A topological route choice model for metro

This article presents a route choice model for public transit networks that incorporates variables related to network topology, complementing those found in traditional models based on service levels (travel time, cost, transfers, etc.) and users’ socioeconomic and demographic characteristics (income level, trip purpose, etc.). The topological variables represent concepts such as the directness of the chosen route and user knowledge of the network. For both of these factors, the necessary data is endogenous to the modelling process and can be quantified without the need for information-gathering beyond what is normally required for building route choice models. Other novel variables in the proposed formulation capture notions of user comfort such as vehicle occupancy rates and certain physical characteristics of network stations. We conclude that these new variables significantly improve the explanatory and predictive ability of existing route choice specifications.     

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。     

Intermodal Transit System Coordination

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.     

Mathematical properties and constraints representation for bottom-up approaches to the evaluation of GHG mitigation policies

Bottom-up models, including MARKAL, MESSAGE and AIM, are widely used when analyzing the effect of greenhouse gas (GHG) abatement policies. These bottom-up models are mostly formulated as a linear programming (LP) optimization model to find both the minimal cost combination of abatement technologies and energy flows while satisfying demands. It is not unusual that the bottom-up modeling involves a great number of technical, industrial, socioeconomic and environmental constraints. Investigating representative constraints needed for analyzing GHG abatement policies, this study proposes how to implement these constraints in bottom-up modeling.