Modeling and analysis of mixed flow of cars and powered two wheelers

In modern cities, a rapid increase of motorcycles and other types of Powered Two-Wheelers (PTWs) is observed as an answer to long commuting in traffic jams and complex urban navigation. Such increasing penetration rate of PTWs creates mixed traffic flow conditions with unique characteristics that are not well understood at present. Our objective is to develop an analytical traffic flow model that reflects the mutual impacts of PTWs and Cars. Unlike cars, PTWs filter between cars, have unique dynamics, and do not respect lane discipline, therefore requiring a different modeling approach than traditional “Passenger Car Equivalent” or “Follow the Leader”. Instead, this work follows an approach that models the flow of PTWs similarly to a fluid in a porous medium, where PTWs “percolate” between cars depending on the gap between them.Our contributions are as follows: (I) a characterization of the distribution of the spacing between vehicles by the densities of PTWs and cars; (II) a definition of the equilibrium speed of each class as a function of the densities of PTWs and cars; (III) a mathematical analysis of the model’s properties (IV) an impact analysis of the gradual penetration of PTWs on cars and on heterogeneous traffic flow characteristics.The proposed model could contribute as an enabler for ‘PTW-aware’ future Cooperative Intelligent Transport Systems technologies and traffic regulations.     

Accurate and cost-effective traffic information acquisition using adaptive sampling: Centralized and V2V schemes

The new generation of GPS-based tolling systems allow for a much higher degree of road sensing than has been available up to now. We propose an adaptive sampling scheme to collect accurate real-time traffic information from large-scale implementations of on-board GPS-based devices over a road network. The goal of the system is to minimize the transmission costs over all vehicles while satisfying requirements in the accuracy and timeliness of the traffic information obtained. The system is designed to make use of cellular communication as well as leveraging additional technologies such as roadside units equipped with WiFi and vehicle-to-vehicle (V2V) dedicated short-range communications (DSRC). As opposed to fixed sampling schemes, which transmit at regular intervals, the sampling policy we propose is adaptive to the road network and the importance of the links that the vehicle traverses. Since cellular communications are costly, in the basic centralized scheme, the vehicle is not aware of the road conditions on the network. We extend the scheme to handle non-cellular communications via roadside units and vehicle-to-vehicle (V2V) communication. Under a general traffic model, we prove that our scheme always outperforms the baseline scheme in terms of transmission cost while satisfying accuracy and real-time requirements. Our analytical results are further supported via simulations based on actual road networks for both the centralized and V2V settings.     

北京局集团公司“三港三区域三品类”货运增量对策

在“公转铁”机遇带动下,北京局集团公司将货运增量重点由煤炭转向“三港三品类”,进行运力资源倾斜。分析“三港三区域三品类”货运量、装车卸车,从运输价格、运距结构、运力匹配、装卸车组织、环保政策、路企双方设备能力等方面分析货运增量影响因素,提出“三港三区域三品类”货运增量对策,即:增强货运市场营销策略积极参与市场竞争、加强运输组织释放“三港、三区域”运能、调整作业方案实现效率提升、依托“公转铁”政策支持优化运输结构、落实专用线扩能改造助力货运上量,提升“三港三区域三品类”市场竞争力,满足货运增量需求,实现北京局集团公司货运量持续增长。     

行人交通信息采集方法分析

从行人的交通特性出发,分别介绍人工采集法、视频采集法、GPS采集法和无线定位采集法等行人交通信息采集方法。详细分析无线定位采集法在行人交通信息采集中的运用,对研究行人交通具有重要意义。     

交通运输非法营运形成机理及整治路径研究——以深圳为例

非法营运严重影响交通运输市场的正常运营秩序,其治理必须在分析形成机理的基础上,探寻合适的整治路径。文章以深圳为例,阐释了非法营运市场的从业人员构成、营运车辆、服务对象及区域分布状况,并从社会性质和运营组织两方面总结其市场特征,采用系统分析方法从社会根源、体制根源、供需根源、利益根源和整治根源五个方面探寻其形成机理,最后建议遵循“疏堵并举、多管齐下”的原则制定治理路径。     

浅谈高速公路道路交通标线施工工艺

介绍了高速公路道路交通标线的施工工艺及验收检查项目。     

城市轨道交通视频监控系统中的故障分析

视频监控系统是轨道交通建设与运营管理中非常重要的组成部分.为提高地铁运营管理水平和地铁治安水平,保障乘客安全,地铁运营正常,我们要保障视频监控系统的正常运行,排除故障,解决问题.在此简要介绍几种在城市轨道交通视频监控系统的建设和运行中的常见问题.     

RFID技术在公交优先中的应用

在城市道路交通拥堵日益严重的今天,公共交通的发展受到各大中城市的高度重视.发展公交,除了增加公交车数量,修筑公交专用道外,如何提高公交的服务质量,提高公交的运行效率至关重要,本文将结合RFID技术,就如何提高公交的运行效率进行探讨.     

短时交通流量预测在最优路径选择中的应用

针对短时交通流量在部队选择最优开进路线时的影响,本文对影响路径诱导的短时交通流量预测算法进行研究,运用基于灰色理论和马尔可夫链的组合预测算法,对某市一条主干道的短时交通流量进行了预测.结果表明,组合预测算法具有更好的预测精度,相对误差为8.768%.能够满足部队选择最优开进路线的时限要求.