Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

How to Use Driving Simulators Properly: Impacts of Human Sensory and Perceptual Capabilities on Visual Fidelity

Fidelity has been a critical concern of researchers throughout the history of driving simulation. Understanding the limits of a driving simulation system is a prerequisite for conducting valid driving simulator studies. This paper proposes a novel and interdisciplinary methodology to ensure validity of studies using driving simulators (primarily for traffic control devices and other object detection tasks) based on the visual limits of human sensory and perceptual capabilities, and the characteristics of raster graphics. This methodology decomposes the perceptual issues of a stimulus into perceptual issues of different visual properties like luminance, hue, or text of the stimulus. By systematically analyzing the mechanism of human vision in driving simulators, the perceptual principle is proposed to ensure perceivable visual details in human-in-the-loop driving simulation systems. Additionally, the graphic principle is proposed to ensure perceivable features of a target object in the virtual driving environment. Both principles quantify the minimum requirements of visual fidelity with two measurements: angular resolution and matrix dimensions. The enriched results from existing pertinent studies are analyzed and organized to yield support of both principles. This research focuses on the minimum requirements for four factors; namely the visual acuity of drivers, the specifications of display systems, the configurations of graphics systems, and the design of virtual scenarios, as well as the relationship among all these factors to assess the visual fidelity in driving simulation systems. Within the realm of human perception, this work can provide criteria for proper design, calibration, and usage of driving simulators.     

Did Chinese cities that implemented driving restrictions see reductions in PM10?

Imposing driving restrictions is becoming increasingly popular as a policy intended to control urban air pollution. Existing studies on this topic offer highly mixed observations, and each study tends to focus on only one city. In this paper, we used 11 Chinese cities with driving restrictions as the treatment group, and compared them to other cities that did not implement the policy. Based on a propensity score matching and difference-in-difference analysis, we found no evidence of a decrease in PM10 concentrations in cities after they implemented driving restrictions. This finding may be attributed to an increase in the number of cars in these cities after implementing driving restrictions, but we also found no evidence of an improvement in air quality for a given number of cars after implementation of the policies.     

Will a driving restriction policy reduce car trips?—The case study of Beijing,China

A driving restriction policy, as one of the control-and-command rationing measures, is a politically acceptable policy tool to address traffic congestion and air pollution in some countries and cities in the world. Beijing is the first city in China to implement this policy. A one-day-a-week driving restriction scheme was expected to take 20% of cars off the road every week day. Using household survey and travel diary data, we analyze the short-term effect of this driving restriction policy on individual travel mode choice. The data also allow us to identify which demographic groups are more likely to break the restriction rule. The estimates reveal that the restriction policy in Beijing does not have significant influence on individuals’ decisions to drive, as compared with the policy’s influence on public transit. The rule-breaking behavior is constant and pervasive. We found that 47.8% of the regulated car owners didn’t follow the restriction rules, and drove “illegally” to their destination places. On average, car owners who traveled during peak hours and/or for work trips, and whose destinations were farther away from the city center or subway stations, were more likely to break the driving restriction rules. Therefore, Beijing is probably in need of more comprehensive and palatable policy instruments (e.g., a combination of congestion tolls, parking fees, fuel taxes, and high-speed transit facilities) to effectively alleviate traffic congestion and air pollution.     

酒后驾驶行为对驾驶安全性影响研究

酒后驾驶是造成机动车道路伤害的危险因素,对道路交通安全的影响非常严重。本文通过一系列适宜性检测试验,比较饮酒前与饮酒后以及随饮酒量的逐步变化酒精对受试者驾驶能力的影响。研究发现,饮酒后受试者心理活动受到影响,反应变差,感知变差,手和脚的动作变迟缓,处置判断错误率上升,并随着饮酒量的逐渐增加,驾驶技能逐渐恶化。     

基于CVT的混联式电动汽车动力切换平稳性研究

针对四轮驱动越野车提出了一种基于金属带式无级自动变速器(CVT)的混联式结构,其动力切换平稳性是这种混联式电动汽车必须解决的关键技术之一。通过发动机、电机、离合器和CVT的协调控制可以使系统在驾驶员发出加速命令时快速响应以及在模式切换时平稳,这将保证驾驶员在车辆切换过程中没有异常感觉。     

电动汽车复合驱动系统

电动汽车的复合驱动系统包括内燃机驱动和电力驱动，它综合了这两种驱动方式的优点。介绍了电动汽车的各种复合驱动结构，分析讨论了这些结构的优缺点，阐述了选择串联还是并联复合驱动结构时应考虑了主要问题，并给了一个单轴复合驱动结构的实例。     

基于支持向量数据描述的驱动桥异响检测

针对驱动桥异响检测缺乏故障样本的问题,提出了异响检测的单值分类法———支持向量数据描述法(SVDD)。这种方法只需要正常运行状态的数据样本,就可以建立单值分类器,区分出正常和异常状态。试验中,提取驱动桥振动信号频谱的二维谱熵作为特征指标,输入到SVDD分类器。结果表明SVDD算法计算效率高,分类效果好,可以满足在线检测的要求。     

驱动桥总成在线检测计算机测控系统研究

本文介绍了驱动桥总成在线检测计算机测控系统及技术实现。在该系统的控制下，实现了基于驱动桥总成的制动性能、速度及阻力矩等性能指标的综合检测，从而使生产过程驱动桥总成质量控制得以实现。该系统也可用于试验研究。     

驾驶循环对车辆能量经济性影响的研究

本文依据国内外具有代表性的不同驾驶循环对一实际的内燃机汽车和一构思的混合动力电动汽车的能量经济性进行了分析。研究了内燃机和电机的运行工况分布，并利用内燃机的万有特性图和电机及其控制系统的等效率曲线以及各驾驶循环的相关特性分析了产不同结果的原因。最后对内燃机汽车和混合动力电动汽车的能量经济性受驾驶循环的影响情况进行了比较和分析。