Clockwise hysteresis loops in the Macroscopic Fundamental Diagram: An effect of network instability

A recent study reported that the Macroscopic Fundamental Diagram of a medium size city exhibited a clockwise hysteresis loop on a day in which a major disturbance caused many drivers to use unfamiliar routes. It is shown below that, even in a perfectly symmetric network with uniform demand, clockwise loops are to be expected when there are disturbances, especially if the disturbances cause a significant fraction of the drivers to not change routes adaptively. It is also shown that when drivers are not adaptive networks are inherently more unstable as they recover from congestion than as they are loaded. In other words, during recovery congestion tends more strongly toward unevenness because very congested areas clear more slowly than less congested areas. Since it is known that uneven congestion distributions reduce network flows, it follows that lower network flows should arise during recovery, resulting in clockwise loops. Fortunately, the presence of a sufficient number of drivers that choose routes adaptively to avoid congested areas helps to even out congestion during recovery, increasing flow. Thus, clockwise loops are less likely to occur when driver adaptivity is high.     

Multi-objective optimization of a road diet network design

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed.     

Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.     

考虑最短距离作业的港口拖轮作业调度优化

为了合理调度拖轮作业,有效提高拖轮的利用率,减少船舶等待时间,针对拖轮作业特点,用多处理器任务调度理论分析了拖轮作业调度问题.在考虑拖轮最短距离作业的前提下,以最小化最大完工时间为优化目标建立了拖轮作业调度模型.采用演化策略算法对拖轮作业调度问题进行优化,提出了一种基于轮盘赌概率分配的编、解码方法,并设计了三点交叉互换的重组算子和个体基因交叉互换的变异算子.算例结果表明:用演化策略算法的优化结果优于仿真结果和粒子群算法的计算结果.采用实数编码时,通过优化算法得到的最大完工时间最小值为356 min,比仿真结果减少了117 min;而采用整数编码时,最大完工时间最小值为369 min,比仿真结果减少了104 min.验证了最短距离作业原则的有效性.     

小城镇道路交通安全管理规划研究

通过分析我国小城城镇特点及其交通安全面临的问题,并结合交通安全规划的理论,提出小城镇道路交通安全规划的具体原则和内容,具有一定的理论和实际意义。     

公路平面交叉口交通组织设计

交叉口是道路系统的重要组成部分,既是道路交通的咽喉,但也是"瓶颈"。存在行车速度低、事故率高、交通拥挤甚至交通堵塞等弊病。针对交叉口交通事故的严重性,提出进行交通组织设计的必要性。主要介绍了3种交通组织方法:设置专用车道、左转弯车辆的交通组织、组织渠化交通。并结合具体设计实例对交通组织设计进行进一步的分析和阐明。     

高沁高速公路郑庄至里必段路线方案研究

结合山区地形,按照"以人为本"和"安全、环保、舒适、和谐"的新理念,对典型路段的路线方案进行优化设计、比选分析,最终选择最佳路线方案。     

城市交通拥堵分析及对策研究

从宏观、中观、微观层次分析导致城市拥堵的原因,倡导可持续的城市交通发展政策,以交通管理、交通供给、交通需求为出发点,提出深化交通体制改革与加强智能信息管理,增加道路有效供给与提升停车管理,构建快速公交系统与加强汽车需求管理,并结合土地利用、城市规划与交通建设协调发展提出建议。     

两种短时交通流混沌预测方法分析

短时交通流预测是智能交通系统的核心内容和交通信息服务、交通诱导的重要基础。采用符合交通流特性的混沌理论对短期交通流进行预测。在相空间重构和混沌识别的基础上,建立短期交通流加权一阶局域预测模型和基于最大Lyapunov指数的预测模型,并对一组实际的交通流数据进行预测。仿真结果表明:两种方法都能较准确的预测交通流,但最大Lyapunov指数预测模型的预测精度相对较高。