低碳经济背景下我国新能源汽车产业发展的对策研究

近年来,在经济发展政策不断调整的背景下,"绿色发展"、"可持续发展"战略被深化到了社会各个产业中.并且从整个世界经济发展的角度来看,节能、环保已经成为了时代的主题.在汽车产业发展过程中,由于碳排放量比较多,所以对经济和环境产生了较大压力.为此,在今后工作中,相关工作人员应该充分认识到低碳经济背景所产生的影响.结合时代发...     

Consumer purchase intentions for electric vehicles: Is green more important than price and range?

In view of global warming and climate change, a transition from combustion to electric vehicles (EVs) can help to reduce greenhouse gas emissions and improve air quality. However, high acquisition costs and short driving ranges are considered to be main factors which impede the diffusion of EVs. Since electricity needs to be produced from renewable energy sources for EVs to be a true green alternative, the environmental performance of EVs is also presumed to be an important factor. This paper investigates the role of environmental performance compared to price value and range confidence regarding consumer purchase intentions for EVs. To develop our hypothesis, we interview 40 end-user subjects about their beliefs toward EVs. Then, we perform 167 test drives with a plug-in battery EV and conduct a survey with the participants to test the hypothesis. Results of a structural equation modeling support the hypothesis that the environmental performance of EVs is a stronger predictor of attitude and thus purchase intention than price value and range confidence.     

Dynamic charging-while-driving systems for freight delivery services with electric vehicles: Traffic and energy modelling

This paper presents a research on traffic modelling developed for assessing traffic and energy performance of electric systems installed along roads for dynamic charging-while-driving (CWD) of fully electric vehicles (FEVs).The logic adopted by the developed traffic model is derived from a particular simulation scenario of electric charging: a freight distribution service operated using medium-sized vans. In this case, the CWD service is used to recover the state of charge of the FEV batteries to shortly start with further activities after arrival at the depot.The CWD system is assumed to be implemented in a multilane ring road with several intermediate on-ramp entrances, where the slowest lane is reserved for the dynamic charging of authorized electric vehicles. A specific traffic model is developed and implemented based on a mesoscopic approach, where energy requirements and charging opportunities affect driving and traffic behaviours. Overtaking manoeuvres as well as new entries in the CWD lane of vehicles that need to charge are modelled according to a cooperative driving system, which manages adequate time gaps between consecutive vehicles. Finally, a speed control strategy is simulated at a defined node to create an empty time-space slot in the CWD lane, by delaying the arriving vehicles. This simulated control, implemented to allow maintenance operations for CWD that may require clearing a charging zone for a short time slot, could also be applied to facilitate on-ramp merging manoeuvres.     

Evaluating the effects of automated vehicle technology on the capacity of freeway weaving sections

Weaving sections, where a merge and a diverge are in close proximity, are considered as crucial bottlenecks in the highway network. Lane changes happen frequently in such sections, leading to a reduced capacity and the traffic phenomenon known as capacity drop. This paper studies how the emerging automated vehicle technology can improve the operations and increase the capacity of weaving sections. We propose an efficient yet effective multiclass hybrid model that considers two aspects of this technology in scenarios with various penetration rates: (i) the potential to control the desired lane change decisions of automated vehicles, which is represented in a macroscopic manner as the distribution of lane change positions, and (ii) the lower reaction time associated with automated vehicles that can reduce headways and the required gaps for lane changing maneuvers. The proposed model is successfully calibrated and validated with empirical observations from conventional vehicles at a weaving section near the city of Basel, Switzerland. It is able to replicate traffic dynamics in weaving sections including the capacity drop. This model is then applied in a simulation-based optimization framework that searches for the optimal distribution of the desired lane change positions to maximize the capacity of weaving sections. Simulation results show that by optimizing the distribution of the desired lane change positions, the capacity of the studied weaving section can increase up to 15%. The results also indicate that if the reaction time is considered as well, there is an additional combined effect that can further increase the capacity. Overall, the results show the great potential of the automated vehicle technology for increasing the capacity of weaving sections.     

A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment

This paper develops a novel linear programming formulation for autonomous intersection control (LPAIC) accounting for traffic dynamics within a connected vehicle environment. Firstly, a lane based bi-level optimization model is introduced to propagate traffic flows in the network, accounting for dynamic departure time, dynamic route choice, and autonomous intersection control in the context of system optimum network model. Then the bi-level optimization model is transformed to the linear programming formulation by relaxing the nonlinear constraints with a set of linear inequalities. One special feature of the LPAIC formulation is that the entries of the constraint matrix has only {−1, 0, 1} values. Moreover, it is proved that the constraint matrix is totally unimodular, the optimal solution exists and contains only integer values. It is also shown that the traffic flows from different lanes pass through the conflict points of the intersection safely and there are no holding flows in the solution. Three numerical case studies are conducted to demonstrate the properties and effectiveness of the LPAIC formulation to solve autonomous intersection control.     

机车车辆横向动力学性能仿真——车辆-轨道耦合模型与传统车辆模型的比较

运用经过大量线路实车运行试验验证的车辆－轨道耦合动力学仿真软件TTISIM，对传统车辆动力学和车辆－轨道耦合动力学两种类型模型的横向动力性能进行了比较与分析。结果表明：车辆无论是在直线上运行 是通过曲线轨道和道岔时,采用传统模型计算所得的轮轨横向相互动作用力均较采用耦合模型计算的大；仿真计算车辆蛇行失稳临界速度时，采用前一模型俐到的结果较后者偏高；而两者计算所得的车辆垂向与横向振动差别甚小。     

面向瓶颈多簇运动波消除的拥堵吸收智能驾驶模型

高速公路瓶颈运动波是诱发通行延误与事故风险主要原因.智能网联下精细化感知与精准化控制为消除运动波影响提供了技术环境.在构建一种在线、主动消除广域运动波的拥堵吸收智能驾驶模型的基础上,解析车头间距与运动波传播关联机制,确定运动波完全消除设计实施条件,提出消除单个运动波最佳驾驶策略;面向多簇运动波形成时间[位置[规模等特性...     

城市交通运行状况对机动车碳排放的影响研究

为定量分析不同城市交通运行状况对机动车碳排放的影响,利用高德平台提供的拥堵延时指数(Congestion Delay Index, CDI)数据,在分析我国交通拥堵城市时空分布特征以及CDI特征的基础上,通过构建基于速度的CO2排放因子,利用VISSIM模拟不同交通运行状况时的交通量,实现不同交通运行状况下机动车碳排放的估算。结果显示：交通拥堵城市分布具有空间依赖性和聚集性,在长三角经济区和珠三角经济区形成两个高聚集中心;CDI具有明显的周期性(7 d)波动规律,且受天气和人类活动等的影响较大,疫情打破了此规律;城市交通运行状况(CDI)对机动车CO2排放有较大的影响,当交通处于轻度拥堵时(CDI为1.582),交通高峰期我国城市机动车年排放的CO2总量约为0.77亿 t,是畅通状态下的4.51倍;当交通保持基本畅通时(CDI为1.35),交通高峰期我国城市机动车CO2年排放总量可减少0.29亿 t;当交通达到中度拥堵时(CDI为1.909),交通高峰期我国城市机动车CO2的年排放增加0.22亿 t;当处于交通严重拥堵时(CDI达2.394),交通高峰期我国城市机动车CO2的年排放总量可达1.33亿 t。改善城市交通运行状况,可大幅度降低机动车的CO2排放量。     

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创新性地考虑了多车型车辆路径问题中不同车型具有不同的边际费用和行驶费用的问题,并同时考虑车型与任务的相容性,对带时间窗约束的多车型多费用非满载车辆路径问题,以最小化总费用为目标建立了数学模型。由于该模型的NP-hard性质,基于高费用车型的边际费用和单位行驶费用比低费用车型的相应费用都要高以及低费用车型的边际费用远大于高费用车型的单位行驶费用的思想,对该模型设计了一个启发式算法。     

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以博弈论为工具,分析了存在公务车的情况下,交通拥挤形成的微观机理以及交通拥挤收费的实施效果。分析表明,拥挤收费并不影响公务车的出行,受到影响的只可能是私家车。在存在大量公务车的情况下,拥挤收费的总体效果取决于私家车出行者的时间价值分布和公务车出行者所占的比重。当公务车出行者的时间价值大于或等于私家车出行者的时间价值时,拥挤收费能有效地化解交通拥挤;当公务车出行者的时间价值小于私家车出行者的时间价值时,拥挤收费很可能只是增加出行者的出行成本,而无法起到缓解交通拥挤的作用。一般地说,高时间价值的私家车出行者所占的比例越高,拥挤收费的效果就越差;公务车出行者占总出行人数的比例越高,拥挤收费的效果越差。