机动车交强险与三者险的比较分析

机动车交通事故责任强制保险和第三者责任险是关于机动车的两个重要险种,两者之间在诸多方面存在着差别,商业性三者险在实践中起着补充"交强险"的作用。文章对两个险种进行了全面的比较分析,以利于提高认识,在保险实践中更好地发挥它们的作用。     

基于ARM和旋转滤波的异步电机故障检测方法的研究

提出了一种基于ARM和Park矢量旋转滤波的异步电机故障检测方法。该方法结合Park矢量旋转滤波和异步电机定转子故障特征,对定子电流信号进行分析,可有效地检测异步电机的故障。并通过实验证明,该检测方法正确可行。     

促进新能源汽车发展的财税政策研究——以上市汽车企业为例

面对环境与能源对汽车产业发展的双重约束,新能源汽车发展己成为当前和今后较长时期内政府、企业、消费者及其他组织机构重点关注的难点与热点问题.基于汽车上市公司相关财务数据,通过对企业税负、政府补贴程度和企业研发费用及其对汽车上市企业净利润的影响分析,不难发现未来时期中国在科学合理引导和激励企业发展新能源汽车的过程中,财税政策干预领域的税收制度设计与政府补贴至关重要.     

Analysis of the effect of charging infrastructure design on electric taxi driving profiles: A case study approach on the example of Singapore

Replacing conventional vehicle taxis with electric vehicles would be an efficient measure to reduce greenhouse gas emissions. Due to the limited range and long charging times of current battery electric vehicles, it is of utmost importance to provide sufficient charging facilities. This article analyses the impact of the placement and charging power of charging stations on potential mileage and revenue of electric taxis on the example of Singapore. Therefore, we developed an agent-based electric taxi simulation model to investigate electric taxis’ driving profiles with respect to different vehicle types and charging infrastructure designs. This model is also capable of simulating conventional taxi driving profiles. The validation of these simulation results with real taxi data showed that the model is reproducing taxi driving profiles with high accuracy in great detail. We found out that electric taxis could reach the same mileage and revenue as conventional taxis if charging with a power of 160?kW is possible. Furthermore, we discovered that waiting times for available charging stations have a stronger effect on revenue than the length of detours to reach charging stations. Based on these findings, we concluded that it is more important to reduce waiting times by placing sufficient numbers of charging stations at each location before expanding the charging network by installing small numbers of charging stations at many locations.     

Estimating emissions based on the integration of microscopic traffic simulation and vehicle dynamics model

This study proposes an integrated simulation approach, which consists of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section, including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

Strategic Purity and Efficiency in the Motor Carrier Industry: A Multiyear Panel Investigation

Two questions facing motor carrier managers are (1) whether carriers should specialize in providing full truckload (TL) or less‐than‐truckload (LTL) services vis‐à‐vis offering mix of both and (2) whether this decision is contingent on carrier size. Yet, the literature provides little guidance because research to date has offered contradictory theoretical predictions and inconsistent empirical findings. Drawing on the theory of strategic purity and information processing theory, we explain why service specialization is likely to increase carriers' technical efficiency and why size will have a more pronounced effect on technical efficiency for carriers specializing in LTL services versus TL services. To test our theory, we assemble a panel data set from archival government sources regarding general freight motor carriers' provision of LTL and TL services. We measure carriers' technical efficiency using data envelopment analysis and test our hypotheses by fitting a series of panel data mixed‐effects models. Our results indicate that carriers are most technically efficient when they specialize in one service type. We also find that size positively affects technical efficiency but only for carriers specializing in LTL services; no returns to scale with regard to technical efficiency exist for carriers specializing in TL services.     

A mixed behaviour equilibrium model with mode choice and its application to the endogenous demand of automated vehicles

This study develops a mixed behavioural equilibrium model with explicit consideration of mode choice (MBE-MC) in a transportation system where fully automated vehicles (AV) coexist with conventional human-driven vehicles (HV). For the mode choice, travellers select among three options, following a logit modal split: driving their private HV, or taking an AV mobility service provided by either a firm or the government. For the route choice, the HV drivers follow the random utility maximisation principle while central agents route the AV passengers following the Cournot Nash (firm agent) or Social Optimal (government agent) principles. We consider two types of travel costs (i.e. travel time and monetary travel cost) to characterise the new features (e.g. expanded link capacity and reduced value of time) of the mixed AV–HV transportation system. We model the MBE-MC problem in a combined mode–route choice framework and formulate it as a route-based variational inequality (VI) problem. We show the equivalence between the VI formulation and the MBE-MC problem, and the existence of a solution to the MBE-MC problem. Then, we modify a partial linearisation algorithm for solving the proposed model. Numerical results validate the equilibrium conditions and show the efficacy of the new model in capturing the features of the mixed AV–HV transportation system. The impact patterns of different parameters on (1) the network performance in terms of AV share and system cost and (2) on the solution efficiency are analysed.     

A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior

Developments in battery electric vehicles (BEVs) have received more and more attentions in the last decades due to alleviating carbon emissions and energy crisis. Consequently, how to rank alternative BEVs to assist consumers make better purchasing decisions is a worthy research study. However, there are still some defects in the existing studies for ranking of BEVs: 1) the evaluation index system of BEVs is not comprehensive; 2) the determination of criteria weights cannot be well applied to the actual purchase scenarios; and 3) the psychological behavior of consumers is ignored. To address those shortcomings, this paper proposes a decision support model to assist with consumers to buy BEVs. First, a systematic evaluation criteria system of BEVs including quantitative and qualitative indicators from parameter configurations and online reviews is constructed. Then, a weight algorithm considering consumer learning is proposed to determine the criteria weights. Furthermore, a decision support process considering consumers' regret avoidance behavior is proposed. Finally, an actual BEV purchase case is given to illustrate the practicability of the decision support model. This can be seen in case studies the proposed support model can be well applied to consumers with different regret avoidance behaviours.     

基于多交互方式的物流车辆监控系统设计研究

文章介绍了一种基于多交互方式的物流车辆监控系统的设计和开发,系统以GPs、GIS、GPRS、CSM等技术为基础。采用了三层B／S和C／S混合的系统体系架构,实现了短信、Web、WAP、普通桌面等多种方式的客户端对车辆进行的监控、跟踪、调度、位置查询、空间分析等功能。与以往交互形式单一的监控系统相比,系统具有更好的交互性、对环境的适应性以及系统扩展的灵活性。