网联环境下混合交通流偶发拥堵演化机理研究

针对混合交通流中智能网联车辆(Connected and Autonomous Vehicles, CAVs)和人工驾驶车辆的交织干涉问题,本文在传统交通流统计理论模型和一阶连续介质模型的基础上,通过引入智能驾驶员跟驰模型(Intelligent driver model, IDM)和协同自适应巡航控制模型(Cooperative Adaptive Cruise Control, CACC),构建人工驾驶车辆和CAVs的混合交通流偶发拥堵演化模型,探索CAVs混入和诱导干涉措施对混合交通流偶发性拥堵传播规律的影响。实验选取重庆市华陶立交至巴南立交路段为路网原型,对CAVs不同渗透率( Pc )下的路段拥堵演化情况进行仿真。实验结果表明：CAVs渗透率越高,混合流流量、占有率和速度的改善情况越显著,但只有当 Pc ≥ 0.2 时,网联车辆对拥堵消散的改善效果才较为明显;Pc ≤ 0.8 时,干涉措施下,拥堵消散状态的持续时间约为不采用干涉措施的 50%;当 Pc = 1.0 时,网联车辆的通行能力是纯人工驾驶交通流的2.34倍;分别在非干涉措施和干涉措施下计算拥堵评价指标,与仿真结果进行对比,最大相对误差在5.38%之内,验证了模型的准确性。研究成果对疏散交通拥堵具有重要意义。     

嵌入式计算机系统在水下航行器的应用

针对小型水下航行器航行和工作特点,论述了采用嵌入式ＭＣＵ与ＥＤＳＰ器件和Ｉ＾２Ｃ总线技术构成的监测与控制系统。     

城市快速公交专用道道路线形设计分析

以汽车的动力特性和通过特性为理论依据,根据目前快速公交专用车辆大都采用低地板大型铰接底地板车辆的现状,结合其容量比一般普通公交大得多的特点,对快速公交专用道的道路线形设计进行分析,提出设计方法。     

Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.     

Fault classification method for the driving safety of electrified vehicles

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.     

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of energy efficient vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (±0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008, i.e., 519 privately owned, exempt EEVs.     

Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.     

Incorporating sustainability assessment in transportation planning: an urban transportation vehicle-based approach

Environmental assessments are on the critical path for the development of land, infrastructure and transportation systems. These assessments are based on planning methods which, in turn, are subject to continuous enhancement. The substantial impacts of transportation on environment, society and economy strongly urge the incorporation of sustainability into transportation planning. Two major developments that enhance transportation sustainability are new fuels and vehicle power systems. Traditional planning ignores technology including the large differences among conventional, hybrid and alternative fuel vehicles and buses. The introduction of alternative fuel vehicles is likely to change the traditional transportation planning process because different characteristics need to be taken into account. In this study a sustainability framework is developed that enables assessment of transportation vehicle characteristics. Identified indicators are grouped in five sustainability dimensions (Environment, Technology, Energy, Economy and Users). Our methodology joins life cycle impacts and a set of quantified indicators to assess the sustainability performance of seven popular light-duty vehicles and two types of transit buses. Bus Rapid Transit receives the highest sustainability index and the pickup truck the lowest. Hybrid electric vehicles are found to have the highest sustainability index among all other passenger vehicles. A sensitivity analysis shows the proposed sustainability dimensions produce robust sustainability assessment for several weighting scenarios. The results are both technology and policy sensitive, thus useful for both short- and long-term planning.     

Influence of connected and autonomous vehicles on traffic flow stability and throughput

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.     

新形势下我国新能源汽车政策现状与发展趋势研究

汽车产业作为我国重要的经济支柱产业,在我国的经济发展和国家发展中发挥了重要的作用,为了寻求产业发展和能源消耗之间的平衡,新能源汽车的概念应时而生。特别是在当前我国各方面建设都进入新常态的形势下,推进新能源汽车的进一步发展,是现在我们必须要认清的一个很迫切的问题,也是一个很现实的问题。