考虑驾驶员行为偏好的车辆最优路径选择的G1-TOPSIS法

以前的车辆最优路径选择大多是考虑路程最短或时间最少.然而在实际的情形往往是伴随着驾驶员不同的行为偏好.充分考虑了驾驶员在路径选择中的不同要求,将G1法引入到驾驶员路径选择影响因素的权重确定,同时发展出基于G1-TOPSIS法车辆最优路径方法,并通过应用例子说明了方法的有效性和实用性.     

基于最优路径的诱导泊车系统

设计一种基于最优路径的停车场诱导泊车系统,一方面利用改进的Dijkstra算法对停车场路径进行推算研究得出最优路径;另一方面则是结合蓝牙、单片机、语音电路等技术,在对车位进行检测的前提下,向驾驶员提供诱导泊车服务,提高用户进入停车场内部的停车效率。整个系统为用户提供方便的同时也提高了经济效益,进一步实现停车智能化、合理化。     

浅析高速公路监控系统

高速公路监控系统对高速公路交通流状态和交通环境进行监测,并根据需要对交通流进行诱导和控制,保证车辆运行畅通、减少交通事故、降低事故的危害性。摘要:高速公路监控系统对高速公路交通流状和交通环境进行监测,并根据需要对交通流进行诱和控制,保证车辆运行畅通、减少交通事故、降低事的危害性。     

瞬时动态用户最优问题的统一模型及算法研究

本文建立了瞬时动态用户最优(IDUO)配流问题的变分不等式(VI)模型。该模型满足Wordrop第一原理要求,使得乘客在任意决策节点都选择当时交通条件下到达讫点的最短路径。所给算法在每一个小时段都能给出路段流入率、流出率及路段流量,对行人进行诱导。     

21世纪交通管理新技术——智能交通系统（下）

4 其它国家的智能交通系统 4.1 日本的通用交通控制系统(UTMS) 日本的通用交通控制系统(UTMS)是由日本国家警察署(NPA)于1993年4月发起建立的新型交通管理系统,计划到2001年以后才能完成。系统的中心目标是在车辆和交通控制中心之间通过使用红外线信号标杆,实现交互式双向通信。系统的最终目标是实现交通的主动控制管理,即将交通控制管理中心对交通需求和交通流的控制管理措施准确无误地传输给驾驶员,引导驾驶员在行车中避开交通     

北京交通预测预报系统投入使用

近日，北京市交通指挥中心的“交通预测预报”系统已经投入使用。这套系统能根据遍布全市各条主要道路上的交通流采集设备采集到的数据，通过几种数学模型运算，对道路未来趋势进行准确预报。据悉，以前发布路况信息，最主要的“瓶颈”是存在交通流检测技术和通讯技术的限制，采集各条主要道路上的交通流数据成本很高，经过科研人员多年的努力，现在这些技术难题都已经陆续得到解决。     

下行MU-MIMO系统能效与频谱效率折中效用分析

针对下行多用户多输入多输出(Multi-User Multiple-Input Multiple-Output,MU-MIMO)系统,建立了能够表达能量效率(energy-efficient,EE)与频谱效率(spectrum-efficiency,SE)折中关系的系统效用函数。由于该效用函数为非凸函数,为了获得最优的系统效用,提出了一种迭代用户功率分配算法。然后,给出了能够实现系统效用最大的传输模式选择方法。仿真结果表明,所提算法能够使得系统效用取得最大值。同时,还证明了在不同的效用偏好参数下,所提方案均可以获得最优系统效用。     

蚁群算法在城市交通导航系统的应用

本文基于蚁群算法模拟城市交通导航系统,对于解决城市交通拥堵问题给出了一些帮助。根据城市交通结构图,结合蚁群算法,有效解决了城市行驶车辆最优路径问题,并建立了智能导航系统。该导航系统利用蚁群算法不仅可以找到车辆行驶的较短路径,还可以帮助车辆选择车流量少的路线。模拟结果表明,该系统可以在较短的时间内,给用户指定最优路径,具有较好的导航效果。     

停车诱导显示屏交叉口前置距离计算方法

阐述了停车诱导系统在缓解大城市CBD地区交通拥堵状况的重要作用。指出确定停车诱导显示屏交叉口前置距离具有重要意义。在对驾驶员对于诱导屏上诱导信息的反应行为的研究基础上,重点对停车诱导系统诱导显示屏在不同车速路段的交叉口前置距离进行了详细的计算分析,并给出了不同车速路段下的推荐值。     

酒店一卡通系统介绍

1概述根据酒店项目对一卡通系统的要求,可以分为以下几个部分:(1)酒店门锁系统:采用感应卡酒店门锁管理。门锁的选择可以根据实际酒店定位及投资情况综合考虑,采用的感应卡门锁,具有较多的功能扩展空间。     

城市公园中慢行系统的选线与设计研究

城市公园作为城市中自然景观的重要组成部分,发挥着为人们提供散步漫游、休憩交往场所的重要作用,其内部慢行系统的研究对提升城市公园整体景观品质和游览体验有着重要的意义。以城市公园慢行系统为研究对象,通过实地调研和理论研究相结合的方法,从选线和设计两大方面探讨了城市公园慢行系统的构建。最后以黄山市滨江游园慢行系统为例,对其内部慢行系统的选线规划、景观规划和细节设计进行了具体的规划和设计,对理论研究结果进行验证和反馈,以期为同类型项目提供指导和借鉴。     

Graph‐Based Modeling of Information Flow Evolution and Propagation under V2V Communications‐Based Advanced Traveler Information Systems

A vehicle equipped with a vehicle‐to‐vehicle (V2V) communications capability can continuously update its knowledge on traffic conditions using its own experience and anonymously obtained travel experience data from other such equipped vehicles without any central coordination. In such a V2V communications‐based advanced traveler information system (ATIS), the dynamics of traffic flow and intervehicle communication lead to the time‐dependent vehicle knowledge on the traffic network conditions. In this context, this study proposes a graph‐based multilayer network framework to model the V2V‐based ATIS as a complex system which is composed of three coupled network layers: a physical traffic flow network, and virtual intervehicle communication and information flow networks. To determine the occurrence of V2V communication, the intervehicle communication layer is first constructed using the time‐dependent locations of vehicles in the traffic flow layer and intervehicle communication‐related constraints. Then an information flow network is constructed based on events in the traffic and intervehicle communication networks. The graph structure of this information flow network enables the efficient tracking of the time‐dependent vehicle knowledge of the traffic network conditions using a simple graph‐based reverse search algorithm and the storage of the information flow network as a single graph database. Further, the proposed framework provides a retrospective modeling capability to articulate explicitly how information flow evolves and propagates. These capabilities are critical to develop strategies for the rapid flow of useful information and traffic routing to enhance network performance. It also serves as a basic building block for the design of V2V‐based route guidance strategies to manage traffic conditions in congested networks. Synthetic experiments are used to compare the graph‐based approach to a simulation‐based approach, and illustrate both memory usage and computational time efficiencies.     

An optimal model for tunnel lighting control systems

We present a tunnel lighting optimal control model in considering traffic safety and energy-saving problems. Firstly, the demand brightness function with relation to tunnel exterior brightness, traffic flow and speed is described. Then an actual tunnel brightness curve is derived according to lamp equipment layouts and lamp properties in tunnels. Further, a simple method is used to determine an average brightness indicator in tunnels. We present a nonlinear optimal control tunnel lighting model in meeting the demand brightness, total average brightness and minimum dimming ratio constraints and so on. Finally, the simulation results at the JiangBeiLing tunnel of Wenzhou city in China show the optimal control system can meet the demand brightness and total average brightness constraints, and have a notable energy-saving effect.     

Information,rational expectations and network equilibria — an analytical perspective for route guidance systems

This paper tries to provide with a unified framework for understanding how drivers act in response to exogenously provided route guidance information; and how they form subjective expectations on traffic conditions from repeated learning. The learning problems are placed in the context of iterative adjustment processes which achieve equilibrium if drivers have rational expectations. Route choice models with rational expectations find a new justification since the models appear as the limits of drivers' learning procedures. This paper is also devoted to the question of whether route guidance information can convey substantial information to drivers even if drivers behave with rational expectations of their environment. The author also tries to propose a framework for designing the optimal route guidance systems.This paper was presented in draft form at an International Workshop on Trade, Knowledge and the Network Economy, held in December 1992 at Mallacoota, Australia.     

Bi-level Programming Formulation and Heuristic Solution Approach for Dynamic Traffic Signal Optimization

Abstract:   Although dynamic traffic control and traffic assignment are intimately connected in the framework of Intelligent Transportation Systems (ITS), they have been developed independent of one another by most existing research. Conventional methods of signal timing optimization assume given traffic flow pattern, whereas traffic assignment is performed with the assumption of fixed signal timing. This study develops a bi-level programming formulation and heuristic solution approach (HSA) for dynamic traffic signal optimization in networks with time-dependent demand and stochastic route choice. In the bi-level programming model, the upper level problem represents the decision-making behavior (signal control) of the system manager, while the user travel behavior is represented at the lower level. The HSA consists of a Genetic Algorithm (GA) and a Cell Transmission Simulation (CTS) based Incremental Logit Assignment (ILA) procedure. GA is used to seek the upper level signal control variables. ILA is developed to find user optimal flow pattern at the lower level, and CTS is implemented to propagate traffic and collect real-time traffic information. The performance of the HSA is investigated in numerical applications in a sample network. These applications compare the efficiency and quality of the global optima achieved by Elitist GA and Micro GA. Furthermore, the impact of different frequencies of updating information and different population sizes of GA on system performance is analyzed.     

Simulation studies of traffic management strategies for a long tunnel

The Hsueh-Shan Tunnel, the fifth long tunnel in the world, has a total distance of 12.9 km. After the opening of the tunnel, traffic demand between Taipei and I-Lan increased dramatically. However, efficient traffic management strategies for the Hsueh-Shan Tunnel need to be developed and evaluated accordingly in order to alleviate traffic congestion due to high demand and/or possible incidents. The research aims to evaluate possible traffic management strategies based on available control devices through simulation-assignment techniques. Possible traffic management strategies, including access control (ramp metering), lane control and route guidance, are proposed and examined through numerical experiments. In order to analyze traffic management strategies based on simulation, DynaTAIWAN, a simulation-assignment model, is developed to simulate traffic control strategies and reflect driver’s response to route guidance. Several indexes, including vehicle queue length, average density and average speed, are used in the comparisons. The results show that ramp control provides the best benefits compared to other strategies and can reduce the average queue length by about 18%.     

数码涡旋机组在孝感市道路交通管理指挥中心大楼的设计应用

孝感市道路交通管理指挥中心大楼于2006年7月进行空调设计。2008年1月正式投入使用。设计选用美国麦克维尔数码多联机系统,夏季制冷,冬季供暖。空调主机选用谷轮数码变容涡旋压缩机。与常规中央空调系统相比,具有明显的节能优势。     

Short‐Term Traffic Speed Prediction for an Urban Corridor

Short‐term traffic speed prediction is one of the most critical components of an intelligent transportation system (ITS). The accurate and real‐time prediction of traffic speeds can support travellers’ route choices and traffic guidance/control. In this article, a support vector machine model (single‐step prediction model) composed of spatial and temporal parameters is proposed. Furthermore, a short‐term traffic speed prediction model is developed based on the single‐step prediction model. To test the accuracy of the proposed short‐term traffic speed prediction model, its application is illustrated using GPS data from taxis in Foshan city, China. The results indicate that the error of the short‐term traffic speed prediction varies from 3.31% to 15.35%. The support vector machine model with spatial‐temporal parameters exhibits good performance compared with an artificial neural network, a k‐nearest neighbor model, a historical data‐based model, and a moving average data‐based model.     

建筑火灾中基于人群行为特征的智能疏散诱导

提出人员逃生从众度、疏散路径选择度等基本概念,通过建立“黑屋”实验平台,用多组人群进行多次疏散实验,研究人群疏散行为参数对疏散时间的影响。把建筑结构参数、火灾中的烟气、温度等参变量通过数据融合处理形成统一的知识表征。用人群密度、人员逃生从众度、疏散路径选择度等参数来表征火灾中人群的行为特征。首次构建智能疏散诱导的机理模型,形成基于人群特征的智能疏散诱导系统。通过智能疏散诱导系统对疏散指示灯的PWM控制,实现疏散路径的动态调整与优化,给出人群疏散的动态标识路径。实验结果表明该系统能够缩短疏散时间,提高疏散效率。     

道路平面交叉口次路远引几何参数设置及通行效率研究

次要车流的左转和直行对交叉口车辆运行影响较大,特别是主路交通流量较大时尤为明显,通过次要道路车流远引的方式可以减少交叉口车辆冲突,有利于提高交叉口运行效率。分析了平面交叉口次路远引适用条件与车流组织方法,以延误最小为目标,构建了远引回转车流掉头位置、远引车辆掉头排队车道长度、远引掉头处开口长度与宽度等关键几何参数计算模型,提出了次路远引交叉口延误和通行能力等计算方法。结合实例验证了上述方法的可行性,仿真显示,在一定条件下平面交叉口次路远引可有效减少信号相位数和车辆平均延误,表明了平面交叉口次路远引的交通组织方法对优化城市道路交叉口设计有较好的应用价值。