A discrete optimization approach for locating Automatic Vehicle Identification readers for the provision of roadway travel times

This paper develops an algorithm for optimally locating Automatic Vehicle Identification tag readers by maximizing the benefit that would accrue from measuring travel times on a transportation network. The problem is formulated as a quadratic 0–1 optimization problem where the objective function parameters represent benefit factors that capture the relevance of measuring travel times as reflected by the demand and travel time variability along specified trips. An optimization approach based on the Reformulation–Linearization Technique coupled with semidefinite programming concepts is designed to solve the formulated reader location problem. To illustrate the proposed methodology, we consider a transportation network that is comprised of freeway segments that might include merge, diverge, weaving, and bottleneck sections. In order to derive benefit factors for the various origin–destination pairs on this network, we employ a simulation package (INTEGRATION) in combination with a composite function, which estimates the travel time variability along a trip that is comprised of links that include any of the four identified sections. The simulation results are actually recorded as generic look-up tables that can be used for any such section for the purpose of computing the associated benefit factor coefficients. Computational results are presented using data pertaining to a freeway section in San Antonio, Texas, as well as synthetic test cases, to demonstrate the effectiveness of the proposed approach, and to study the sensitivity of the quality of the solution to variations in the number of available readers.     

基于N-K模型的隧道施工事故多风险因素耦合分析

为解决多风险因素耦合作用对隧道安全施工的影响,在分析2009—2019年国内101次隧道施工事故发生原因的基础上,将影响隧道安全施工的风险因素区分为人为因素、设备因素、环境因素和管理因素4方面; 将风险耦合理论引入隧道施工事故风险分析中,探讨隧道施工事故多风险因素的耦合机制、分类和解耦原理,利用N-K模型构建隧道施工风险耦合模型,揭示隧道施工事故多风险因素间的耦合效应。研究结果表明： 参与耦合作用的风险因素越多,耦合作用形式计算的耦合值越大,则隧道施工风险越大。在3个风险因素参与的耦合过程中,人为-设备-环境因素之间的相互耦合作用造成的隧道施工风险最大;在2个风险因素参与的耦合过程中,设备-环境因素之间的相互耦合作用造成的隧道施工风险最大。基于解耦思想,可以减小隧道施工中各风险因素之间的耦合效应,进而降低隧道施工事故发生的可能性。