轨道交通乘客个性化出行路径规划算法

随着城市轨道交通网络的不断完善,可供乘客选择的轨道交通出行路径日益 增加,乘客出行路径决策愈加复杂.本文在分析轨道交通服务水平变量对不同属性乘客出 行路径选择行为影响的基础上,提出轨道交通乘客个性化出行路径规划算法.首先,基于 非集计理论构建针对不同类别乘客的路径选择模型,该模型综合考虑乘车时间、换乘时 间、换乘次数、车内拥挤度及个人属性等因素对乘客路径选择行为的影响.其次,基于不同 类别乘客的路径选择行为差异,构建考虑车内拥挤度变化的乘客个性化出行路径动态规 划算法,为不同属性乘客规划广义出行时间最小的路径.最后,基于广州地铁数据对算法 进行验证.结果表明,该算法针对乘客个人属性规划的最优出行路径,更加贴合乘客的出 行心理.     

基于旅游动机的旅游目的地选择行为分析

旅游目的地选择是游客出行决策的核心问题,本文对游客的目的地选择行为进 行了研究.本课题组选取北京市区8个景点,以在京旅游的游客作为研究对象,组织进行了 游客出行行为调查.问卷设计22 项旅游动机,通过对游客旅游动机项提取因子,并对旅游 动机的因子得分进行聚类分析把游客分为4 类.在构建游客旅游目的地选择行为模型时, 对首个目的地和非首个目的地分别建模.模型中引入了旅游动机类型变量,证明旅游动机 对游客目的地选择行为影响显著.另外出行距离在不同阶段对游客目的地选择的影响存 在显著的差异.该模型精度较高,为进一步研究旅游目的地选择行为提供了理论依据.     

血液酒精浓度对驾驶行为的影响研究

为了探讨饮酒对驾驶员驾驶行为的影响,以驾驶模拟器为平台,测试了13名驾驶人员在不同血液酒精浓度（0mg/dl,20mg/dl,50 mg/dl,80 mg/dl）、不同场景下加速、刹车情况并调查了其主观感受。进行数据分析后初步得到一些结论：饮酒（特别是在较高血液酒精浓度的情况下）确实会对驾驶行为产生影响并可能会导致某些危险驾驶行为;性别和驾驶经验也会对不同酒精浓度下的驾驶行为产生影响。     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。     

城市轨道交通车辆基地站场勘测内容和方法研究

车辆基地是城市轨道交通系统的重要组成部分,针对目前车辆基地勘测设计过程中普遍重设计轻勘测、缺乏系统的站场勘测内容与方法的现状,通过对行业、企业相关勘测规范的理解和归纳,结合自己勘测设计实践,系统论述车辆基地站场勘测内容和方法,主要包括车辆基地基线的测设和应用、地形测量、站场横断面测绘、专项调查与测绘等几方面,掌握车辆基地站场勘测内容和方法将为车辆基地设计与施工、节约用地、降低投资等方面发挥重要的作用。     

武汉市过长江交通流量特征分析

武汉市过长江交通是武汉市最主要的交通流向之一。根据流量观测数据分析长江交通流量特征,表明武汉市区过长江交通饱和,交通需求总量大,出行目的种类多。过长江交通没有明显、固定的高峰日和高峰小时,除通勤交通外。还有公务等大量非通勤交通。其中武昌与汉口之间交通是主流向,需要适当新增通道缓解过江难问题。     

基于神经网络的道路通行能力与交通需求匹配度判别研究

交通的供需是否匹配关系到城市和枢纽的发展前景。文中在探讨道路通行能力与需求匹配特性的基础上,用BP神经网络理论建立一种交通匹配预测模型。该模型发挥神经网络的优势,对数据并行处理和分布存储,通过训练、学习产生一个非线性映射,自适应地对数据进行预测。通过相关数据实验证明,该神经网络模型有较高的精度,并有较好的适用性。