考虑驾驶人风格的换道轨迹规划与控制（双语出版）

基于自动换道控制技术中融合个性化驾驶人风格的研究,建立考虑驾驶人风格的车辆换道轨迹规划及控制模型以提高换道规划控制模型对不同风格驾驶人的适用性,在保证安全性的基础上进一步满足驾驶人的个性化需求。首先通过问卷调查的方式采集得到了212份驾驶人风格量表数据,采用主成分分析法和K均值（K-means）聚类分析法将驾驶人按驾驶风格分为激进型、普通型和谨慎型,并通过驾驶模拟器试验采集不同风格驾驶人分别在自车道前车、目标车道前车和目标车道后车影响下的换道行为数据。然后对椭圆车辆模型进行改进,以描述不同风格驾驶人的行车安全区域,并据此构建3种典型工况下不同风格驾驶人的换道最小安全距离模型,结合驾驶舒适性约束、车辆几何位置约束以及不同风格驾驶人的换道行为数据,以换道纵向位移最短为目标,实现适应驾驶人风格的换道轨迹规划。最后以基于预瞄的路径跟踪模型作为前馈量,设计基于动力学的线性二次型最优（LQR）反馈控制器,通过调节控制权重矩阵实现3种工况下不同驾驶人风格的换道轨迹跟踪。PreScan和MATLAB/Simulink联合仿真结果表明：所设计的考虑驾驶人风格的换道轨迹规划及跟踪控制模型能够实现不同驾驶风格的自动换道轨迹规划及跟踪控制,可满足驾驶人个性化换道需求。     

信号系统在直线电机运载系统中的应用

阐明直线电机运载系统的产生背景、构成和工作原理,重点分析在直线电机运载系统开放的电磁环境下,信号系统车载设备和轨旁设备的电磁兼容性问题。论述为了充分发挥直线电机运载系统的优越性．应在坡道的启动控制、车辆的制动控制、小半径曲线控制、牵引力波动控制、感应板电流过载防护等方面注意信号系统与相关专业的接口,并应根据道岔类型为信号系统配置合适的转辙设备。     

一类有竞争的物流配送中心选址模型

对已有多个配送中心存在的前提下, 新增配送中心为获取最大市场占有量如何进行有效的选址决策问题进行了研究, 建立了一个选址决策模型, 把求解的问题归结为无约束的非线性规划问题, 并给出了迭代算法, 最后对如何解决考虑多种选址影响因素及多个新增配送中心的复杂情况进行了讨论。     

遥感在新建中吉乌国际铁路中国境内段可行性研究中的应用

采用 TM卫星图像在可行性研究阶段对地质复杂地区进行判释评价是一种行之有效的方法。本文对工作区的构造单元、地层岩性、不良地质进行了判释 ,并根据影像特征对工程地质条件、区域稳定性进行了定性评价。     

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诱增交通量是交通需求预测与交通建设项目评价中的重要组成部分.本文从诱增交通量概念出发，从宏观和微观两个角度阐述了区域诱增交通量产生的机理，分析了现行单个建设项目诱增交通量计算思路的局限性，研究提出了基于区域的诱增交通量计算的多元线性回归模型.论文结合我国的国情，对该模型参数进行了标定，提出了符合中国实际的基于区域诱增交通量计算方法.利用北京地区改革开放之后(1978年至2003年)的数据进行了实例分析，得到了道路建设对交通量的近期影响弹性系数0.17,远期影响弹性系数0.29的结果.     

城市道路交叉口当量人群运行特征

基于非机动车和行人通过交叉口时的交通流运行特征, 定义了当量人群的概念来描述非机动车和行人对机动车通行的共同影响。统计了高峰小时的当量人群数据, 考虑样本的稳定性、样本量的大小以及应用的便利性, 以15 min为分析时段, 采用回归分析的方法得到了当量人群的当量人数与当量人群的平均群时距和群个数之间的回归关系模型。分析结果表明: 当量人群的群时距符合移位负指数分布; 当量人群的平均群时距随着当量人数的增加而减小; 当量人群的群个数随着当量人数的增加表现出先增加后减小的趋势。     

Optimization models for differentiating quality of service levels in probabilistic network capacity design problems

This paper develops various chance-constrained models for optimizing the probabilistic network design problem (PNDP), where we differentiate the quality of service (QoS) and measure the related network performance under uncertain demand. The upper level problem of PNDP designs continuous/discrete link capacities shared by multi-commodity flows, and the lower level problem differentiates the corresponding QoS for demand satisfaction, to prioritize customers and/or commodities. We consider PNDP variants that have either fixed flows (formulated at the upper level) or recourse flows (at the lower level) according to different applications. We transform each probabilistic model into a mixed-integer program, and derive polynomial-time algorithms for special cases with single-row chance constraints. The paper formulates benchmark stochastic programming models by either enforcing to meet all demand or penalizing unmet demand via a linear penalty function. We compare different models and approaches by testing randomly generated network instances and an instance built on the Sioux–Falls network. Numerical results demonstrate the computational efficacy of the solution approaches and derive managerial insights.     

Development and evaluation of a statistically reliable traffic counting program

This paper reviews the existing procedures to compute the seasonal factors, growth factors, and the number of automatic traffic recorder stations (ATRs) for developing a statistically reliable traffic counting program. The review is based on, (i) theoretical evaluation of the procedures, (ii) analysis of the results obtained from applying these procedures to extensive real life data, and (iii) experience of past researchers with these methods. The paper primarily deals with existing statistical procedures for determining seasonal factors, since it is believed that these factors play the most important role in estimating Annual Average Daily Traffic (AADTs) from short counts. The procedure of cluster analysis (which is most commonly used to determine seasonal factors) is critically reviewed. The shortcomings of this method motivated the development of a different statistical procedure, based on regression analysis, to determine seasonal factors. It is shown that this newly developed method gives better results than the cluster analysis techniques. Furthermore, separate sections are dedicated to a thorough analysis of determination of number of ATR stations and computation of growth factors.     

Lights,camera, legal action! The effectiveness of red light cameras on collisions in Los Angeles

This study estimates the effect of red light cameras (henceforth cameras) on collisions under the Los Angeles Automated Photo Enforcement Program that ran from 2006 to 2011. To control for selection bias and unobservables, a data set is constructed such that intersections with cameras are compared to control groups of nearby intersections without cameras, matched on observable characteristics. To capture potential spillover effects of cameras, control groups at various distances from the intersections with cameras are considered. A Poisson panel data model with random coefficients is applied to these data and estimated using Bayesian methods. The program suffered from weaknesses in enforcement. The city’s courts did not uphold citations and this dampened the effect cameras had on drivers. These problems are accounted for in modeling. Controlling for these concerns, results indicate that the cameras decreased red light running related collisions, but increased right-angle and injury collisions, as well as collisions overall.     

Safety modeling for two‐way left‐turn lanes and a procedure to identify two‐way left‐turn lane segments with safety concerns

In the past, two‐way left‐turn lane (TWLTL) median treatments have been frequently used in Florida to inexpensively improve traffic and safety performances. In order to identify factors that may have significant impacts on safety operations in TWLTL sections and to identify TWLTL locations that present existing and future safety concerns, a research project was carried out and results are summarized in the paper. In the research, a three‐year crash history database with crashes and section characteristics from a total of 1688 TWLTL sections all over Florida was developed and used. A negative binomial regression model was developed to determine the statistical relationship between the number of crashes per mile per year and several variables such as traffic volume, access density, posted speed, and number of lanes. In regard to the methodology, in order to identify locations with safety concerns, several steps are needed: development of real crash data distribution, determination of statistical distribution models that better represent the actual crash data, determination of percentile values for the average number of crashes, estimation of crash rates for sections with the same characteristics, estimation of critical values for the variables corresponding to the percentile values for average number of crashes, calculation of tables of critical average annual daily traffic values, and generation of a list of TWLTL locations with critical safety concerns. Results presented in the paper have been used in real applications. Copyright © 2012 John Wiley & Sons, Ltd.