Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Vehicle restrictions and CO2 emissions in Beijing – A simple projection using available data

The Beijing Government launched a new policy on restricting vehicle ownership in late 2010 to regulate the faster motorization and the excessive vehicular carbon dioxide (CO₂) emissions. In this paper, we first analyzed this policy and its effect on private passenger vehicle population. The private passenger vehicle population in Beijing from 2011 to 2020 was predicted under three different scenarios: no constraint (NC), current constraint (CC) and tighter constraint (TC). Then the assessment of vehicular emissions reduction benefits was made on the basis of private passenger vehicle population, vehicle kilometers traveled and CO₂ emission factors. It was projected that the CO₂ emissions in 2020 will reach 23.90, 15.55 and 13.23 million tons under NC, CC and TC respectively. The policy is very effective in controlling the faster motorization and reducing CO₂ emissions.     

Controlled mechanical vibration applied to driver’s right heel to sustain alertness: Effects on cardiovascular behavior

Vehicle-related countermeasures to sustain driver’s alertness might improve traffic safety. The purpose of this study was to investigate the effects of somatosensory 20 Hz mechanical vibration, applied to driver’s right heel during prolonged, simulated, monotonous driving, on their cardiovascular hemodynamic behavior. In 12 healthy young male volunteers, during 90-min periods of simulated monotonous driving, we compared cardiovascular variables during application of 20 Hz mechanical vibration with 1.5 Hz as a control and with no vibration. The parameters recorded were indices of key cardiovascular hemodynamic phenomena, i.e., blood pressure as an indicator of stress, cardiac output, and total peripheral-vascular resistance. The principle results were that all conditions increased the mean blood pressure, and elicited a vascular-dominant reaction pattern typically observed in monotonous driving tasks. However, mean blood pressure and total peripheral-vascular resistance during the monotonous task were significantly decreased in those receiving the 20 Hz vibration as compared with 1.5 Hz and with no vibration. The observed differences indicate the cardiovascular system being more relieved from monotonous driving stress with the 20 Hz vibration. The major conclusion is that applying 20 Hz mechanical vibration to the right heel during long-distance driving in non-sleepy drivers could facilitate more physiologically appropriate status for vehicle operation and could be a potential vehicular countermeasure technology.     

翻车机牵车驱动装置优化改造

针对翻车机牵车驱动装置在设计上存在问题,从机械结构和电气控制上进行了分析,并相应地进行了优化改造,使之更合理,消除了故障隐患。     

爆胎汽车整车运动分析及控制

通过轮胎试验得到GT175/60 R14轮胎在正常胎压及零胎压下的力学特性参数,以此为依据,运用CarS im软件对爆胎汽车进行整车动力学仿真,找出汽车偏航原因,分析驾驶员不同操作所引起的整车运动性能变化以及汽车稳定性控制系统对爆胎汽车的影响。仿真结果表明,稳定性控制系统对于减轻爆胎带来的后果具有积极的作用。     

再生制动技术在汽车中的应用

再生制动技术是一种有效的节能方式。传统的汽车制动,是将车辆的动能变为摩擦片的热能浪费了,而再生制动技术的目的就是使这部分能量储存起来再利用,此种技术节约了能源,并降低了废气排量。文章对再生制动技术进行了理论研究,分析了再生制动技术的节能原理;从传动方式和能量存储方式上对再生制动技术汽车的名称作出定义,同时对再生制动汽车的功率流进行了分析。指出再生制动汽车在达到回收制动能量目的的同时,具有很多优点,是当前汽车发展的方向。     

汽车平顺性时域仿真分析

采用虚拟试验场技术进行了汽车行驶平顺性的时域仿真。建立了面向汽车平顺性分析的整车刚弹耦合有限元模型,同时建立了脉冲输入路面模型和随机输入路面模型。采用1/3倍频带分布加速度均方根值方法及总加权方法对试验车辆的平顺性进行了评价。试验结果表明,运用虚拟试验场技术能够真实地反映汽车的行驶平顺性,仿真分析结果可靠。     

汽车噪声控制技术的最新进展与发展趋势

对汽车噪声控制技术领域的最新进展及发展趋势进行综述,包括噪声控制技术在汽车新产品设计中的应用(整车级别的声学品质目标设定、系统和元件级别的声振特性目标设定)、NVH仿真分析的置信度、NVH虚拟环境技术、车辆噪声控制的材料及结构技术等相关主题。     

存在车辆干扰的车道线识别

为避免道路上行驶的其它车辆对车道线识别的干扰,提出了一种结合车辆识别的车道线识别方法。融合雷达数据,车辆识别模块首先在图像中识别出车辆占据的区域;对于每一个车道线识别模块挑出的车道线候选点进行判断,去除处于车辆区域的车道线点;如果有效车道线点数目不足,则利用卡尔曼滤波的跟踪结果,确定符合最小风险函数的车道线位置。经过多种工况下的试验验证,该方法能够稳定地对车道线进行识别,准确地提取车道线参数,并且算法对车辆干扰有良好的抵抗能力。     

汽车驾驶员行为模式及其心理因素对可靠性的影响

综述了汽车驾驶员行为的三种典型模式，详细地剖析了汽车人机系统中驾驶员的行为特征，建立了驾驶员行为模式，并推导出计算驾驶员失误率的公式。应用交通心理学的基本观点，根据驾驶员失误的心理指标体系，结合实际交通事故案例分析，阐明了心理因素对驾驶员可靠性的影响及其程度。