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.     

On the fundamental diagram and supply curves for congested urban networks

Macroscopic fundamental diagrams (MFD) of traffic for some networks have been shown to have similar shape to those for single links. They have erroneously been used to help estimate the level of travel in congested networks. We argue that supply curves, which track vehicles in their passage through congested networks, are needed for this purpose, and that they differ from the performance curves generated from MFD. We use a microsimulation model, DRACULA and two networks, one synthesizing the network for Cambridge, England, and one of the city of York, England, to explore the nature of performance curves and supply curves under differing patterns of demand.We show that supply curves differ from performance curves once the onset of congestion is reached, and that the incorrect use of performance curves to estimate demand can thus seriously underestimate traffic levels, the costs of congestion, and the value of congestion relief measures. We also show that network aggregated supply curves are sensitive to the temporal distribution of demand and, potentially, to the spatial distribution of demand. The shape of the supply curve also differs between origin–destination movements within a given network.We argue that supply curves for higher levels of demand cannot be observed in normal traffic conditions, and specify ways in which they can be determined from microsimulation and, potentially, by extrapolating observed data. We discuss the implications of these findings for conventional modelling of network management policies, and for these policies themselves.     

关于公交线路线形及对位编码的思考

把城市公交线路站点进行线性回归,将其归纳为纵线、横线、左斜线、右斜线和环(含弧)线,并对社区公交提出新的见解.同时采用了分线形按方位区间分别对位编码的方法,对普通的公交线路番号的每个代码赋予特定的含义,使其具有明确的线路走向和方位识别功能.还对“线形布线及对位编码法”在实施中可能出现的问题及应对措施提出了自己的意见.该...     

黄山市慢行交通系统规划研究

在当前能源供应趋紧、城市交通拥堵加剧的背景下,规划完善的慢行交通系统,对于促进城市综合交通体系的可持续发展具有重要意义。基于黄山市慢行交通现状,明确黄山市慢行交通的功能定位和发展策略,构建主次搭配的分级慢行交通网络,并提出慢行设施的设置标准。     

Studying port selection on liner routes: An approach from logistics perspective

The research aims to study the port selection in liner shipping. The central work is to set up a model to deal with port choice decisions. The model solves three matters: ports on a ship’s route; the order of selected ports and loading/unloading ports for each shipment. Its objective is to minimize total cost including ship cost, port tariff, inland transport cost and inventory cost. The model has been applied in real data, with cargo flows between the USA and Northern Europe. Afterwards, two sensitive analyses are considered. The first assesses the impact of a number of port calls on the total cost which relates closely to the viability of two service patterns: multi ports and hub & spoke. The second analyzes the efficiency of large vessels in the scope of a logistics network. The overriding result of this research is to indicate the influence of logistics factors in the decision of port choice. The research emphasizes the necessity to combine different factors when dealing with this topic, or else a result can be one-sided.     

Optimal locations and travel time display for variable message signs

This paper first develops a network equilibrium model with the travel time information displayed via variable message signs (VMS). Specifically, the equilibrium considers the impact of the displayed travel time information on travelers’ route choices under the recurrent congestion, with the endogenous utilization rates of displayed information by travelers. The existence of the equilibrium is proved and an iterative solution procedure is provided. Then, we conduct the sensitivity analyses of the network equilibrium and further propose a paradox, i.e., providing travel time information via VMS to travelers may degrade the network performance under some poor designs. Therefore, we investigate the problem of designing the VMS locations and travel time display within a given budget, and formulate it as a mixed integer nonlinear program, solved by an active-set algorithm. Lastly, numerical examples are presented to offer insights on the equilibrium results and optimal designs of VMS.     

基于深度学习的驾驶员状态识别

提出了基于驾驶员脸部及周围信息的驾驶员状态检测方法。文章通过实车摄像头采集了驾驶员驾驶状态视频数据,利用Dlib和OpenCV库对采集的驾驶员图像进行脸部检测,基于驾驶员脸部数据建立了深度学习数据集,然后基于该数据集设计了一种卷积神经网络模型FaceNet,利用PyTorch深度学习框架在数据集上对模型进行训练,最终得到了有较高准确率的驾驶员状态检测模型,其可识别抽烟、睡觉、左手打电话和右手打电话四种驾驶员状态。     

转炉煤气中O_2气体分析系统设计

通过分析煤气回收工艺,介绍了炼钢厂转炉煤气中O2气体分析系统,包括取样单元、样品传输单元、样品预处理单元、分析单元。O2气体分析系统安装在气化装置的现场,设置了现场分析防护室,为其提供良好的运行环境和特殊的防护,以确保实时、准确地检测出转炉煤气中O2的含量。     

Airline network choice and market coverage under high-speed rail competition

While the existing literature has focused on the short-term impacts, this paper investigates the long-term impacts of high-speed rail (HSR) competition on airlines. An analytical model is developed to study how an airline may change its network and market coverage when facing HSR competition on trunk routes. We show that prior to HSR competition, an airline is more likely to adopt a fully-connected network and cover fewer fringe markets if the trunk market is large. Under HSR competition, the airline will, for a given network structure, have a greater incentive to cover more fringe (regional or foreign) markets if the trunk market is large, or the airline network is close to hub-and-spoke. Further, the airline will, for any given market coverage, move towards a hub-and-spoke network when the trunk market is large, or the number of fringe markets covered by the airline network is large. Both effects are more prominent when the decreasing rate of airline density economies is large. We further show that HSR competition can induce the airline to adopt network structure and market coverage that are closer to the socially optimal ones, thereby suggesting a new source of welfare gain from HSR based on its long-term impacts on airlines. Implications for operators, policy makers and specific countries (such as China) are also discussed.     

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.