出行时间成本的测算方法及其影响因素分析

介绍了出行时间成本理论的假定,基于机会成本原理对出行时间成本进行了测算,针对其基本特性对其影响因素进行了深入分析,并据此在工资法的基础上提出了出行时间成本的计算模型。     

8XC196KC用于ABS轮速测量方法的改进研究

对ABS中速度测量的过程进行仔细的分析,提出了一种能够将精度和实时性相结合的速度测量方案,该方案能够较为有效地平衡精度和实时性之间的矛盾,并通过实际程序的执行验证了这一结论。这一测量方法不仅可用于ABS的速度测量,也可推广用于其他的速度或周期测量方案中。     

基于计算机视觉的驾驶员转向操作实时监测研究

为实时监控驾驶员操纵转向盘的状态，构建了基于机器视觉汽车转向盘实时监控系统，并运用阈值分割和边缘检测方法对转向盘图像中感兴趣区域进行了图像分割，提出了转向盘转角的计算公式。试验结果表明，感兴趣区域图像分割与转向盘转角监测方法有效。     

工程机械组群动态组织与集成管理系统研究

阐述了工程机械组群动态组织与集成管理系统的组成，特点和发展趋势，分析了系统的技术关键发及技术性能，确定了系统的构成方案，详细探讨了各功能单元的结合关系以及系统的社会，经济效益。     

信号控制对动态路线选择的影响研究

以动态路线选择模型为基础的先进的出行者信息系统（ＡＴＩＳ）的实施必然对城市交通控制系统产生影响，同时交通控制系统的控制方案对路线诱导信息“运行时间”的估计也发生作用，影响用户对最优路线的造选择。对两系统的相互关系进行了分析，并建立了两系统相互关系模型最后给出了实际案例分析。     

一种基于垂直字符边界特征的车牌定位方法

提出了一种基于垂直字符边界点特征的车牌定位方法，该方法能有效定位车牌，定位精度高达９８％，定位时间不超过２ｓ，并能有效地克服光线和天气条件等影响。     

温度和麻醉对神经几种兴奋性指标的影响——兼论何者可以正确反映兴奋性

在蟾蜍坐骨神经-腓神经观察了温度和麻醉对几种兴奋性指标的影响。结果表明,标准电量(a)随兴奋性的变化而有规律地变化。兴奋性愈高。a值愈小。而Weiss式中的b、基强度(Rh)、时值(Chr)及强度—时间曲线均不能正确反映兴奋性。细胞膜时间常数(RC)与兴奋性的变化无规律性联系。结论,a是兴奋性的可靠定量指标。     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.