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...     

公路平面交叉口交通安全养护评价体系及方法研究

从公路平面交叉口交通安全养护需求出发,对平面交叉口交通安全养护评价指标体系和方法进行了系统研究和分析,形成了完整的公路平面交叉口交通安全养护评价体系。基于路基路面、安全设施、管理设施、交叉口渠化、绿化五个方面建立了平面交叉口交通安全养护评价指标体系;提出了评价指标数据采集方法和标准;验证了数据采集的一致性;建立了平面交叉口安全养护评价模型;标定出了模型参数;并选取试验路口利用模型计算值和专家主观打分均值的相关性分析,对建立的模型有效性进行了验证。     

嵌入式系统在电子警察中的应用

介绍了智能综合电子警察自动监测系统的概念,针对目前市场对电子警察系统的要求,分析了基于windows平台开发电子警察的存在不足,对嵌入式一体化产品的特点和优势进行了简要的分析,拓展了嵌入式一体化产品在智能交通系统领域中的应用范围。     

城市高架公路新型声屏障研究

在分析城市交通噪声主要特征的基础上 ,探讨声屏障的声学设计、结构设计及强度设计方法 ,介绍城市高架公路新型声屏障的试验室测试结果和应用情况。测试和应用结果表明 ,这种新型声屏障是城市高架公路控制噪声的有效设施。     

A framework for travel time variability analysis using urban traffic incident data

This study aims to develop a framework to estimate travel time variability caused by traffic incidents using integrated traffic, road geometry, incident, and weather data. We develop a series of robust regression models based on the data from a stretch in California's highway system during a two-year period. The models estimate highway clearance time and percent changes in speed for both downstream and upstream sections of the incident bottleneck. The results indicate that highway shoulder and lane width factor adversely impact downstream highway clearance time. Next, travel time variability is estimated based on the proposed speed change models. The results of the split-sample validation show the effectiveness of the proposed models in estimating the travel time variability. Application of the model is examined using a micro-simulation, which demonstrates that equipping travelers with the estimated travel time variability in case of an incident can improve the total travel time by almost 60%. The contribution of this research is to bring several datasets together, which can be advantageous to Traffic Incident Management.     

Cost scaling based successive approximation algorithm for the traffic assignment problem

This paper presents a cost scaling based successive approximation algorithm, called ε-BA (ε-optimal bush algorithm), to solve the user equilibrium traffic assignment problem by successively refining ε-optimal flows. As ε reduces to zero, the user equilibrium solution is reached. The proposed method is a variant of bush-based algorithms, and also a variant of the min-mean cycle algorithm to solve the min-cost flow by successive approximation. In ε-BA, the restricted master problem, implying traffic equilibration restricted on a bush, is solved to ε-optimality by cost scaling before bush reconstruction. We show that ε-BA can reduce the number of flow operations substantially in contrast to Dial’s Algorithm B, as the former operates flows on a set of deliberately selected cycles whose mean values are sufficiently small. Further, the bushes can be constructed effectively even if the restricted master problem is not solved to a high level of convergence, by leveraging the ε-optimality condition. As a result, the algorithm can solve a highly precise solution with faster convergence on large-scale networks compared to our implementation of Dial’s Algorithm B.     

Did California’s hand-held cell phone ban reduce accidents?

On July 1st, 2008, California enacted a ban on hand-held cell phone use while driving. Using California Highway Patrol panel accident data for California freeways from January 1st, 2008 to December 31st, 2008, we examine whether this policy reduced the number of accidents on California highways. To control for unobserved time-varying effects that could be correlated with the ban, we use high-frequency data and a regression discontinuity design. We find no evidence that the ban on hand-held cell phone use led to a reduction in traffic accidents.     

Adapt-Traf: An adaptive multiagent road traffic management system based on hybrid ant-hierarchical fuzzy model

Usually, road networks are characterized by their great dynamics including different entities in interactions. This leads to more complex road traffic management. This paper proposes an adaptive multiagent system based on the ant colony behavior and the hierarchical fuzzy model. This system allows adjusting efficiently the road traffic according to the real-time changes in road networks by the integration of an adaptive vehicle route guidance system. The proposed system is implemented and simulated under a multiagent platform in order to discuss the improvement of the global road traffic quality in terms of time, fluidity and adaptivity.     

Is equilibrium in transport pure Nash,mixed or Stochastic?

The classical theory of transport equilibrium is based on the Wardrop’s first principle that describes a Nash User Equilibrium (UE), where in no driver can unilaterally change routes to improve his/her travel times. A growing number of economic laboratory experiments aiming at testing Nash-Wardrop equilibrium have shown that the Pure Strategy Nash Equilibrium (PSNE) is not able to explain the observed strategic choices well. In addition even though Mixed Strategy Nash Equilibrium (MSNE) has been found to fit better the observed aggregate choices, it does not explain the variance in choices well. This study analyses choices made by users in three different experiments involving strategic interactions in endogenous congestion to evaluate equilibrium prediction. We compare the predictions of the PSNE, MSNE and Stochastic User Equilibrium (SUE). In SUE, the observed variations in choices are assumed to be due to perception errors. The study proposes a method to iteratively estimate SUE models on choice data with strategic interactions. Among the three sets of experimental data the SUE approach was found to accurately predict the average choices, as well as the variances in choices. The fact that the SUE model was found to accurately predict variances in choices, suggests its applicability for transport equilibrium models that attempt to evaluate reliability in transportation systems. This finding is fundamental in the effort to determining a behaviourally consistent paradigm to model equilibrium in transport networks. The study also finds that Fechner error which is the inverse of the scale parameter in the SUE model is affected by the group sizes and the complexity of the cost function. In fact, the larger group sizes and complexity of cost functions increased the variability in choices. Finally, from an experimental design standpoint we show that it is not possible to estimate a noise parameter associate to Fechner error in the case when the choices are equally probable.