新型三桩式防撞设施的数值模拟分析

针对目前通航河道上船舶撞桥事故频发,而桥梁往往缺乏有效防撞设施的现状,提出新型三桩式桥梁防撞设施的设计方案.三桩式桥梁防撞设施具有占地少、造价低和吸能效果明显等优点,能够满足运河桥墩防撞的要求.根据船舶与桥梁碰撞的相关理论,采用ANSYS/LS-DYNA非线性有限元软件模拟船舶与三桩式防撞设施的碰撞作用,深入分析和评估...     

城市商业广场地下停车场交通设计若干理念

通过调查,分析了大型商业广场地下停车场的主要特征与使用特点.结合实例,从商业广场地下停车场内外部交通组织、车库内部分区、出口引导标识和人性化交通设施设计等方面出发,论述了大型商业广场地下停车场交通设计的若干理念与具体实现形式,为城市大型商业建筑地下停车场交通设计提供了必要的理念支撑.     

考虑路段失效的军事物流配送中心选址模型

针对战场保障网络常常遭受敌人打击的现象,建立了考虑路段失效的军事配送中心可靠选址模型.模型为双层规划形式,上层规划的目标是优化系统在无路段失效和出现路段失效时所覆盖的总的需求量,下层规划的目标是最小化某一路段失效时系统覆盖的需求量.采用启发式算法求解下层规划,运用遗传算法求解整个模型.通过一个算例验证模型的优越性和算法的有效性.算例结果表明,尽管模型所得选址方案在无路段失效时覆盖的需求量,小于不考虑路段失效的最大覆盖模型选址方案覆盖的需求量,但在最佳路段失效时模型选址方案的覆盖效果优于后者.     

基于混合A*和可变半径RS曲线的自动泊车路径优化方法

路径规划是自动泊车系统的重要组成部分,是确保泊车运动安全、缩短行车距离、提高乘坐舒适性的关键。而当前自动泊车规划系统往往面临行驶空间狭小、障碍物多、路径搜索难度大等技术挑战,同时搜索曲线半径固定容易导致路径接点处曲率不连续,增大了路径跟随控制难度和轮胎磨损程度,这些都提升了泊车路径规划的研究难度。针对以上问题,设计可变半径的Reeds-Shepp曲线,提出基于混合A^*和该曲线的自动泊车路径规划方法,通过调整曲线半径,提升其在复杂场景下路径的搜索能力和灵活性。随后,设计基于分段贝塞尔曲线和梯度下降的路径优化方法,利用其多阶导数连续的优势优化已搜索的路径曲率,并采用梯度下降来保证路径曲率大小和对障碍的规避,解决直线与圆弧相接等位置曲率变化不连续的难题。结合路径搜索与路径优化的泊车规划方法能够切实满足复杂场景下的泊车需要。最后,基于团队自主研发的PanoSim虚拟系统与MATLAB搭建联合仿真环境,针对多种自动泊车工况测试验证提出的方法。研究结果表明：调整Reeds-Shepp曲线的搜索半径进行全局路径搜索,可获得更短和更易跟随的路径,具有良好的灵活性;基于贝塞尔曲线和梯度下降法的路径优化可有效消除曲率突变点、约束路径曲率并保证对障碍的无碰撞要求。     

高速公路改扩建作业区交通安全设施设置研究

根据高速公路改扩建施工区的交通特性及驾驶人的反应特征,将施工作业区划分为7个分段,构建驾驶人视认模型,并对各个分段安全设施进行设置,可保障高速公路施工作业区的安全与通畅,这已被郑洛高速公路所证实。     

旅游城市高铁站站前广场综合交通改善设计——以黄山北站为例

在全国高铁网络逐步构成的背景下,旅游城市高铁站站前广场在高铁运营后逐渐显现出了设施配套不足、交通组织混乱等问题.以黄山北站为例,通过分析黄山北站客流特征、站前广场交通设施现状、交通组织及运行,对黄山北站客流进行了预测,对交通设施规模进行了测算.根据预测结果,提出了交通改善策略,并从设施布局、交通组织等方面提出了近期和远期的具体交通改善方案.     

基于智能体模拟的浮动式停车价格实施效果研究

在城市机动车保有量快速增长的背景下，制定合理的停车价格对缓解停车难问题具有重要的作用. 基于多智能体的建模方法，结合典型城市商业区停车调查数据搭建仿真环境，通过编程实现停车过程中的行为决策规则，建立浮动式停车价格下的路内停车模拟平台，并对浮动式停车价格的实施效果进行研究. 模拟结果表明，浮动式停车价格策略的实施不仅使路内停车资源的利用更为均衡，区域内车位紧张状况有所缓解，停车寻泊时间有所减少，还提高了周边道路上车辆运行速度. 本研究可以为提高停车效率、缓解区域道路交通拥堵提供一定决策建议.     

公路路基排水设施及其施工方法研究

工程实践表明，积水是影响公路使用寿命的重要因素。鉴于此，依据新疆地区特殊的地质条件，提出适合该地区的公路路基排水技术，并探讨排水设施的施工方法，可为新疆地区相关工程项目提供参考与借鉴。     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.