than that of non-school-holiday workdays. Such a sharp reduction in congestion leads to a significant decrease in PM₁₀ concentration. Policymakers should lower such “extra” congestion and environmental costs via optimizing the spatial balance between school supply and demand.     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

Understanding the impacts of mobile phone distraction on driving performance: A systematic review

The use of mobile phones while driving—one of the most common driver distractions—has been a significant research interest during the most recent decade. While there has been a considerable amount research and excellent reviews on how mobile phone distractions influence various aspects of driving performance, the mechanisms by which the interactions with mobile phone affect driver performance is relatively unexamined. As such, the aim of this study is to examine the mechanisms involved with mobile phone distractions such as conversing, texting, and reading and the driving task, and subsequent outcomes. A novel human-machine framework is proposed to isolate the components and various interactions associated with mobile phone distracted driving. The proposed framework specifies the impacts of mobile phone distraction as an inter-related system of outcomes such as speed selection, lane deviations and crashes; human-car controls such as steering control and brake pedal use and human-environment interactions such as visual scanning and navigation. Eleven literature-review/meta-analyses papers and 62 recent research articles from 2005 to 2015 are critically reviewed and synthesised following a systematic classification scheme derived from the human-machine system framework. The analysis shows that while many studies have attempted to measure system outcomes or driving performance, research on how drivers interactively manage in-vehicle secondary tasks and adapt their driving behaviour while distracted is scant. A systematic approach may bolster efforts to examine comprehensively the performance of distracted drivers and their impact over the transportation system by considering all system components and interactions of drivers with mobile phones and vehicles. The proposed human-machine framework not only contributes to the literature on mobile phone distraction and safety, but also assists in identifying the research needs and promising strategies for mitigating mobile phone-related safety issues. Technology based countermeasures that can provide real-time feedback or alerts to drivers based on eye/head movements in conjunction with vehicle dynamics should be an important research direction.     

城市快速路基本路段车辆运行特性调查与分析

快速路系统既承担大城市内部中长距离的机动车交通,又承担大城市与区域内其它城镇联系的对外交通。依托教育部高等学校博士学科点专项科研基金项目《城市快速路系统通行能力计算与服务水平评价方法研究》,对国内七个典型城市的快速路进行了交通调查,从交通量的变化特性、车速运行特性及交通组成特性方面对车辆运行特性进行了分析。     

多轴驱动车辆的扭矩优化分配

实践证明，制约多轴驱动车辆发展的问题之一是驱动扭矩的鸽合理分配技术。文中在假定所有轮胎具有个同滚动半径，同一车轴的左右轮胎爱力状态相同的前提下，以牵引功率最大，对多轴驱动车辆的驱动扭矩做了优化分配。通过分析得出，在一般路面正常行驶时，只有保证分配到各个驱动车轮的扭矩与各自的轴荷相匹配时，汽车才具有最小的功率循环及最高的牵引效率。     

纯氢燃料电池汽车性能的仿真

本文以由纯氢作燃料、采用串联式结构的燃料电池车用研究对象，通过仿真对车辆的部分参数和驾驶循环对车辆的性能影响进行了分析。在所分析的车辆参数中，动力系统效率的提高对车辆能量经济的改善最为有效，其次是车的总质量、空气阻力系数和滚动阻力系数减小的影响。在对原地起步加速特性的影响中，车重的减轻效果最为明显，其次是空气阻力系数和动阻力系数减小的影响。这些结论为燃料电池车动力系统的优化设计提供了依据。     

装甲车辆非稳定工况驱动性能仿真模型

基于发动机和传动系统的动态过程，本文开发了一个装甲车辆非稳定工况的驱动性能仿真模型。对一台装甲车辆的加速过程进行了实例仿真计算，计算结果与实测值符合较好。这个仿真模型可以方便地用于装甲车辆非稳定工况动力性能的研究。     

高速公路陡坡弯道路段安全性评价

结合运行车速理论,分析判定陡坡弯道的汽车行驶安全性,并在设计、管理等方面对存在安全隐患路段提出改进措施。     

Development of a representative urban driving cycle construction methodology for electric vehicles: A case study in Xi’an

This paper develops a systematic and practical construction methodology of a representative urban driving cycle for electric vehicles, taking Xi’an as a case study. The methodology tackles four major tasks: test route selection, vehicle operation data collection, data processing, and driving cycle construction. A qualitative and quantitative comprehensive analysis method is proposed based on a sampling survey and an analytic hierarchy process to design test routes. A hybrid method using a chase car and on-board measurement techniques is employed to collect data. For data processing, the principal component analysis algorithm is used to reduce the dimensions of motion characteristic parameters, and the K-means and support vector machine hybrid algorithm is used to classify the driving segments. The proposed driving cycle construction method is based on the Markov and Monte Carlo simulation method. In this study, relative error, performance value, and speed-acceleration probability distribution are used as decision criteria for selecting the most representative driving cycle. Finally, characteristic parameters, driving range, and energy consumption are compared under different driving cycles.     

基于视频识别技术的无信号交叉口安全预警系统原型开发

基于视频识别技术开发无信号交叉口安全预警系统原型,在Visual Studio 2010开发环境下,借助halcon8.0图像处理算子,应用背景差法识别与跟踪运动车辆,实时采集车速、加速度、距离等微观交通信息,建立无信号交叉口安全通行模型实现动态安全预警功能,利用模型车辆测试系统的预警可靠性,在参数设置合理的条件下取得了87%的预警成功率。