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.     

Urban travel time reliability at different traffic conditions

The decision making of travelers for route choice and departure time choice depends on the expected travel time and its reliability. A common understanding of reliability is that it is related to several statistical properties of the travel time distribution, especially to the standard deviation of the travel time and also to the skewness. For an important corridor in Changsha (P.R. China) the travel time reliability has been evaluated and a linear model is proposed for the relationship between travel time, standard deviation, skewness, and some other traffic characteristics. Statistical analysis is done for both simulation data from a delay distribution model and for real life data from automated number plate recognition (ANPR) cameras. ANPR data give unbiased travel time data, which is more representative than probe vehicles. The relationship between the mean travel time and its standard deviation is verified with an analytical model for travel time distributions as well as with the ANPR travel times. Average travel time and the standard deviation are linearly correlated for single links as well as corridors. Other influence factors are related to skewness and travel time standard deviations, such as vehicle density and degree of saturation. Skewness appears to be less well to explain from traffic characteristics than the standard deviation is.     

中国铁路提速后技术进步对产出贡献的测算

选取我国铁路提速后1997~2007年间的相关数据,采用基于科布——道格拉斯生产函数的Solow余值法,将有限分布滞后模型和半参数回归模型引入计算模型,对数据进行拟合,计算得到铁路提速后技术进步、固定资本投入以及人力资本投入对产出的贡献率,并根据计算结果提出促进我国高速铁路建设的相关对策建议.     

城市灯控平面交叉口的自行车交通设计研究

城市灯控平面交叉口混合交通流安全和效率的核心研究对象应该是自行车与机动车交通流间的相互影响。本丈在大量的理论分析和实践的基础上,探讨时空分离法的自行车交通设计的基本原则和交通空间设计方法,即自行车右转弯专用车道设计、左转自行车二次过街以及自行车与行人过街一体化设计,并进行了南京市太平北路与珠江路交叉口的应用实例分析。本文的城市灯控平面交叉口自行车的交通设计方法可为解决城市灯控平面交叉口混合交通问题提供借鉴。     

基于人均产值比的成都市物流需求分析

在阐述物流需求与人均国民生产总值关系的基础上,运用"人均产值比"法,对影响成都市农产品、工业品和居民消费品物流需求的主要因素进行分析,从而得出成都市物流需求基本特征,可为物流发展及规划提供参考。     

桥梁风致振动的混沌特性

利用非线性理论和混沌时间序列分析方法, 建立了桥梁风致振动的数学模型, 开发了计算桥梁振动加速度时间序列Lyapunov指数的MATLAB程序, 进行了桥梁涡振和颤振的风洞试验, 分析了不同风攻角下的桥梁风致振动的阻尼比、Lyapunov指数与风速的关系以及涡振振幅与风速的关系, 研究了桥梁颤振和涡振的混沌特性。试验结果表明: 在颤振试验中, 当风速小于颤振临界风速15.5m·s^-1时, Lyapunov指数小于0, Lyapunov指数与阻尼比存在很大的相关性, 当风速从3m·s^-1增大为18m·s^-1时, 相空间逐渐发散; 在涡振试验中, 当风速从4.5m·s^-1增大至8.5m·s^-1时, Lyapunov指数大于0, 桥梁发生明显涡振, 并由多频振动逐渐转变为单频振动, 相空间变为一个较为理想的圆。桥梁的涡振与颤振均属于混沌现象, 低风速下的Lyapunov指数可用来预测高风速下的风致振动, 并且利用相空间也能识别涡振与颤振。     

近断层地震动作用下减隔震桥梁空间动力分析

采用非线性时程分析法, 分析了减隔震桥梁和非减隔震桥梁的三维地震响应。通过对比减隔震桥梁在不同地震动激励下的动力响应, 研究了减隔震桥梁承受近断层地震动的响应特性。通过对比减隔震和非减隔震桥梁纵向地震位移, 研究了近断层地震动对铅销橡胶支座的减震性能的影响。研究结果表明: 与普通地震动激励相比, 在近断层长周期脉冲型地震动激励下, 减隔震桥梁减震率由54.4%降低为18.3%, 隔震支座的减震效果降低了; 在近断层脉冲地震动作用下, 减隔震桥梁梁体纵向位移为179.6mm, 非减隔震桥梁为151.6mm, 铅销橡胶支座增大了梁体的纵向位移, 易造成相邻梁体的碰撞或落梁, 因此, 近断层地区桥梁不宜采用铅销橡胶支座隔震。     

Fully autonomous vehicles: analyzing transportation network performance and operating scenarios in the Greater Toronto Area,Canada

Fully autonomous vehicles (AVs) have the potential to considerably change urban mobility in the future. This study simulates potential AV operating scenarios in the Greater Toronto Area (GTA), Canada, and assesses transportation system performance on a regional level. For each scenario, the base capacities of certain types of road links are modified to simulate the theoretical increase in throughput enabled by AV driving behavior. Another scenario examines driverless parking operations in downtown Toronto. Simulation results indicate that the increased attractiveness of freeways relative to other routes leads to slightly increased average travel distance as vehicles divert to access higher capacity road links. Average travel time is found to decrease by up to one-fifth at the 90% AV market penetration level. Concurrently, localized increases in congestion suggest that proactive transportation planning will be needed to mitigate negative consequences of AV adoption, especially in relation to induced demand for personal automobile travel.     

Mental models of driving and speed: biases,choices and reality

This paper provides a review of research performed by Svenson with colleagues and others work on mental models and their practical implications. Mental models describe how people perceive and think about the world including covariances and relationships between different variables, such as driving speed and time. Research on mental models has detected the time-saving bias [Svenson, O. (1970). A functional measurement approach to intuitive estimation as exemplified by estimated time savings. Journal of Experimental Psychology, 86, 204–210]. It means that drivers relatively overestimate the time that can be saved by increasing speed from an already high speed, for example, 90–130?km/h, and underestimate the time that can be saved by increasing speed from a low speed, for example, 30–45?km/h. In congruence with this finding, mean speed judgments and perceptions of mean speeds are also biased and higher speeds given too much weight and low speeds too little weight in comparison with objective reality. Replacing or adding a new speedometer in the car showing min per km eliminated or weakened the time-saving bias. Information about braking distances at different speeds did not improve overoptimistic judgments of braking capacity, but information about collision speed with an object suddenly appearing on the road did improve judgments of braking capacity. This is relevant to drivers, politicians and traffic regulators.     

A copula-based approach for estimating the travel time reliability of urban arterial

Estimating the travel time reliability (TTR) of urban arterial is critical for real-time and reliable route guidance and provides theoretical bases and technical support for sophisticated traffic management and control. The state-of-art procedures for arterial TTR estimation usually assume that path travel time follows a certain distribution, with less consideration about segment correlations. However, the conventional approach is usually unrealistic because an important feature of urban arterial is the dependent structure of travel times on continuous segments. In this study, a copula-based approach that incorporates the stochastic characteristics of segments travel time is proposed to model arterial travel time distribution (TTD), which serves as a basis for TTR quantification. First, segments correlation is empirically analyzed and different types of copula models are examined. Then, fitting marginal distributions for segment TTD is conducted by parametric and non-parametric regression analysis, respectively. Based on the estimated parameters of the models, the best-fitting copula is determined in terms of the goodness-of-fit tests. Last, the model is examined at two study sites with AVI data and NGSIM trajectory data, respectively. The results of path TTD estimation demonstrate the advantage of the proposed copula-based approach, compared with the convolution model without capturing segments correlation and the empirical distribution fitting methods. Furthermore, when considering the segments correlation effect, it was found that the estimated path TTR is more accurate than that by the convolution model.