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.     

Scheduling of Intelligent and Autonomous Vehicles under pairing/unpairing collaboration strategy in container terminals

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.     

Network equilibrium models with battery electric vehicles

The limited driving ranges, the scarcity of recharging stations and potentially long battery recharging or swapping time inevitably affect route choices of drivers of battery electric vehicles (BEVs). When traveling between their origins and destinations, this paper assumes that BEV drivers select routes and decide battery recharging plans to minimize their trip times or costs while making sure to complete their trips without running out of charge. With different considerations of flow dependency of energy consumption of BEVs and recharging time, three mathematical models are formulated to describe the resulting network equilibrium flow distributions on regional or metropolitan road networks. Solution algorithms are proposed to solve these models efficiently. Numerical examples are presented to demonstrate the models and solution algorithms.     

Smarter and more connected: Future intelligent transportation system

Emerging technologies toward a connected vehicle-infrastructure-pedestrian environment and big data have made it easier and cheaper to collect, store, analyze, use, and disseminate multi-source data. The connected environment also introduces new approaches to flexible control and management of transportation systems in real time to improve overall system performance. Given the benefits of a connected environment, it is crucial that we understand how the current intelligent transportation system could be adapted to the connected environment.     

“1+X”证书制度下的汽车检测与维修专业“三教”存在问题研究

在教学过程中,"师资,教材,教法"是基本内容,教学质量指标也受到影响。本文以新能汽车检验维修专业为例,对职教二十条进行了分析。职业教育"三教一体化"改革的重要性,同时,针对教师,教材和教学方法等问题提出了切实可行的改革思路,仅供相关人员参考。     

Connected cruise control: modelling,delay effects,and nonlinear behaviour

Connected vehicle systems (CVS) are considered in this paper where vehicles exchange information using wireless vehicle-to-vehicle (V2V) communication. The concept of connected cruise control (CCC) is established that allows control design at the level of individual vehicles while exploiting V2V connectivity. Due to its high level of modularity the proposed design can be applied to large heterogeneous traffic systems. The dynamics of a simple CVS is analysed in detail while taking into account nonlinearities in the vehicle dynamics as well as in the controller. Time delays that arise due to intermittencies and packet drops in the communication channels are also incorporated. The results are summarised using stability charts which allow one to select control gains to maintain stability and ensure disturbance attenuation when the delay is below a critical value.     

自律分布数字化列车控制系统及在线扩展技术

现行ATC系统控制模式存在自动闭塞区间长度以性能最差的列车确定,多级制动时加减速度急剧变化,降低乘坐舒适度等缺点,需要构建车载设备智能化程度高的自律数字化列车控制系统(D ATC),以提高我国CTCS等级。有综合车载系统与独立车载系统两种方法实现系统在线构建。用测试方法进行确信性评估,证明综合车载系统便于进行高效率的在线测试和安全运行。     

机车车辆滚动振动试验台和试验方法

本文阐述了机车车辆室内试验台试验的优点，系统介绍了我国自行研制的机车车辆整车滚动振动试验台，从运动自由度、机械结构到系统的组成，并给出试验台的主要功能参数、试验能力，最后介绍了机车车辆动力学试验台试验方法和试验过程。     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.