Optimization of limited network capacity with toll settings

A non-smooth optimization model is established for determining reserve capacity of a road network with toll settings. Optimization of limited network capacity with toll settings can be formulated as a mathematical program with equilibrium constraints (MPEC). A quasi-Newton subgradient projection and contractive method (QSPC) with global convergence is proposed. Numerical calculations are conducted using an example network where good results are obtained.     

基于云网格集成调度的防拥堵车辆路径规划算法

在道路交通路网中,车辆拥堵问题是流量与路网结构之间相互作用的一个复杂动态过程,通过车辆路径规划,实现对路网网格集成调度,从而提高路网通行吞吐量。传统方法采用并行微观交通动态负载平衡预测算法实现车辆拥堵调度和车辆路径规划,不能准确判断路面上的车辆密度,路径规划效益不好。提出一种基于云网格集成调度的防拥堵车辆路径规划算法,即构建基于Small-World模型的云网格路网模型,采用RFID标签信息进行路况信息采集,实现交通网络拥堵评估信息特征的提取,采用固有模态函数加权平均求得各车道的车辆拥塞状态函数,对所有车道内车辆密度取统计平均可获得簇内的车辆密度。设计交通路网拥堵检测算法来对当前个体道路信息进行一维邻域搜索,从而实现车辆路径规划控制目标函数最佳寻优。通过动态博弈的方式求得车辆防拥堵路径的近似最优轨迹,实现路径规划算法的改进。仿真结果表明,该算法能准确规划车辆路径,实现最优路径控制,从而提高严重拥堵路段的车流速度和路网吞吐性能,性能优越。     

智能收费系统关键技术研究及实现

不停车电子自动收费系统是提高高速公路车辆通过率的关键技术设备之一。文章论述了智能收费系统的构成原理和关键技术，着重讨论了射频技术、网络通信、计算机视觉和系统管理等技术方法的应用概况，提出了一套具体的解决不停车自动收费系统的方案，对发展智能收费技术有一定的参考意义。     

Vibration control of vehicle active suspension system using a new robust neural network control system

The main problem of vehicle vibration comes from road roughness. For that reason, it is necessary to control vibration of vehicle’s suspension by using a robust artificial neural network control system scheme. Neural network based robust control system is designed to control vibration of vehicle’s suspensions for full suspension system. Moreover, the full vehicle system has seven degrees of freedom on the vertical direction of vehicle’s chassis, on the angular variation around X-axis and on the angular variation around Y-axis. The proposed control system is consisted of a robust controller, a neural controller, a model neural network of vehicle’s suspension system. On the other hand, standard PID controller is also used to control whole vehicle’s suspension system for comparison.Consequently, random road roughnesses are used as disturbance of control system. The simulation results are indicated that the proposed control system has superior performance at adapting random road disturbance for vehicle’s suspension.     

高速公路自动收费系统日常维护

近年来,随着高速公路通车里程的快速增长,其在路网中的重要性日益突出。在这种情况下,采用非现金方式支付通行费,利用先进的电子手段,使车辆不需要停车就能收取通行费的系统就成为迫切的需要。针对目前的现状,采用车载识别卡与收费车道自动车辆识别系统,通过无线电波实现车辆自动识别和数据交换,并由计算机系统控制指挥车辆通行。利用计算机系统控制的高速公路自动收费系统,有效的提高了收费效率,但对于高速公路自动化收费系统的维护也提出了更高的要求。     

面向车载容迟网络的连通性建模与仿真研究

针对车载容迟网络连通性建模进行了研究。首先假设车辆驶入道路的过程服从泊松分布,以及车辆在道路上的行驶速度服从正态分布。继而对基于泊松过程的车间时距分布进行推导,并以此导出行驶车辆在道路上的连通概率。为了验证所提假设和连通模型的正确性和有效性,以欧洲城市卢森堡在7:30 a.m.~8:30 a.m.时间段内的交通数据为实验场景,在城市交通仿真平台（simulation of urban mobility,SUMO）对车辆速度的概率分布、车辆到达率、道路中的平均车辆数及网络连通概率进行了理论计算和仿真实验分析。实验结果表明理论模型的计算值和仿真结果是一致的,所提出的假设和连通模型具有合理性和正确性。     

A heuristic approach to commodity purchasing

In this paper a Heuristic model is proposed for commodity purchasing. The model is based on the combined use of Dynamic Programming model and a price trend forecasting model. The proposed approach is highly efficient and is simple to use even by a layman. Performance of the proposed model is compared with that of the Dynamic Programming model. The results of the sensitivity analysis indicate that the proposed approach performs consistently better compared to that of the Dynamic Programming model. It is. therefore, believed that the proposed approach would be fruitfully utilized in designing an optimal commodity purchasing system.     

Traffic modelling framework for electric vehicles

This article reviews and improves a recently proposed model of road network dynamics. The model is also adapted and generalised to represent the patterns of battery consumption of electric vehicles travelling in the road network. Simulations from the mobility simulator SUMO are given to support and to illustrate the efficacy of the proposed approach. Applications relevant in the field of electric vehicles, such as optimal routing and traffic load control, are provided to illustrate how the proposed model can be used to address typical problems arising in contemporary road network planning and electric vehicle mobility.     

路桥不停车电子自动收费系统的实现

本文介绍一种用于公路、桥梁不停车收费的完善的电子自动收费体系.该体系由自动收费交通控制管理网络和银行清算辅助网络组成;两大网络通过拨号方式实现电子数据交换,达到通行控制与电子收费相结合的目的,利用TAG卡或感应式IC卡为电子媒体,实现不停车收费.     

Neural Network Based Feedback Linearization Control of an Unmanned Aerial Vehicle

This paper presents a flight control design for an unmanned aerial vehicle (UAV) using a nonlinear autoregressive moving average (NARMA-L2) neural network based feedback linearization and output redefinition technique.The UAV investigated is non- minimum phase.The output redefinition technique is used in such a way that the resulting system to be inverted is a minimum phase system.The NARMA-L2 neural network is trained off-line for forward dynamics of the UAV model with redefined output and is then inverted to force the real output to approximately track a command input.Simulation results show that the proposed approaches have good performance.     

Simulation Exercise on Time Perception Parameters in Discrete-time Dynamic Assignment Models

In order to assess the performance of information systems to road users and of demand management measures, like staggered and/or flexible work times and road pricing, with respect to congestion prevention problems, it is necessary to simulate dynamics of traffic flows on the transport network and users' behaviour. This can be accomplished by taking into account several aspects such as users' information level, travel demand distribution over time and the expected smoothing effect of adopted measures and information systems. Dynamic assignment and arrival time choice models and computational procedures to perform this assessment for various traffic scenarios and hypotheses about users' behaviour are presented in this paper. Moreover, the indicators needed to quantify information systems and demand management effectiveness are identified together with parameters defining traffic scenarios. The main results obtained by applying these models and techniques as deterministic and probabilistic simulation tools are also presented and discussed.     

A GPS-free method for vehicle future movement directions prediction using SOM for VANET

Predicting the next movement directions, which will be chosen by the vehicle driver at each junction of a road network, can be used largely in VANET (Vehicular Ad-Hoc Network) applications. The current methods are based on GPS. In a number of VANET applications the GPS service is faced with some obstacles such as high-rise buildings, tunnels, and trees. In this paper, a GPS-free method is proposed to predict the vehicle future movement direction. In this method, vehicle motion paths are described by using the sequence of turning directions on the junctions, and the distances between the junctions. Movement patterns of the vehicles are extracted through clustering of the vehicle’s motion paths using SOM (Self Organizing Map). These patterns are then used for predicting the next movement direction, which will be chosen by the driver at the next junction. The obtained results indicate that our GPS-free method is comparable with the GPS-based methods, while having more advantages in different applications regarding urban traffic.     

一种改进的神经网络道路跟踪方法

ALVINN是目前世界上性能最好的基于神经网络的智能车道路跟踪系统,但由于其道路 跟踪摄像机是固定不变的,导致在转弯时可能丢失道路信息,从而使其性能下降,甚至不能 完成这一任务．本文提出一种道路跟踪方法,使得在学习过程中和自主道路跟踪状态下,都 能有效地控制道路跟踪摄像机的方位角,以保证道路尽可能处于摄像机采集的图像中央,在 客观上为改进ALVINN的道路跟踪性能提供了可能,计算机仿真结果验证了这种方法的有效性 ．     

多受灾点应急救援车辆调度的优化遗传算法

在多个地区发生灾害后,迫切需要及时救援和物资的快速运输,从仓库调拨物资到受灾点,交通网络规模较大,运输货物类型多样,并且要满足各个受灾点的资源需求、实时路况、运抵时限要求等多个目标约束条件,车辆调度具有较大难度.为解决多重约束带来的困难,根据遗传算法的生物进化理论和群体遗传学机制,建立了车辆应急运输的多目标优化问题模型,设计合适的序列编码方式表示车辆行进路线及运输货物类型;建立了新的优化遗传算法,从编码方式的设计、适应度函数、选择、交叉和变异操作机制的设计三个方面做了创新改进,主动保持优良基因,根据阶段进展调节交叉和变异概率,有效提高好的新模式的产生几率,较好地克服了已有方法的早熟局部收敛所导致的结果偏差较大的不足.多个仿真实验结果表明,优化遗传算法比已有算法在满足送达时限以及送达时间的总长度等方面均有较大提高,对于复杂的调度任务,在保证运抵时限的前提下,可占用更少的车辆,花费更少的行进时间完成物资运输,从而满足多受灾点对物资的实时性需求.     

公路联网收费系统网络故障诊断与解决措施探讨

随着社会经济的蓬勃发展,我国的公路系统也越来越发达。网络给公路收费系统带来便利的同时,也带来了危机。本文对公路联网收费系统常见网络故障进行了分析,并提出了相关解决措施。     

无线Mesh网络的高实时业务调度方法*

为了解决无线Mesh网络实时业务的规划调度问题,提出一种基于动态规划的实时业务调度算法。首先,通过边集映射,将网络中的边转化为映射节点,进行阶段划分。然后,每个Mesh路由器节点根据缓存中的队列情况预测数据包的排队时间,并结合业务截止期,进行优先级重新分配,得到映射边的接入权值。最后,利用动态规划算法,根据映射边的接入权值选择最优的映射节点接入次序,得到该业务在各阶段的最优调度顺序。仿真结果表明,该算法能够兼顾高、低优先级业务的实时需求,降低全网业务的平均时延和丢包率。     

ETC系统中车道控制器的设计

车道控制器是ECT系统中的重要组成部分.车道控制器用于管理ETC系统中的交通信号灯、视频采集设备、栏杆机、车辆检测设备和费额显示器等设备.介绍了一种基于W77E58微处理器的车道控制器的详细设计方案,同时给出了车道控制器的硬件结构和软件组成.     

A predictor-corrector guidance control scheme for AGV navigation

This paper presents a scheme that employs feedforward control in conjunction with a predictor-corrector scheme for guidance control of Automated Guided Vehicles (AGVs). The predictor-corrector scheme provides the desired values of steering parameters which depend on the geometry of the track and a driving criterion. The geometry of the track/road ahead of the vehicle is obtained by extrapolating the identified (estimated) geometry of the track/road traversed during the elapsed time interval. This real-time identification is carried out by fitting a curve to the path traversed by the vehicle. The coordinates of the path are provided by a transformation formulation which makes use of the motion parameters and a kinematic model of the vehicle. The driving criterion specifies the positioning of the AGV on the track. Several possible criteria are identified in the paper and mathematical formulations are presented for one such criterion. Results of off-line calculations using simulated track profiles and experimental data obtained using a prototype AGV while following various track profiles are provided for illustration.     

Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling

The development of mobile positioning technologies makes massive individual trajectory data easily accessible, which facilitates the revisit of spatial interaction issue in recent years. Researchers have proposed many methods to investigate the spatial interactions derived from human movements, such as the gravity model and radiation model. However, these studies have mainly focused on the interactions among areal units at an aggregated level, neglecting that in most cases, human movements are carried by vehicles and constrained by the underlying road network, which causes the interactions among roads. To fill this gap, we propose a novel approach to identify spatial interaction patterns of vehicle movements on urban road network. As the topic model originating from the domain of natural language processing has powerful advantages in extracting semantic relations of words from corpus, we utilize it to extract interaction relations of urban roads from massive vehicle trajectories. First, "strokes" (i.e., natural streets) are chosen as geographical units to represent the vehicle moving paths. Then, an analogy between geographical elements (i.e., stroke, moving path) and textual elements (i.e., word, document) is established, and a topic model is applied to the moving paths to identify the spatial interaction patterns on road network. From a mass of trajectory data collected by GNSS-equipped taxis in Beijing, the "topic patterns", which can be viewed as clusters of spatially interacted strokes, are identified, visualized and verified. It is argued that our proposed approach is effective in identifying spatial interaction patterns, which provides a new perspective for spatial interaction modelling and enriches the current spatial interaction studies.     

基于等效网络的车辆导航系统路线规划算法

在实际交通行为中,不可避免地存在着交叉口时间延迟,而且交通管制信息如交叉口转向限制也普遍存在,这些交通特征使得常规的最短路算法难以满足车辆导航系统路线规划的要求。提出基于“节点-弧段-特征”的数据结构存储方案,能够完整描述路网的平面拓扑和交通特征属性;针对具有交叉口转向限制和交叉口延迟等特征的交通网络,首先采用对偶图方法构造等效网络,在等效网络中采用常规的最短路算法计算最优路线,然后将它转化为原道路网中的行车路线。试验证明这种方法能够有效解决包含交通特征的车辆导航系统路线规划问题.