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。     

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.     

Recursive estimation of average vehicle time headway using single inductive loop detector data

Vehicle time headway is an important traffic parameter. It affects roadway safety, capacity, and level of service. Single inductive loop detectors are widely deployed in road networks, supplying a wealth of information on the current status of traffic flow. In this paper, we perform Bayesian analysis to online estimate average vehicle time headway using the data collected from a single inductive loop detector. We consider three different scenarios, i.e. light, congested, and disturbed traffic conditions, and have developed a set of unified recursive estimation equations that can be applied to all three scenarios. The computational overhead of updating the estimate is kept to a minimum. The developed recursive method provides an efficient way for the online monitoring of roadway safety and level of service. The method is illustrated using a simulation study and real traffic data.     

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.     

城市交通系统通行性影响因素及计算理论

文章分析了震后城市交通系统通行性的影响因素,提出了包含路段单元通行概率、路段连通概率及路网连通概率的城市交通系统通行性计算理论,为城市路网的连通可靠性评价提供参考。     

驾驶人安全意识体验式训练装置研究

通过对目前常用驾驶人安全意识培训方法的对比,认为体验式培训为最适合的培训方法;进一步对我国2007-2010年间大型道路交通事故特征进行分析,得出驾乘人员不系安全带是引起人员伤亡一大原因。通过设计研发碰撞、翻转两个体验式训练装置,使驾乘人员在保证安全的前提下真切感受道路交通事故发生瞬间安全带对人体的保护作用,有效提高驾驶人的安全意识,减少道路交通事故的发生及人员的伤亡。     

地下交通转换平台射流通风特性及风流组织方式研究

为探究地下交通转换平台内通风系统的合理布局,采用比尺模型试验和CFD模拟相结合的方法,研究射流风机和通风组织对地下交通转换平台内气流运动的影响。结果表明： 1）当联络通道内风机射流朝向敞开段时,为使风机升压系数Kj最大,630 mm、900 mm、1 120 mm射流风机的布设位置应距离敞开段分别大于40、50、65 m; 2）大口径射流风机具有更大的Kj,但占用的断面空间更大,且射流诱导段更长,应根据联络通道长度和高度合理选择射流风机口径; 3）地下交通转换平台的通风组织不宜采用同侧开启方式,采用对角抽吸方式时,联络通道内的污染物混入比最低、通风效率最高。