Towards lane-level traffic monitoring in urban environment using precise probe vehicle data derived from three-dimensional map aided differential GNSS

Today's urban road transport systems experience increasing congestion that threatens the environment and transport efficiency. Global Navigation Satellite System (GNSS)-based vehicle probe technology has been proposed as an effective means for monitoring the traffic situation and can be used for future city development. More specifically, lane-level traffic analysis is expected to provide an effective solution for traffic control. However, GNSS positioning technologies suffer from multipath and Non-Line-Of-Sight (NLOS) propagations in urban environments. The multipath and NLOS propagations severely degrade the accuracy of probe vehicle data. Recently, a three-dimensional (3D) city map became available on the market. We propose to use the 3D building map and differential correction information to simulate the reflecting path of satellite signal transmission and improve the results of the commercial GNSS single-frequency receiver, technically named 3D map-aided Differential GNSS (3D-DGNSS). In this paper, the innovative 3D-DGNSS is employed for the acquisition of precise probe vehicle data. In addition, this paper also utilizes accelerometer-based lane change detection to improve the positioning accuracy of probe vehicle data. By benefitting from the proposed method, the lane-level position, vehicle speed, and stop state of vehicles were estimated. Finally, a series of experiments and evaluations were conducted on probe data collected in one of the most challenging urban cities, Tokyo. The experimental results show that the proposed method has a correct lane localization rate of 87% and achieves sub-meter accuracy with respect to the position and speed error means. The accurate positioning data provided by the 3D-DGNSS result in a correct detection rate of the stop state of vehicles of 92%.     

Simulation of vertical dynamic vehicle–track interaction using a two-dimensional slab track model

The vertical dynamic interaction between a railway vehicle and a slab track is simulated in the time domain using an extended state-space vector approach in combination with a complex-valued modal superposition technique for the linear, time-invariant and two-dimensional track model. Wheel–rail contact forces, bending moments in the concrete panel and load distributions on the supporting foundation are evaluated. Two generic slab track models including one or two layers of concrete slabs are presented. The upper layer containing the discrete slab panels is described by decoupled beams of finite length, while the lower layer is a continuous beam. Both the rail and concrete layers are modelled using Rayleigh–Timoshenko beam theory. Rail receptances for the two slab track models are compared with the receptance of a traditional ballasted track. The described procedure is demonstrated by two application examples involving: (i) the periodic response due to the rail seat passing frequency as influenced by the vehicle speed and a foundation stiffness gradient and (ii) the transient response due to a local rail irregularity (dipped welded joint).     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

Vehicle value of travel time savings: Evidence from a group-based modelling approach

The value of travel time savings (VTTS) accounts for a majority of the total user benefits in economic appraisal of transport investments. This means that having an accurate estimate of VTTS for different segments of travel continues to retain currency, despite there being a rich literature on estimates of VTTS for different travel modes, travel purposes, income groups, life cycles, and distance bands. In contrast, there is a dearth of research and evidence on vehicle VTTS, although joint travel by car is an important segment of travel. This paper fills this gap by developing a group-based modelling approach to quantify the vehicle VTTS and compares this with the VTTS for a driver with and without a passenger. An online survey was conducted in Sydney in 2014 and the data used to obtain a number of new empirical estimates of vehicle and driver VTTS. The new evidence questions the validity of various assumptions adopted in current practice for valuing the time savings of car passengers and multiple occupant cars.     

International experience with speed limits during and prior to the energy crisis of 1973–4

This paper presents an artificial neural network (ANN) based method for estimating route travel times between individual locations in an urban traffic network. Fast and accurate estimation of route travel times is required by the vehicle routing and scheduling process involved in many fleet vehicle operation systems such as dial‐a‐ride paratransit, school bus, and private delivery services. The methodology developed in this paper assumes that route travel times are time‐dependent and stochastic and their means and standard deviations need to be estimated. Three feed‐forward neural networks are developed to model the travel time behaviour during different time periods of the day‐the AM peak, the PM peak, and the off‐peak. These models are subsequently trained and tested using data simulated on the road network for the City of Edmonton, Alberta. A comparison of the ANN model with a traditional distance‐based model and a shortest path algorithm is then presented. The practical implication of the ANN method is subsequently demonstrated within a dial‐a‐ride paratransit vehicle routing and scheduling problem. The computational results show that the ANN‐based route travel time estimation model is appropriate, with respect to accuracy and speed, for use in real applications.     

Scaled vehicle tire characteristics: dimensionless analysis

This article demonstrates the use of dimensional analysis for scaled vehicle tires. The motivation for this approach is the understanding of realistic nonlinear tire behavior in scaled vehicle control studies. By examining the behavior of vehicle tires within a dimensionless framework, several key tire parameters are developed that allow for an appropriate relationship between full-sized tires and scaled tires. Introducing these scalings into vehicle dynamics studies allows for the development of scaled vehicles that have a high degree of dynamic similitude with full-sized vehicles, but are safer and more economical testbeds on which to develop experimental control strategies. Experimental data are used to compare the nonlinear characteristics for sets of scaled and full-sized tires. Finally, design of a scaled vehicle based on tire characteristics is demonstrated.     

基于区位理论的物流配送中心车辆调度优化算法

针对物流配送中心的车辆调度,建立了车辆分配和路径优化的数学模型,并对配送分区的实现采用四叉树法;对运输巡回线路的实现采用蚁群算法求解。通过算例,给出了基于区位理论的物流配送中心车辆分配和路径优化的具体方案。     

摩托车国Ⅲ排放整车匹配试验研究

通过对原车排放摸底，然后对供油系统进行针对性的调整优化，进而对催化转化器和二次空气阀进行匹配，配合较完善的检测手段，北京英泰公司的摩托车排放控制技术方案和产品可以很好地满足国Ⅲ排放标准的限值和耐久性要求。     

车用滑动轴承及常用的合金材料

滑动轴承是内燃机中的重要部件,常见车用滑动轴承的质量优劣,与其选用的合金材料密切相关。文章较详细地阐述了汽车发动机曲轴上,承受径向载荷的滑动轴承的性能特点、组织结构及内燃机滑动轴承的常用材料;同时还分别介绍了锡基轴承合金、铅基轴承合金、铝基轴承合金、铜基轴承合金及多层轴承合金的滑动轴承中合金材料的特点、性能和用途。使用中应做到合理选用,以发挥其应有作用,延长使用寿命。     

乌鲁木齐地铁2号线哈马山车辆基地方案研究

国内对西北地区地铁车辆基地总平面布置、屋架结构形式及屋面采光方案的系统研究较少。从乌鲁木齐地铁2号线哈马山车辆基地的选址用地入手,通过分析段址环境及出入段线接轨条件,对场坪高程确定及总平面布置方案进行研究。通过对国内工业厂房普遍采用的钢筋混凝土柱支承网架结构、钢筋混凝土柱支承梯形钢屋架结构及门式刚架结构的特点进行对比分析,从节省用钢量及便于库内上部管线的布置角度推荐采用钢筋混凝土柱支承网架结构形式。通过对屋面三角形天窗、采光带/采光板及矩形天窗的特点进行对比分析,从采光效率及不易被积雪覆盖角度推荐采用三角形天窗形式。