不同动力电池新能源货运配送车辆节能减排绩效评价研究

为研究新能源货运车辆装配不同动力电池对节能减排的影响,选取某款新能源货运配送车辆为研究对象,利用GaBi软件建立了3种常用动力电池的整车生命周期评价模型,从原材料获取、生产制造、装配、运行使用、报废回收5个阶段进行节能减排差异分析,并对全球变暖潜值 （Global Warming Potential,GWP） 等环境影响类型进行归一化处理和量化计算处理。结果表明,分别装配3种电池整车的化石能源消耗以煤炭为主、环境排放以CO2为主;纯电动汽车的能源消耗、污染物排放集中在运行使用阶段;综合比较,装配了三元锂电池的整车,其全生命周期节能减排效果最佳,装配了锰酸锂电池的整车则表现最差。加大清洁能源的使用力度、减少用于电力生产的化石能源消耗、提高回收率等措施,可以显著减少污染物排放。     

人工智能在车辆自动驾驶中的应用

提出一种新的基于人工智能的感知 计划 动作agent结构实现智能车辆自动驾驶的方案。首先通过描述该结构的原理说明该结构可以解决自动驾驶中存在的一些问题,接着通过建立自动驾驶知识库阐述如何具体实现自动驾驶,最后通过仿真实验验证该方法能够为智能车辆实现自动或辅助驾驶提供一种非常有效的机制。     

运用经济杠杆长效治理超载超限运输

分析了经济利益贯穿的货主—运输业户—车辆生产、改装厂家的超载超限运输链条的成因、现状和危害;提出了要从以核定载质量为依据转而以货车实际总重和轴载限额为依据对货车实施计重收费的思路,通过区别对待,体现公平,分步推进,累积治理,实现运用经济杠杆,达到长效治理超载超限运输的目的;阐述了江苏、河南、青海等省份实行计重收费所产生的积极效果以及他们推广的安排;提出在计重收费方法以及低速动态轴载称重设备精度、可靠度和价格方面还需要进一步探讨。     

治理公路超载超限运输的长效机制和对策研究

为建立治理超载超限运输的长效机制,首先建立了运输企业收入的计量模型,分析了企业利润与运输价格、运输成本、超载罚款等变量之间的互动关系及企业获得最大利润的条件。在此基础上,针对中国道路货运市场结构的特点,从理性经济人的角度,对运输企业在“惩罚博弈”下可能的行为选择进行了研究;其次结合美国治理超载超限运输的经验,分析了不同执法强度和执法密度组合的执法策略及其适用条件、执法效果等,对中国治理超载超限运输提出了解决方案和具体的政策建议,对中国治理超载超限运输具有指导意义。     

Predicting queue variability to enable analysis of overload risk

ABSTRACT

Predicting the risk of traffic demands and delays exceeding critical limits at road junctions, airports, hospitals, etc., requires knowing how both mean and variance of queue size vary over time. Microscopic simulation can explore variability but is computationally demanding and gives only sample results. A computationally efficient approximation to the mean is used in many modelling tools, but only empirical extensions for variance in particular situations have been available. The paper derives theoretical formulae for time-dependent and equilibrium variance, believed to be novel and to apply generally to queues covered by the Pollaczek–Khinchin mean formula, and offering possible structural insights. These are applied in an extended approximation giving mutually consistent mean and variance estimates with improved accuracy. Tests on oversaturated peak demand cases are compared with Markov probabilistic simulation, demonstrating accuracy (R^2?>?0.99) for typical random, priority-like (M/M/1) and traffic-signal-like (M/D/1) queues. Implications for risk analysis, planning and policy are considered.     

Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.     

电动汽车充电桩安全管理研究

随着国家对环境保护和能源节约的重视以及新能源政策的实施,电动汽车行业迎来了快速发展。充电基础设施的建设,是加快电动汽车推广的重要需要。电动汽车充电基础设施建设和运营业务发展的机会也极大,随之而来的安全管理工作要求也越来越高。本文依据充电桩建设和运营的特点,剖析其中面临的安全风险,并提出加强安全管理工作的措施,为充电桩企业安全管理运营提供参考和借鉴。     

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.     

STX1(2)型驮背多功能运输车超偏载检测标准

分析了STX₁₍₂)型驮背多功能运输车对既有超偏载检测方法和标准的适应性,提出了该车的超偏载检测方案,明确了公路货车或半挂车超偏载的检测方法及评判标准。     

Consumer preferences for battery electric vehicles: A choice experimental survey in China

To accelerate the diffusion of battery electric vehicles (BEVs), consumer preferences for different products and policy attributes must be determined. Although previous studies have investigated consumer preferences for some product attributes, including purchase price, operation cost, driving range, and charging time, limited studies have discussed the broader aspects of product attributes, such as battery warranty and depreciation rate. Moreover, market-oriented incentives, including the personal carbon trading (PCT) scheme and the tradable driving credits (TDC) scheme, can theoretically be effective alternatives to expensive purchase subsidies. However, there is a lack of empirical evidence that confirms the influence of these two schemes on BEV adoption. To fill these gaps, we conducted a stated preference choice experimental survey in China and investigated the effect of product attributes, existing policy incentives, and two emerging market-oriented incentives on BEV adoption. Our results reveal that along with the main product attributes, battery warranty has a significant positive effect on inducing mainstream consumers to adopt BEVs while no preference difference occurs among existing policy incentives after purchase subsidies are abolished. For young consumers, almost all incentives that reduce the operation cost (e.g., PCT) or increase convenience (e.g., TDC) can increase their adoption of BEVs. These findings can provide important implications for the government with regard to designing novel incentives and promoting BEV adoption.