中心城区路网优化策略研究 ——以沧州市为例

为解决中心城区道路拥堵问题,分析了城区交通拥堵形成的主要原因,并基于此提出中心城区路网优化策略。以沧州市中心城区为例,详细阐述了其路网优化设计的基本思路和路网布局,最终得出沧州市中心城区路网优化设计方案。     

武汉光谷国际网球中心与三环线衔接匝道研究

介绍了武汉市三环线武黄立交新增匝道的设计思路、方案调整及匝道车道数研究。通过分析新增匝道建设的主要受控因素,提出了三环线到达及驶离网球中心停车场不同路径的匝道方案,并从多方面对匝道方案进行综合比选。     

浅谈市政工程中小桥设计问题

随着我国城市化建设的快速发展,越来越多的城市高架桥梁、轨道交通、下穿隧道等市政交通项目应运而生,而这些新增交通项目与现状地面道路、河道以及市政管线等构筑物的空间冲突,导致城市中小桥梁建设的形式也越来越丰富。如何合理地解决市政工程中小桥设计中遇到的问题,结合工程设计实例提了几点相应的解决思路。从造价、经济、使用管养安全等角度,确定合适的管线过桥组合方案;对于处于平面交叉口处的变宽桥梁,应综合考虑美观、经济、实施简单等方面确定最合理的设计方案;与地下工程有关联的市政工程中小桥需沟通多部门,进行多方面的充分论证。     

综合交通枢纽车道边交通组织方式研究

针对现代综合交通枢纽车道边的交通组织方式进行研究,结合车站的整体建筑布局、周边路网、交通量等提出了简单、实用和高效的交通组织方式。     

大型活动的交通调查及分析

随着我国经济的不断发展,全国各地举行的大型活动越来越多。大型活动产生突增交通量造成周边地区的交通拥挤,而分析大型活动带来的交通拥挤则是以对大型活动的交通调查为基础的。以长春市南岭体育场周围的道路交通系统为基础,对举行足球比赛产生的观众到达高峰和离开高峰进行了实地调查,并通过问卷的方式对观众出行方式及其他与此活动相关的特性进行了分析。     

Multiple criteria optimization method for the vehicle assignment problem in a bus transportation company

A vehicle assignment problem (VAP) in a road, long‐haul, passenger transportation company with heterogeneous fleet of buses is considered in the paper. The mathematical model of the VAP is formulated in terms of multiobjective, combinatorial optimization. It has a strategic, long‐term character and takes into account four criteria that represent interests of both passengers and the company's management. The decision consists in the definition of weekly operating frequency (number of rides per week) of buses on international routes between Polish and Western European cities. The VAP is solved in a step‐wise procedure. In the first step a sample of efficient (Pareto‐optimal) solutions is generated using an original metaheuristic method called Pareto Memetic Algorithm (PMA). In the second step this sample is reviewed and evaluated by the Decision Maker (DM). In this phase an interactive, multiple criteria analysis method with graphical facilities, called Light Beam Search (LBS), is applied. The method helps the DM to define his/her preferences, direct the search process and select the most satisfactory solution.     

Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.