微观交通再现仿真系统研究与开发

为了再现过去某段时间的交通状况,提出一个微观交通再现仿真系统,主要由车辆生成模型、OD分配模型和车辆初始分布模型组成。仿真系统对车辆仿真进行了再现分析,能够有效展示各路段上的交通流量、车辆密度、车辆的行驶速度,真实再现路段上的交通流状况。选取上海市中环路的实际采集数据进行仿真验证,结果表明微观交通再现仿真系统真实再现了交通流的时空变化。应用该系统能够为交通道路规划与管理提供技术支持,并能对各种交通参数进行比较和评价。     

城市中观交通仿真的交通流车簇模型

为了解决城市交通仿真模型仿真速度和仿真精确度的平衡问题,针对城市交通流运行特征,同时考虑影响交通流运行的若干因素,如车辆数目、红绿灯控制等,提出一种中观交通仿真车辆群体模法.该模型结合了宏观模型和微观模型的优点,同时对应的交通流配流算法解决了传统模型的不足,城市交通仿真实验结果表明了车辆群体模型和分配算法的合理性和有效性.     

基于SUMO平台的微观交通仿真研究

微观交通仿真在城市交通控制系统中有着重要地位,而微观仿真模型的建立是其主要内容之一。Krauss模型是基于安全车速范式的微观、空间连续的车辆跟驰模型,为避免原始Krauss模型中加速度突变的问题,本文在其基础上提出了融合车辆减速度渐变过程的新模型。在SUMO仿真平台上编程实现了改进后的车辆跟驰模型,并在同等条件下对原始模型和改进模型进行了实例仿真分析,结果表明改进后的模型在一定程度上避免了加速度突变问题,交通流运行的仿真情况在整体性能上有显著改善,仿真效果与现实交通情况更趋一致。     

复杂交通环境无人驾驶车辆防碰撞方法仿真

无人驾驶车辆自身具有强非线性特征,且信号时延和参数的不确定性特点显著,同时还易受道路附着系数及前后车距离等因素影响。为此提出复杂交通环境无人驾驶车辆防碰撞方法。构建无人驾驶车辆相关的动力学模型,并利用模型预测车辆在行驶过程中的相关数据。采用切比雪夫定律预处理车辆的数据信息,得到前后车辆的运动参数。通过模型预测控制法对参数求解,得到无人驾驶车辆的最佳行驶轨迹与跟踪控制序列,完成复杂交通环境无人驾驶车辆的防碰撞。仿真结果表明,所提方法的路径跟踪效果与给定路径一致、避障能力达到100%,常规状态与紧急状态下的跟踪-避障能力强。因此所提方法具有整体有效性,研究价值较高。     

基于MT发生器的车辆生成模型构建与仿真

针对交通流仿真技术中广泛使用的线性同余发生器在周期长度和随机性方面的不足,引入MT随机数发生器,通过性能评价验证其优越性,然后在空闲和拥挤两种交通状态下,基于MT发生器产生的随机数,应用不同的随机分布构建相应的随机发车模型。在VC环境下开发车辆生成程序进行仿真实验,将仿真数据与实测数据进行对比分析,结果表明,基于MT发生器的随机发车模型更好地逼近了实际交通状态。     

基于停车线位置的左转车辆行驶轨迹仿真模型

以信号交叉口左转车辆为研究对象,根据数值逼近和几何学原理,建立了停车线位置改变前后两种不同的左转车辆行驶轨迹仿真模型。对于当前交通状态,采用最佳平方逼近和Chebyshev近似原理的方法,建立了左转车辆行驶轨迹的三次抛物线模型,并通过实例予以验证;对于停车线位置改变后的未来状态,给出了直线—回旋线—回旋线—直线组合的左转车辆行驶轨迹模型。进一步,建立了停车线位置与临界半径函数关系线性模型,使回旋线参数计算更为简单。仿真结果表明,所建模型较好地逼近了相应交通状态。     

基于时序CPN的交叉路口车辆控制模型

对比经典Petri网模型，提出了基于时序CPN的交叉路口车辆控制模型，从时间和空间上对车辆的流通进行描述。使用CPN Tools建立时序CPN模型并进行仿真，模拟了交叉路口的车辆交通过程，实验结果证明该模型很好的反映了车辆流通时的时间和位置信息等动态特征。     

混合粒子群算法求解交通路网中的车辆调度问题

为使路网中的车辆调度问题更加符合实际交通状况．提出了改进的车辆调度模型;针对这个模型,将粒子群算法和模拟退火算法相结合,设计了混合粒子群算法求其有效近似解;最后结合西安市实际交通调查数据．编程实现混合粒子群算法对模型进行计算与仿真,仿真结果表明了此方法的有效性．     

基于Agent的驾驶员-车辆建模研究与实现

微观交通仿真技术是解决城市交通网络拥塞问题的有效工具.在各种交通元素中,驾驶员-车辆单元是交通流的主体.该文通过对交通流中驾驶员、车辆特性的分析,将驾驶员和车辆视为一个整体,并基于Agent理论对之进行建模.文中详细分析了Agent的生成和路径搜索及选择算法,研究了Agent的跟驰、换道和挤占道等行为.该文最后介绍了基于Agent模型建立的一种微观交通仿真器,并在该仿真器上进行仿真实验.结果表明该系统能够较好的仿真实际交通流状况.     

基于Multi-Agent的多车道交通流的分布式仿真研究

该文以Agent技术为基础,对多车道交通流进行了模拟,并与实际的道路交通流特点进行了比较。首先根据驾驶员实际驾车的特点,建立车辆Agent的基本模型,对车辆Agent换道超车和加速策略进行描述。然后以分布式模型为基础,将多车道交通环境中的车辆运行模拟为Multi-Agent的相互作用。在仿真中,采用了面向Agent的仿真软件Starlogo。从微观上看,所描述的车辆模型能够完成加速和换道过程;从宏观上看,仿真中交通流特点与实际情况是一致的。说明该文的模型符合实际情况,同时也表明了使用Agent技术进行多车道交通流系统仿真的准确性和可行性。     

连续交通流可视化仿真

在大型城市的交通态势模拟中,宏观模型相比于微观模型,具有效率高,物理意义明确的优点,但缺乏车辆在各个时刻的细节描述。为了使宏观模型的交通模拟的显示更加直观,结合微观模型的更新方式,提出了基于宏观模型的可视化方法。通过道路上的车辆初始密度得到所有车辆的初始位置和速度;根据宏观路段速度更新车辆信息,使得宏观路段密度值与微观车辆所构成的车辆流密度相符。该方法能够给出宏观模型中车辆在各个时刻的运动情况,并添加了微观上的细节。以实例证明了该方法的可行性。     

Visual perception modelling for intelligent virtual driver agents in synthetic driving simulation

This paper introduces a vision model used within a synthetic (or purely software-based) driving simulation framework. This framework represents driver decision-making, individual vehicle movement and emergent traffic flow, and is intended to aid the integration of driver psychology, traffic management and vehicle engineering. The aims of developing the vision model discussed here are twofold: Firstly, to remove the unrealistic availability of ‘perfect knowledge’ concerning the positions and velocities of vehicles in a simulation and secondly, to provide a means of introducing deeper cognitive models of driver reasoning and behaviour. The paper presents the essential mechanisms of the vision model, along with the results of initial validation experiments conducted with Leicestershire Constabulary, Traffic Division in the UK. In these experiments, subjects' visual perception of positions and speeds of moving vehicles were measured and compared with estimations of the agent based driving simulator. The results have demonstrated the feasibility of modelling driver vision within an agent based traffic simulation using concepts derived from AI and ALife systems. The paper is completed by a short discussion on the future development of cognitive models enabled through more detailed vision modelling.     

基于路由机制的变权网络路径快速生成算法

在大规模交通流仿真中,车辆个体路径生成环节存在着大量重复计算。为避免重复计算及提高车辆个体路径生成速度,将计算机网络中的路由机制引入到交通流仿真中,提出一种基于路由机制的变权网络路径快速生成算法,即把每个道路路口节点作为路由器,分解并存储原本与车关联的路径作为指路信息。仿真车辆通过访问该指路信息获取下一步行车方向,并且当路网权值发生变化时,能及时响应路网的动态变化,从而给出求实时路况下仿真车辆行驶路径的一种方法。     

动态车辆路径问题中实时信息生成算法

实时信息的产生对动态车辆路径问题仿真器的研究起着非常重要的作用。为此,提出了实时信息的生成算法,包括随机公路网络的生成,实时交通信息的生成和随机客户需求的生成等。实验结果表明,算法所产生的实时信息和现实中的实时信息比较接近,能够满足动态车辆路径问题仿真器的要求。     

The effectivity of new traffic-technologies and transportation-systems in suburban areas and on motorways

At the Forschungsgesellschaft Kraftfahrwesen mbH Aachen (fka) the submicroscopic traffic simulation program PELOPS (Program for the dEvelopment of Longitudinal micrOscopic traffic Processes in a Systemrelevant environment) was developed in co-operation with the BMW AG. It simulates the traffic flow on motorways with a specific view on vehicle affairs. One application for PELOPS was the assessment of ACC (Adaptive Cruise Control) systems inside the PROMETHEUS program. A new research period extends the use of ACC about the functionality to urban areas. This requires an extension of PELOPS to include some specific models. With this extension, it is possible to analyse new traffic technologies for individual vehicles or infrastructure. Based on detailed traffic measurements, different scenarios are simulated to improve the traffic flow and to relieve the environment. These scenarios include ACC systems, inter-vehicle-communication and intelligent traffic lights. Another actual application is the analysis of the influence of new road trains (extra-long trucks with increased speed and enhanced breaking-capabilities) on traffic-flow and driving safety on German motorways. The paper gives detailed information about the simulation techniques and the results of the current analysis.     

T-CPS下考虑人驾车行为影响的混行车辆协同控制

由于传统人驾车(traditional human-driven vehicles,HVs)驾驶行为会受到驾驶员的心理和生理活动的不确定性影响,可能使得车辆频繁地加减速,进而导致混合交通条件下网联自动车(connected and automated vehicles,CAVs)很难快速跟踪此行为.针对这一问题,首先提出一种提前预测传统人驾车行为的组合神经网络.在此基础上,考虑通信时延和车辆运动学特性,设计一种基于交通信息物理系统(transportation-cyber physical system,T-CPS)的混行车群内车辆协同控制策略,使其能够快速跟踪上传统人驾车行为,并对混行车群内网联自动车之间的串稳定性进行分析.最后,在混合交通条件下设置由1辆传统人驾车、1辆领头网联自动车和4辆跟随网联自动车形成的混行车群,利用下一代交通仿真(next generation simulation,NGSIM)车辆轨迹数据选出高质量传统人驾车状态,并通过仿真实验验证所提协同控制策略的有效性和可行性.由仿真实验结果可知,所提协同控制策略可以保证所有的网联自动车能够快速跟踪上传统人驾车行为,为解决新型混合交通带来的新问题提供一定的理论指导和借鉴.     

Cooperative vehicle path generation during merging using model predictive control with real-time optimization

This paper proposed a cooperative merging path generation method for vehicles to merge smoothly on the motorway using a Model Predictive Control (MPC) scheme which optimizes the motions of the relevant vehicles simultaneously. The cooperative merging is a merging in where the most relevant vehicle in the main lane would accelerate or decelerate slightly to let the merging vehicle merge in easily. The proposed path generation algorithm can generate the merging path ensuring the merging vehicle can access the whole acceleration area, and do not exceed it. We have introduced a state variable to the optimization problem by which the merging point for the merging vehicle is optimized. The simulation results showed that the cooperative merging path can be successfully generated under some typical traffic situations without re-adjustment of the optimization parameters.     

Automatic intersection and traffic rule detection by mining motor-vehicle GPS trajectories

The generation of road networks from ubiquitous motor-vehicle GPS trajectories has recently gained wide interest. However, few attempts have been made to automatically extract road network properties such as intersections and traffic rules to facilitate the production of high-quality routable maps. For urban street networks, the vehicle trajectory logged by a GPS receiver tends to be straight on streets and curved at intersections although the local deviation exists due to vehicle paths deviating from road centrelines and GPS positioning errors. This paper uses large curved trajectories at traffic intersections and presents novel algorithms for automatically detecting road intersections and traffic rules. Two inherent issues related to GPS trajectories have been resolved using the proposed approach. First, the serious fluctuations of vehicle trajectories due to multipath reflectivity from high-rise buildings have been eliminated, thereby enabling the effective detection of real curved trajectories occurring at traffic intersections. Second, the heterogeneity of traffic density has been considered when using the curved trajectories to automatically detect road intersections. The proposed algorithm was implemented using open-source software libraries and tested using large taxi trajectories collected in Suzhou City, China. A total of 285 at-grade intersections were detected automatically, and dynamic traffic rules were elucidated for each intersection. Compared with the manually interpreted results, the detection results were high quality and provided detailed information for the construction of a routable map.