基于出站时间的高速公路收费站车辆排队检测

目前,对高速公路收费站进行服务评价的数据主要依靠人工现场调查或使用专用检测设备来获取,在人力、资金方面消耗较大。而收费站的海量收费数据则可通过自动调查直接获得,充分利用这些收费数据资源可以获得很好的经济价值。分析了目前国内在公路收费站排队研究方面的局限性和不足。基于高速公路收费站的实际数据,研究分析了排队情况下同车道相邻车辆的出站时间规律,对收费站的车辆排队检测算法,以及车辆队长、排队逗留时间、服务时间等指标的量化计算进行了方法设计。以陕西省富平、韩城和芝川收费站的收费数据进行了实例计算,并与 M/G/1模型的计算结果以及调研数据进行对比,分析其绝对误差,对比结果表明平均服务时间的绝对误差不超过3 s;除韩城收费站105车道外,平均队长的绝对误差不超过1辆;除富平收费站101车道外,平均逗留时间的绝对误差不超过10 s。验证了算法的有效性与普适性。     

电力牵引工频高压电磁场对人体视—运动反应时的影响

通过对我国电力牵引达２２年区段的２７．５ｋＶ工频电场强度为１．７５－３．４６ｋＶ／ｍ，磁感应强度为０．６０－１．７５ｍＴ，人体感应电流为１０．０８－５８．４０μＡ环境下作业的１３５９名工人和无电磁场接触史的３７５名工人的视－运动反应时值进行的测验和分析。结果表明两组无明显差异。引起视－运动反应时值的延长。结果表明两组无明显差异，引起视－运动反应时值的延长，机体协调功能减退的主要原因是年龄因素的增长     

基于行程时间可靠性的多类用户交通分配模型

分析了路网在随机因素作用下造成的出行者行程时间的不确定性.假设出行者基于期望行程时间和行程时间可靠性的均衡选择路径,根据出行者对待行程时间可靠性的不同态度,将其路径选择行为分类,建立了基于行程时间可靠性的多类用户交通分配的变分不等式模型.给出了模型的对角化算法.对一个小型测试网络的计算结果表明,该模型能够反映出行者在不确定环境下的路径选择行为.     

基于PERT的弹道导弹装填作业流程优化研究

通过对多枚弹道导弹装填网络作业流程进行分析,建立了三组数学模型。基于该模型将多枚导弹装填的问题转化为一种寻求最优方案的问题,并以三枚导弹装填网络作业流程的优化为例,阐述多枚导弹装填优化模型的过程,最后给出了多枚弹装填的时间公式。     

铁路贯通线融冰特性试验研究

研究目的:铁路10 kV贯通线因采用架空线与电缆混接方式,且其导线截面远小于电力系统110 kV及以上输电线路,因此,必须对其融冰特性试验研究,为10 kV贯通线融冰方案的实施提供基础数据。研究结论:本文在实验室模拟的现场环境中,选取了LGJ-35、LGJ-50和LGJ-70三种规格的钢芯铝绞线和相同截面积的10 kV交联电缆,进行了贯通线融冰试验研究,分析了融冰电流对贯通线电缆的承受能力、融冰时间和脱冰方式的影响,得出了如下结论:10 kV贯通线的最佳融冰电流范围为:LGJ-35,175～195 A;LGJ-50,210 A～240 A;LGJ-70,265～305 A。最佳融冰时间为1～2 h。     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.     

A stochastic analysis of highway capacity: Empirical evidence and implications

This paper presents a stochastic characterization of highway capacity and explores its implications on ramp metering control at the corridor level. The stochastic variation of highway capacity is captured through a Space–Time Autoregressive Integrated Moving Average (STARIMA) model. It is identified following a Seasonal STARIMA model (0, 0, 2₃) × (0, 1, 0)₂, which indicates that the capacities of adjacent locations are spatially–temporally correlated. Hourly capacity patterns further verify the stochastic nature of highway capacity. The goal of this paper is to study (1) how to take advantage of the extra information, such as capacity variation, and (2) what benefits can be gained from stochastic capacity modeling. The implication of stochastic capacity is investigated through a ramp metering case study. A mean–standard deviation formulation of capacity is proposed to achieve the trade-off between traffic operation efficiency and robustness. Following that, a modified stochastic capacity-constraint ZONE ramp metering scheme embedded cell transmission model algorithm is introduced. The numerical experiment suggests that considering capacity variation information would alleviate the spillback effect and improve throughput. Monte Carlo simulation further supports this argument. This study helps verify and characterize the stochastic nature of capacity, validates the benefits of using capacity variation information, and thus enhances the necessity of implementing stochastic capacity in traffic operation.     

一种基于县域城乡客运公交化改造的公交时刻表编制方法

为进一步协调县域城乡客运公交化改造与公交高效化运营之间的关系,合理确定城乡客运公交化改造后的公交时刻表至关重要。以县域城乡客运公交化改造为研究对象,提出了一种适合城乡客运公交化改造的公交时刻表编制方法。通过人工调查法获取客流信息,建立客流处理模型,获得最大断面客流量等信息。在此基础上,运用客流需求法建立数学模型,求得发车时间间隔并优化。最后,通过比较验证获得最终的公交时刻表。以池河至石泉客运班线公交化改造为例,改造后的公交时刻表极大地方便了沿线居民的出行,从而证明该时刻表具有较好的可行性。     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.