Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.     

Model-based predictive control for bicycling in urban intersections

In this paper, a model predictive control approach for improving the efficiency of bicycling as part of intermodal transportation systems is proposed. Considering a dedicated bicycle lanes infrastructure, the focus in this paper is to optimize the dynamic interaction between bicycles and vehicles at the multimodal urban traffic intersections. In the proposed approach, a dynamic model for the flows, queues, and number of both vehicles and bicycles is explicitly incorporated in the controller. For obtaining a good trade-off between the total time spent by the cyclists and by the drivers, a Pareto analysis is proposed to adjust the objective function of the MPC controller. Simulation results for a two-intersections urban traffic network are presented and the controller is analyzed considering different methods of including in the MPC controller the inflow demands of both vehicles and bicycles.     

Personalized real-time traffic information provision: Agent-based optimization model and solution framework

The advancement of information and communication technology allows the use of more sophisticated information provision strategies for real-time congested traffic management in a congested network. This paper proposes an agent-based optimization modeling framework to provide personalized traffic information for heterogeneous travelers. Based on a space–time network, a time-dependent link flow based integer programming model is first formulated to optimize various information strategies, including elements of where and when to provide the information, to whom the information is given, and what alternative route information should be suggested. The analytical model can be solved efficiently using off-the-shelf commercial solvers for small-scale network. A Lagrangian Relaxation-based heuristic solution approach is developed for medium to large networks via the use of a mesoscopic dynamic traffic simulator.     

水平荷载作用下钢管支架的弹塑性极限承载力分析

通过考虑桩土相互作用以及材料和几何非线形，对钢管支架在水平荷栽作用下的极限承载力及其影响因素进行了分析，从而对钢管支架的安全度作出合理的评价。     

汽车机械故障原因及防范措施

自中国改革开放以来我国的经济得到了飞速的提升,人们的生活质量和生活水平也在日新月异的变化,在现今时代汽车已经普及到了千家万户,成为了人们日常生活的必需品,也正因为如此汽车机械故障的原因及防范措施也逐渐受到了人们的关注,本文也就汽车故障产生的原因进行了分析,并寻找出相对应的解决策略。     

基于多维信息特征分析的驾驶人认知负荷研究

准确评估驾驶人认知负荷水平，对于深入研究驾驶人行为特性，改善驾驶安全性具有重要意义。现有的驾驶人认知负荷分类方法，大多基于心电、脑电等生理信息和车辆信息，由于特征选择上的单一性，导致驾驶人认知负荷分类模型的分类精度不高。设计基于跟驰场景的不同认知负荷N-back次任务试验，通过采集受试者的生理信号和车辆信号，结合NASA_TLX主观评分和机器学习算法，提出了基于多维信息特征融合的驾驶人认知负荷分类方法。研究表明：基于生理信息和车辆信息的多维信息特征认知负荷分类方法，其精度显著高于传统的基于生理信息的认知负荷分类方法，以多维信息特征为输入，随机森林法以其稳定性好、抗过拟合能力强的特点，表现出优异的分类效果，相比神经网络和支持向量机，具有最高的平均分类精度。     

高城镇化水平地区高、快速路复合通道研究

通过对复合通道相关研究的综述,总结了高、快速路复合通道的积极意义,提出复合通道建设的难点主要为通道走廊的选择与布局模式的选取、降低节点复杂程度、解决各系统间的转换需求以及施工组织复杂.并以佛山市广佛新干线复合通道为例简要介绍了上述几个难点的处理思路,最后分析了复合通道建设存在的几个要点问题,为该类型道路的建设提供一定的基础.     

倾斜 PHC 管桩的处理方法及剩余承载力研究

已完成施打的PHC管桩,由于疏于保护等因素,使桩承受了非能预见的水平荷载,桩身通常会出现一定程度的倾斜,它会使PHC管桩桩身产生裂缝、断裂、弯曲或倾斜,使PHC管桩承载力降低或者失效,对工程质量及安全产生重大的影响.通过某工程的PHC管桩受基坑滑坡影响造成倾斜处理实例,从现有理论分析成果出发,结合工程实际处理的对策,得出对于工程实际中具有指导意义的结论,为类似工程缺陷桩的处理提供一个有效的方案.