考虑局部排队延误的VMS 选址双层规划模型

用Monte Carlo 模拟技术刻画路网状态的随机性,优先考虑在交通网络瓶颈路段设置可变信息板待选点,建立多目标优化可变信息板选址双层规划模型.上层模型为基于不确定风险决策最小和诱导效益最大的双目标规划模型,下层模型为考虑局部网络有排队延迟现象的随机用户平衡模型.采用增广Lagrange 对偶算法与相继平均算法组合求解下层模型,采用非劣排序遗传算法-II 求解整个双层规划模型.算例结果表明,在可变信息板资金预算约束下,非劣排序遗传算法-II 能够有效求解可变信息板选址的多目标优化问题,得到6 组Pareto 解.研究结果可为城市道路网可变信息板诱导配置的优化和建设提供决策支持.     

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地铁站台客流的顺利出站与换乘导向标识提供的有效引导服务关系密切.本文对地铁站台导向标识系统的布局优化方法进行了研究.首先根据导向标识的服务特点,提出了基于信息熵理论的标识引导服务效能的计算方法,考虑到乘客与导向标识的交互特点,以分段概率函数的形式表达乘客接受引导服务的过程;其次以导向标识协同服务效能最大为目标,建立了导向标识布局优化模型,证明简化后的模型是基于协同覆盖的选址模型,并设计启发式算法对模型求解.最后将该模型应用于站台出站导向标识布局优化中,优化后标识服务效能增加32.5%,引导范围增加39.16%.计算结果证明,该模型有效提升了导向标识系统的服务效能,可以为更多乘客提供引导服务.     

无人潜器光学引导回收技术的仿真研究

该文介绍了无人潜器UUV(UnmannedUnderwaterVehicle)光学引导回收技术方面最新的研究结果 ,提出了回收过程的光学引导系统的模型 ,给出了不同光源配置条件下的光学引导系统仿真结果及其精确性和可靠性。这些仿真结果也可以帮助建立一个光学引导和控制模式。     

基于扩张状态观测器的双桨推进无人艇抗干扰目标跟踪控制

[目的]针对无人艇(USV)的模型不确定性和未知海洋环境扰动,提出一种基于扩张状态观测器(ESO)的双桨推进无人艇抗干扰目标跟踪控制算法.[方法]在运动学层级,设计基于平行接近制导原理的目标跟踪制导律;在动力学层级,针对模型不确定性和未知环境扰动,设计基于ESO的纵荡速度和艏摇角速度自抗扰控制律,以减小模型不确定性和环...     

城市停车选择行为研究综述

回顾近20 年停车选择行为的既有研究成果,从研究方法、影响因素两方面总结了国内外的 研究现状及存在的问题。指出既有研究方法多采用非集计模型建模,忽视了该模型“完全理性 人”假设的缺陷和不足;影响因素主要关注停车收费、停车便利性对停车选择行为的影响,针对 违章停车的惩罚因素缺乏深入的量化分析;在智能交通飞速发展的背景下,基于停车诱导信息系 统的停车选择影响因素研究依然停留在排队车辆总数、总行程时间等宏观因素,较少关注融入停 车者主观偏好的微观因素;研究区域多集中在中心商业区,而对于具有刚性停车需求且停车资源 匮乏的居住区的停车选择行为研究不足。最后提出了停车选择行为的研究趋势和方向,旨在为城 市静态交通的规划及管理提供新的思路和方法。     

城市交通控制与诱导系统协同的信息分析

交通信号控制和动态交通诱导是城市交通管理的两个主要手段，2者协同运作能提高城市交通管理效率。多源交通信息处理是交通控制与交通诱导实现协同的基础和关键。文章分析了交通控制与动态诱导系统的信息需求特点，对交通控制与交通诱导系统协同运作的数据处理与信息融合进行了研究。     

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目前，停车困难已经成为城市商业中心区的突出问题，本文以工作实践为基础，对北京市商业中心区停车问题进行了初步的研究分析，在充分吸取国内外先进技术和经验的基础上，给出了停车诱导系统的总体结构，LED 可变信息情报板的规划设置以及系统信息提供注意事项，提出了停车诱导管理的设计与控制方法，并结合北京市王府井和西单地区停车诱导管理系统实际建设应用，表明应用效果明显.     

两种激光制导干扰技术仿真研究

介绍了漫反射假目标有源干扰技术和转移式光纤无源干扰技术两种不同激光制导干扰技术的组成和工作原理,对比分析这两种激光制导干扰技术的技术指标。得出两种不同干扰技术的优缺点,为对激光制导武器实施更为有效的干扰提供了理论依据。     

A route guidance system considering travel time unreliability

Under a stochastic roadway, drivers need a route guidance system incorporating travel time variability. To recommend a customized path depending on the trip purpose and the driver’s risk-taking behavior, various path ranking methods have been developed. Unlike those methods, our proposed disutility method can easily incorporate a target arrival time in the ranking process by measuring how late the travel is and by penalizing it depending on the severity of lateness. In addition, the disutility-based route guidance system can properly address travel time unreliability that causes unacceptable disruptions to the driver’s schedule (i.e., unexpected long delay). We compare the disutility-based path ranking method with other ranking methods, the percentile travel time, the mean excess travel time, and the on-time arrival probability. We show that the disutility has stronger discriminating power and requires less solution space to find an optimal path. The most important advantage is that it can estimate a driver’s risk-taking behavior for each trip purpose by using the discrete choice analysis. We construct a simulation framework to acquire the travel time data on a hypothetical roadway. We analyze the data and show how various ranking methods recommend a customized path. Using the data, we show the advantage of the disutiltiy method over the other methods, which is generating a customized path with respect to the target arrival time by properly penalizing the travel time lateness.     

Behavior-consistent real-time traffic routing under information provision

The problem addressed here involves a controller seeking to enhance traffic network performance via real-time routing information provision to drivers while explicitly accounting for drivers’ likely reactions towards the information. A fuzzy control modeling approach is used to determine the associated behavior-consistent information-based network control strategies. Experiments are performed to compare the effectiveness of the behavior-consistent approach with traditional dynamic traffic assignment based approaches for deployment. The results show the importance of incorporating driver behavior realistically in the determination of the information strategies. Significant differences in terms of system travel time savings and compliance to the information strategies can be obtained when the behavior-consistent approach is compared to the traditional approaches. The behavior-consistent approach can provide more robust performance compared to the standard user or system optimal information strategies. Subject to a meaningful estimation of driver behavior, it can ensure system performance improvement. By contrast, approaches that do not seek to simultaneously achieve the objectives of the drivers and the controller can potentially deteriorate system performance because the controller may over-recommend or under-recommend some routes, or recommend routes that are not considered by the drivers.