货车司机看过来! 4.5吨以下货车道路运输证已经取消

正自2019年1月1日起,各地交通运输管理部门不再为总质量4.5吨及以下普通货运车辆配发道路运输证;对于总质量4.5吨及以下普通货运车辆从事普通货物运输活动的,各地交通运输管理部门不得对该类车辆、驾驶员以"无证经营"和"未取得相应从业资格证件,驾驶道路客货运输车辆"为由实施行政处罚。2018年12月底,交通运输部发布《交通运输部     

车展群雄荟萃

大金龙:创新技术闪亮登场在本届展会上,大金龙举行了"大金龙博士后科研工作站新成果发布会",一举推出博士后科研工作站全新研发的拥有自主知识产权、以客车驾驶节能降耗和主动安全为主线的创新技术成果,包括节油驾驶提醒系统、夜视成像报警系统、前向防撞报警系统和车道偏离报警系统,并全新搭载智能雨刮系统、360°全景环视系统、侧面防撞报警系统。大金龙通过深入调研、对比试验发现:拥有良好的驾驶习     

贵阳自动驾驶公交车环境感知系统设计及测试研究

基于城市公共交通具有线路固定、需停靠站等特点,本文研究设计了贵阳自动驾驶公交车智能驾驶系统,并对自动驾驶系统的总体结构及各主要关联对象的功能进行了分析。文章重点研究了车辆环境感知系统,对系统主要硬件设备,工控机工作控制流程,以及对车道、行人、车辆、交通信号灯、标志牌及停靠车站的检测方式进行了研究。系统于2018年8月14日开始在贵阳市贵安新区进行测试,结果显示,系统各项目检测成功率高达90%以上,大部分指标检测成功率高达98%,总体满足智能驾驶公交车的预定要求。     

关于分心驾驶行为的综述

分心驾驶行为是造成交通事故的一个重要原因。如今随着导航系统、智能电话等车载系统的普及,诱发驾驶员分心驾驶行为的因素越来越多。本文通过对国内外关于分心驾驶行为的文献研究,整理了常用的调查研究方法,归纳了国内外分心驾驶对驾驶安全影响的结论,最后也总结了关于分心驾驶监测和预警的成果。结果显示,分心驾驶行为是可以检测和预警的,但目前对理论的实际运用还不够成熟,提出了一些个人的观点,分心驾驶的研究还有广阔的前景。     

感知特性类驾驶行为与驾驶适宜性检测单项指标相关性研究

本文以驾驶员在驾驶行车过程中的驾驶行为特性为分析基础,分析了感知特性类驾驶行为。并利用"营运车辆驾驶人适宜性甄别检测系统及系列检测装置"专题项目采集到的驾驶适宜性检测数据和获得的受检驾驶员最近三年来的安全行车记录数据作为相关性研究的基础数据。在将检测数据进行处理后,利用SPSS统计分析软件进行了正态分布检验、安全类驾驶行为与危险类驾驶行为的独立样本检验,然后利用双变量相关性对感知特性类驾驶行为与适宜性检测评价指标进行关联分析,分析结果表明:不同特性类的驾驶行为与适宜性检测指标的相关性有大小之分。     

大金龙客车增配“节油驾驶提醒系统”

一位经验丰富的节油驾驶专家在客车上24小时待命，随时对驾驶员进行贴身指导，提醒其按照最佳节油状态驾驶客车。这并不是不切实际的设想，大金龙通过在车上安装ECO-driving（节油驾驶提醒系统）已经将这一设想变为现实。     

非法营运怎么管?

正非法营运挖守法营运的墙角,也不是一天两天的事了。这在世界各国都或多或少地存在,但在当下的中国已经愈演愈烈。"克隆车"、"黑摩的"、无证巡游车网约车、无证班车、无证包车、无证旅游客运车,六大金刚翩跹起舞,70公里到200公里线路非法营运车辆猖狂无比,每次载客量5到10人,无孔不入,见缝插针,让守法经营者压力倍增,苦闷无比。国务院"商事制度"改革出台之后,网约车各大平台征战之时,很多从事非法营运者自觉机会难得,他们会浑水摸鱼,先期在应当取得许可的领域领取     

驾驶员反应时间研究

对于预警类智能辅助驾驶系统,驾驶员的反应时间是一个重要参数。本文针对不同的驾驶员类型、不同的预警方式,在实车测试平台上进行驾驶员反应时间的测量。通过实验可以得出各种情况下不同的驾驶员反应时间,该研究的成果将对预警类智能辅助驾驶系统中预警方式和预警时间的选取起到积极的作用。     

轨道交通全自动驾驶核心设备系统独立第三方安全评估方案设计

全自动驾驶是城市轨道交通发展的方向。结合南京轨道交通7号线采用全自动驾驶技术的工程建设,介绍和分析了轨道交通核心设备系统的可靠性、可适用性、可维护性、安全性要求。所采用的独立第三方安全评估方案设计,旨在全面提升核心设备系统的产品质量,能够充分满足7号线全自动运行系统对安全性、可靠性的要求。     

雷诺PREMIUM定位长途公路卡车

为顺应提高生产率与增加驾驶舒适性的迫切需求,雷诺推出了Premium长途公路卡车.V-MAC管理系统、高效低耗的"共轨"柴油发动机、巡航控制系统与InfoMax管理系统完美融合,使该系列产品性能超强、驾驶舒适并且运行成本低廉.     

Towards an understanding of adaptive cruise control

Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead. This research describes the results of a detailed microscopic simulation investigation into the potential impacts of ACC on motorway driving. In addition to simulation, real vehicle driving profiles, obtained from instrumented vehicle experiments in three European countries, have been used to compare real following behaviour with that of a simulated ACC equipped vehicle. This new approach has shown that following with an ACC system can provide considerable reductions in the variation of acceleration compared to manual driving. This indicates a potential comfort gain for the driver and environmental benefits. A number of critical situations in which ACC does not perform well have also been identified. The research also highlights the limitations of microscopic simulation in modelling the impacts of ACC because of the lack of understanding of the interaction between the driver and the ACC system relative to the traffic conditions.     

Modeling of individual vehicle safety and fuel consumption under comprehensive external conditions

This research intends to explore external factors affecting driving safety and fuel consumption, and build a risk and fuel consumption prediction model for individual drivers based on natural driving data. Based on 120 taxi drivers’ natural driving data during 4 months, driving behavior data under various conditions of the roadway, traffic, weather, and time of day are extracted. The driver's fuel consumption is directly collected by the on-board diagnostics (OBD) unit, and safety index is calculated based on Data Threshold Violations (DTV) and Phase Plane Analysis with Limits (PPAL) considering speed, longitudinal and lateral acceleration. By using a linear mixed model explaining the fixed effect of the external conditions and the random effect of the driver, the influences of various external factors on fuel consumption and safety are analyzed and discussed. The prediction model lays a foundation for drivers' fuel consumption and risk prediction in different external conditions, which could help improve individual driving behavior for the benefit of both fuel consumption and safety.     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

What Does Happen to Our Driving When We Get Older?

Abstract

The objective of this paper is to uncover the main antecedents associated with driving errors among older drivers in order to establish a framework for analyzing potential skill improvements using other approaches, for example, games. The article also aims at classifying age-related declines in seniors' abilities associated with their driving performance. The research undertakes an analysis of attempts made through the investigation of the literature. We have systematically searched papers and extracted (1) prevalent driving errors among seniors and (2) underlying age-related declines in seniors' abilities associated with their driving performance. We have also identified some characteristics of the research in this area (e.g. the research methods and geographical distribution of the research). Our expert panel mapped the functional declines in seniors' abilities to the driving errors to identify the relationship between these findings. A reliability test resulted in 81% reliability of findings. We have identified eight groups of driving errors, which could be affected by physical, visual, and cognitive declines among seniors. According to the experts' opinions, the underlying relationship of physical, visual, and cognitive declines among seniors and their driving errors were also presented. Our findings show that there is a potential for the use of innovative interventions such as playing video games to create an inexpensive, motivational, and enjoyable method that may provide a transfer effect to specific driving skills. This could help improve seniors' driving performance by improving specific functional abilities associated with driving.     

基于货运车辆预警数据的高速公路危险驾驶热点路段识别

本文以货运车辆车联网数据中的车辆碰撞预警、疲劳预警和超速预警数据为研究对象,针对G4高速公路北京和河北境内道路上的三种预警热点路段进行识别。运用全局空间自相关性分析方法得出三种预警数据在道路空间中不是随机分布,而是集中在某一个或几个路段上;进一步采用局部空间相关性分析方法识别出三种不同预警类型下对应的热点路段。交通管理部门可根据识别出的预警热点路段提出针对性的管控措施,有助于缓解交通事故的发生,提高货运安全水平。     

Development of a driving simulator based eco-driving support system

This research developed an eco-driving feedback system based on a driving simulator to support eco-driving training. This support system could provide both dynamic and static feedback to improve drivers’ eco-driving behavior. In the process of driving, drivers could get voice prompts (e.g., please avoid accelerating rapidly) once non-eco-driving behavior appeared, and also could see the real-time CO₂ emissions curves. After driving, drivers could receive an eco-driving evaluation report including their fuel consumption rank, potential of fuel saving and driving advice corresponding to their driving behavior. In this support system, five items of non-eco-driving behavior (i.e., quick accelerate, rapid decelerate, engine revolutions at a high level, too fast or unstable speed on freeways and idling for a longer time) were defined and could be detected. To validate this support system’s effectiveness in reducing fuel consumption and emissions, 22 participants were recruited and three driving tests were conducted, first without using the support system, then static feedback and then dynamic feedback utilized respectively. A reduction of 5.37% for CO₂ emissions and 5.45% for fuel consumption was obtained. The results indicated that the developed eco-driving support system was an effective training tool to improve drivers’ eco-driving behavior in reducing emissions and fuel consumption.     

汽车发动机排气门辅助制动系统试验分析

文章介绍了排气门辅助制动系统的构造及其工作原理,通过平板式制动试验台试验与整车道路试验,验证了排气门辅助制动系统对汽车运行的安全性、经济性和驾乘舒适性都有着显著的提高。     

Electric vehicles’ energy consumption measurement and estimation

Use of electric vehicles (EVs) has been viewed by many as a way to significantly reduce oil dependence, operate vehicles more efficiently, and reduce carbon emissions. Due to the potential benefits of EVs, the federal and local governments have allocated considerable funding and taken a number of legislative and regulatory steps to promote EV deployment and adoption. With this momentum, it is not difficult to see that in the near future EVs could gain a significant market penetration, particularly in densely populated urban areas with systemic air quality problems. We will soon face one of the biggest challenges: how to improve efficiency for EV transportation system? This research takes the first step in tackling this challenge by addressing a fundamental issue, i.e. how to measure and estimate EVs’ energy consumption. In detail, this paper first presents a system which can collect in-use EV data and vehicle driving data. This system then has been installed in an EV conversion vehicle built in this research as a test vehicle. Approximately 5 months of EV data have been collected and these data have been used to analyze both EV performance and driver behaviors. The analysis shows that the EV is more efficient when driving on in-city routes than driving on freeway routes. Further investigation of this particular EV driver’s route choice behavior indicates that the EV user tries to balance the trade-off between travel time and energy consumption. Although more data are needed in order to generalize this finding, this observation could be important and might bring changes to the traffic assignment for future transportation system with a significant share of EVs. Additionally, this research analyzes the relationships among the EV’s power, the vehicle’s velocity, acceleration, and the roadway grade. Based on the analysis results, this paper further proposes an analytical EV power estimation model. The evaluation results using the test vehicle show that the proposed model can successfully estimate EV’s instantaneous power and trip energy consumption. Future research will focus on applying the proposed EV power estimation model to improve EVs’ energy efficiency.     

Household-level commuting mode choices,car allocation and car ownership level choices of two-worker households: the case of the city of Toronto

The paper presents a comprehensive investigation on household level commuting mode, car allocation and car ownership level choices of two-worker households in the City of Toronto. A joint econometric model and a household travel survey dataset are used for empirical investigations. Empirical models reveal that significant substitution patterns exist between auto driving and all other mode choices in two-worker households. It is revealed that, female commuters do not prefer auto driving, but in case of a one car (and two commuters with driving licenses) household, a female commuter gets more preference for auto driving option than the male commuter. Reverse commuting (commuting in opposite direction of home to central business district) plays a critical role on household level car allocation choices and in defining the stability of commuting behaviour of two-worker households. Two worker households in higher income zones and with longer commuting distances tend to have higher car ownership levels than others. However, higher transit accessibility to jobs reduces household car ownership levels. The study reveals that both increasing two worker households and reverse commuting would increase dependency on private car for commuting.