Reliable sensor deployment for network traffic surveillance

New sensor technologies enable synthesis of disaggregated vehicle information from multiple locations. This paper proposes a reliable facility location model to optimize traffic surveillance benefit from synthesized sensor pairs (e.g., for travel time estimation) in addition to individual sensor flow coverage (e.g., for traffic volume statistics), while considering probabilistic sensor failures. Customized greedy and Lagrangian relaxation algorithms are proposed to solve this problem, and their performance is discussed. Numerical results show that the proposed algorithms solve the problem efficiently. We also discuss managerial insights on how optimal sensor deployment and surveillance benefits vary with surveillance objective and system parameters (such as sensor failure probabilities).     

Modeling capacity flexibility of transportation networks

Flexibility of the transportation system is one of the important performance measures needed to deal with demand changes. In this paper, we provide a quantitative assessment of capacity flexibility for the passenger transportation network using bi-level network capacity models. Two approaches for assessing the value of capacity flexibility are proposed. One approach is based on the concept of reserve capacity, which reflects the flexibility with respect to changes in terms of demand volume only. The second approach allows for variations in the demand pattern in addition to changes in demand volume in order to more fully capture demand changes. Two models are developed in the second approach to consider two types of capacity flexibility. The total capacity flexibility allows all users to have both route choice and destination choice when estimating capacity flexibility. The limited capacity flexibility estimates how much more demand volume could be added to a fixed demand pattern by allowing the additional demand to deviate from the fixed demand pattern. Numerical examples are provided to demonstrate the different concepts of capacity flexibility for a passenger transportation system under demand changes.     

不同类型交通需求管理实践与探索——以深圳市为例

交通需求管理是大城市交通政策的重要组成部分,提出了基于实施难易影响因素的交通需求管理措施分类,总结了深圳从20世纪90年代中期开始相继实施的一系列相对较易实施的交通需求管理措施情况,分析展望需进一步考虑的交通需求管理措施。针对交通拥挤收费这一较难及重大的需求管理措施,回顾了深圳探索性研究拥挤收费方案,包括交通拥挤收费总体调控目标、收费区域范围、收费模式与时段、收费系统技术选型等,分析了实施面临的困难,并提出了实施突破与替代的建议。     

公路平面交叉口安全评价指标及方法

为了快速地对公路平面交叉口安全状况进行评价,本文利用冲突指数、交叉口几何设计事故影响系数、安全设施事故影响系数建立了平面交叉口安全评价指标并分别给出了冲突指数、交叉口几何设计事故影响系数、安全设施事故影响系数的计算流程和方法。最后选取平面交叉口指标计算值和专家主观打分均值的相关性分析,对平面交叉口安全评价指标的有效性进...     

彩信技术在交通违法主动告知中的应用

由于目前的交通违法告知方法存在着信息不对称问题,导致车辆驾驶人不能实时获知自己的交通违法情况,故可能出现自身的重复性交通违法或由套牌车辆的交通违法而被高额罚款。为此,本文提出了一个基于GPRS MODEM通讯技术的彩信发布系统。作者采用C#.net开发了图像处理模块,对电子警察系统抓拍的违法原始图片进行切割并压缩,构成...     

互通式立交交织区段通行能力及服务水平分析

介绍了高速公路互通式立交匝道出入口与主线交织区段的通行能力及服务水平分析的基本方法,并以一处枢纽互通式立交内环匝道交织区段为例,进行了计算,经对计算结果的深入分析,得出了结论。     

平阳高速公路穿越东村小窑煤矿采空区设计

近年来山西省的高速公路穿越煤矿采空区和铝土矿采空区的工程很多,采空区的处治设计直接影响到高速公路的运营安全和使用寿命。结合工程实践,针对平阳高速公路煤矿采空区的特点,阐述穿越东村小窑煤矿采空区的三种处治设计方案,并对方案进行对比,可供同行参考。     

多孔管孔出流速度和流量影响因素数值仿真及试验

本文通过控制变量法进行工况设计,对多孔管进行数值模拟和试验对比,分别研究多孔管管径、管长、孔径、孔间距、水压五个变量对多孔管孔出流速及流量的影响。使用ANSYS软件中的DesignModeler模块进行几何建模,ICEM中的O-Block技术进行流体计算域网格划分,Fluent软件进行求解。研究发现,多孔管管内径和管长的增加均使孔出流速和出流量减小,管长度的增加会影响孔出流沿程的均匀性;孔径的增大使孔出流速明显减小,且影响孔出流沿程的均匀分布,出流量受孔径的影响较复杂,在孔径不超过2.5mm时可以认为出流量与孔径的平方成正比;孔间距的增大对孔出流速和沿程均匀分布基本无影响,而与出流量成正比。最后将数值模拟结果和试验进行对比,发现试验数据所反映的多孔管出流量与管内径、管长、孔径和孔间距的关系与数值模拟基本吻合,而试验中管的出流量普遍比数值模拟小。     

重载铁路调度集中系统的研究

分散自律调度集中系统是将列车运行调整计划下传到各个车站自律机中自主自动执行;在列车运行调整计划的基础上,解决列车作业与调车作业在时间与空间上的冲突,实现列车和调车作业的统一控制.在重裁铁路上实施调度集中要解决重载运输干线上高密度列车运行条件下列车进路的自动排列.并对调车作业和列车作业进行冲突检测和调整.给出了重载铁路分散自律调度集中系统的整体结构,详细研究了针对重载运输组织的系统功能和特点.对重载运输铁路调度集中具有借鉴和示范作用.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.