罗城经怀宝至融水洞头公路越岭段路线方案研究

山区越岭段路线方案设计是整个项目路线设计的关键。文章结合罗城经怀保至融水洞头(罗城至风吹坳段)公路项目,从工程地质、技术经济、工程规模、方案实施、环境保护等方面,对该项目的灯美山至终点(风吹坳)段经平洞岭和经白岩坳的越岭段路线方案进行综合比选与论证,为类似山区越岭段路线方案设计工作提供参考。     

高速公路路线方案设计案例分析

结合永武高速朋口至车田段、泉三高速和洋至小桥段路线方案比选.介绍了山区高速公路路线方案确定原则.可为高速公路路线设计及方案选择提供参考.     

水土保持对道路路线方案优化应用

路线水保生态优选对道路安全、生态环境质量恢复及工程造价具有决定性作用.介绍青海省湟(源)至西(海)公路二期工程水土保持优化路线设计,对相应路线设计具有参考意义.     

桂柳高速公路改扩建路线方案设计探讨

文章以G72泉州至南宁高速公路广西桂林至柳州段改扩建工程永福至黄冕段典型路线方案为例,针对老路指标低、事故黑点多等问题,比选走廊带、隧道、互通方案,优化线路平纵面,探讨山区高速公路改扩建路线方案,以期为类似工程提供借鉴。     

广西河都高速公路顺高段隧道群设计方案比选

河都高速公路顺安至高岭段项目地形复杂、工程量艰巨,路线布设困难,如何选择最优的路线方案,是河都高速公路勘察设计要突破的重点和难点。文章结合工程概况拟定了两种路线方案,并从工程地质条件、工程规模、占地拆迁、营运效益和工程造价等方面对这两种方案进行比较,选出推荐使用的路线方案。     

就S307川口至大河家(省界)公路浅谈公路路线设计中涉及到的问题

主要针对S307川口至大河家(省界)公路路线设计的基本原则、路线设计中应注意的问题进行了简要阐述分析。     

浅谈沿河傍山地形公路选线

沿河岸的山岭路线走向,主要考虑周边环境及地形地貌、地质条件、施工条件、运营安全及环境保护、造价等因素,路线方案多分为两类,一是沿江的桥梁风景长廊,二是偏离河岸隐藏于大山之中的隧道通道。路线方案的确定,将影响整个项目的投资规模、工期长短、车辆运行的舒适与安全性等,由于涉及到河流饮用水源等民生问题,河岸山岭地形的路线走向更为注重环境保护因素。文章结合处于典型河岸地形的广西三江至柳州高速公路丹州路段路线选线工作实际,对沿河高架桥群路线及山岭隧道群路线的方案思路进行比选探讨。     

垃圾填埋场通过方案设计研究

阐述武定至昆明高速公路(K57+960K58+900段)路线测设中,对于垃圾填埋场,应根据其地形、地貌及路线平、纵、横,钻探资料等进行多方位的研究,合理选择通过方案。     

三维优化决策系统在山区高速公路路线优化中的应用

针对山区高速公路地质环境复杂、路线设计及优化难度大等特点,文章基于数字化、智慧交通的设计理念,以乐业至百色高速公路为依托工程,在路线设计优化过程中利用数字地形模型,同时采用三维优化运算软件对山区高速公路路线进行优化分析,以期较短时间内选择出经济合理的路线方案并大幅度降低工程造价,为同类工程优化设计提供参考。     

山区二级公路工可路线方案设计比选研究

路线设计是公路项目的工程可行性研究的灵魂,而山区二级公路由于其地形复杂、控制因素多、建设难度大等特点更需要合理设计并通过比选确定推荐方案。文章介绍了山区二级公路工可路线方案的设计原则、要点,并结合省道庙神至龙头公路的路线设计实例,通过多个路线方案比选,确定最终的推荐方案,分析了垭口选择、旧路利用在山区二级公路路线方案设计的重要性,为山区二级公路选线提供参考。     

Multi-criteria route planning based on a driver’s preferences in multi-criteria route selection

In this study, some different approaches were designed, implemented, and evaluated to perform multi-criteria route planning by considering a driver’s preferences in multi-criteria route selection. At first, by using a designed neuro-fuzzy toolbox, the driver’s preferences in multi-criteria route selection such as the preferred criteria in route selection, the number of route-rating classes, and the routes with the same rate were received. Next, to learn the driver’s preferences in multi-criteria route selection and to classify any route based on these preferences, a methodology was proposed using a locally linear neuro-fuzzy model (LLNFM) trained with an incremental tree based learning algorithm. In this regard, the proposed LLNFM-based methodology reached better results for running-times, as well as root mean square error (RMSE) estimations in learning and testing processes of training/checking data-set in comparison with those of the proposed adaptive neuro-fuzzy inference system (ANFIS) based methodology. Finally, the trained LLNFM-based methodology was utilized to plan and predict a driver’s preferred routes by classifying Pareto-optimal routes obtained by running the modified invasive weed optimization (IWO) algorithm between an origin and a destination of a real urban transportation network based on the driver’s preferences in multi-criteria route selection.     

永福至鹿寨公路潮水至波寨段路线方案比选分析

文章结合广西公路旧路改建工作实际,介绍了存在复杂交叉关系的旧路改建项目的基本特点及解决方法,并以永福至鹿寨公路潮水至波寨段工程为例,提出了不同的路线设计方案,对比分析各方案对路线选线的影响,为今后广西区域旧路改建项目的选线工作提供参考。     

基于Google Earth的公路路线漫游解决方案

介绍了Google Earth及其KML语言的基本知识,提出了在Google Earth中实现沿公路路线漫游的解决方案,给出了实现路线漫游的方法、步骤,为公路路线选线、汇报方案提供了一种生动、直观的表现方式。     

Designing a route planner to facilitate and promote cycling in Metro Vancouver,Canada

With increasing fuel costs, greater awareness of greenhouse gas emissions and increasing obesity levels, cycling is promoted as a health promoting and sustainable transport mode. We developed a cycling route planner (http://cyclevancouver.ubc.ca) for Metro Vancouver, British Columbia, Canada, to facilitate cycling amongst the general public and to facilitate new route location by transportation planners. The geographical information system-based planner incorporates variables that influence choices to travel by bicycle (e.g., distance, elevation gain, safety, route features, air pollution and links to transit) in selecting the preferred routing. Using a familiar and user-friendly Google Maps interface, the planner allows individuals to seek optimized cycling routes throughout the region based on their own preferences. In addition to the incorporation of multiple user preferences in route selection, the planner is unique amongst cycling route planners in its use of topology to minimize data storage redundancy, its reliance on node/vertex index tables to increase efficiency of the route selection process, and the use of web services and asynchronous technologies for quick data delivery. Use of this tool can help promote bicycle travel as a form of active transportation and help lower greenhouse gas carbon dioxide (CO₂) and air pollutant emissions by reducing car trips.     

山区水电工程场内公路路线设计探讨

文章针对山区水电站场内公路路线节点多、平面交叉多、立体分布广泛、上下线施工干扰大、布线方案困难等特点,对山区水电站场内公路路线布置与选线的原则、路线平纵设计方法、路线设计对构造物的影响等进行了分析探讨,为山区水电工程场内公路路线设计提供参考。     

Optimum routing of battery electric vehicles: Insights using empirical data and microsimulation

This study investigates the energy consumption impact of route selection on battery electric vehicles (BEVs) using empirical second-by-second Global Positioning System (GPS) commute data and traffic micro-simulation data. Drivers typically choose routes that reduce travel time and therefore travel cost. However, BEVs’ limited driving range makes energy efficient route selection of particular concern to BEV drivers. In addition, BEVs’ regenerative braking systems allow for the recovery of energy while braking, which is affected by route choices. State-of-the-art BEV energy consumption models consider a simplified constant regenerative braking energy efficiency or average speed dependent regenerative braking factors. To overcome these limitations, this study adopted a microscopic BEV energy consumption model, which captures the effect of transient behavior on BEV energy consumption and recovery while braking in a congested network. The study found that BEVs and conventional internal combustion engine vehicles (ICEVs) had different fuel/energy-optimized traffic assignments, suggesting that different routings be recommended for electric vehicles. For the specific case study, simulation results indicate that a faster route could actually increase BEV energy consumption, and that significant energy savings were observed when BEVs utilized a longer travel time route because energy is regenerated. Finally, the study found that regenerated energy was greatly affected by facility types and congestion levels and also BEVs’ energy efficiency could be significantly influenced by regenerated energy.     

Routing aspects of electric vehicle drivers and their effects on network performance

This study investigates the routing aspects of battery electric vehicle (BEV) drivers and their effects on the overall traffic network performance. BEVs have unique characteristics such as range limitation, long battery recharging time, and recuperation of energy lost during the deceleration phase if equipped with regenerative braking system (RBS). In addition, the energy consumption rate per unit distance traveled is lower at moderate speed than at higher speed. This raises two interesting questions: (i) whether these characteristics of BEVs will lead to different route selection compared to conventional internal combustion engine vehicles (ICEVs), and (ii) whether such route selection implications of BEVs will affect the network performance. With the increasing market penetration of BEVs, these questions are becoming more important. This study formulates a multi-class dynamic user equilibrium (MCDUE) model to determine the equilibrium flows for mixed traffic consisting of BEVs and ICEVs. A simulation-based solution procedure is proposed for the MCDUE model. In the MCDUE model, BEVs select routes to minimize the generalized cost which includes route travel time, energy related costs and range anxiety cost, and ICEVs to minimize route travel time. Results from numerical experiments illustrate that BEV drivers select routes with lower speed to conserve and recuperate battery energy while ICEV drivers select shortest travel time routes. They also illustrate that the differences in route choice behavior of BEV and ICEV drivers can synergistically lead to reduction in total travel time and the network performance towards system optimum under certain conditions.     

Knowledge-based systems for transport network analysis: A fifth generation perspective on transport network problems

This paper considers the formative steps in the development of an expert system for route selection in transport networks. It discusses the application of knowledge-based system (KBS) technology to the production of an expert system to provide route guidance information for some groups of urban travellers. There is a focus on the possibilities for applying a ‘fifth generation’ programming language, such as PROLOG, to the solution of network path selection problems, and the maintenance of a dynamic network database. There are significant arguments both for and against the use of the fifth generation languages, and the alternatives are discussed in speculative terms, on the basis of trials and experiments with PROLOG. The paper develops the specifications for a route guidance KBS for urban road travel, noting that one particular concern is that of providing the most suitable advice to a given traveller, rather than the system-wide rating of ‘best’ advice. Driver attitudes, behaviour, preferences, and vehicle characteristics differ widely, and the degree of satisfaction with any advice provided would depend largely on how closely the expert system could match the preferences of the individual traveller. Thus the system would need to gauge the characteristics of the user as well as those of the network under consideration. Further, prototype route guidance KBS are probably better directed at some clearly defined groups of urban travellers, such as commercial vehicle operations, rather than as community-wide systems.     

A statistical approach to the traveling salesman problem

A statistical approach is shown to be adaptable to the N-city traveling salesman problem by considering route distances to be random variables which are continuous and normally distributed. A solution to the shortest route distance and path can be approximated by utilizing a Monte Carlo simulation to obtain a representative sample of possible journeys. The approach involves recursive statistical inference which is used to select next-city visits leading to the most probable minimum route path. A statistical selection of the minimum route path is computationally efficient and computer run time increases in proportion to the square of the number of cities as opposed to an (N - 1)! increase for a deterministic approach. The accuracy of the statistical approach is directly proportional to the number of Monte Carlo simulations.     

Route Choice Behaviour of Freeway Travellers Under Real-time Traffic Information Provision – Application of the Best Route and the Habitual Route Choice Mechanisms

Abstract

This paper investigates route choice behaviour on freeways between Taipei and Taichung in Taiwan under the provision of real-time traffic information. Two types of route choice selection rules (the best-route and habitual-route) are analysed using ordered probit models to identify the major influences on freeway travellers’ route choice behaviour. The level of service associated with each route is defined as a generalised cost saving (GCS) and specified non-linearly with a threshold inherent to travellers. The marginal (dis)utility thresholds in the ‘best’ and ‘habitual’ behaviour models are identified through a goodness-of-fit grid. The results confirm that the thresholds for changing the inertia behaviour of drivers should be larger than the ones for choosing the best routes. In addition, the drivers are more likely to choose either the best or the habitual routes once the GCS are greater than the identified threshold values.