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.     

The Northern Sea Route competitiveness for oil tankers

This article proposes a decision model for a ship-owner who contemplates the benefits of sailing north via the Northern Sea Route (NSR) or south via the Suez Canal Route (SCR) when transporting oil products from Russia to Asia. The decision is based on potential cost and transit time savings that change on a monthly basis according to sailing conditions and the area along the NSR. This study is applied to a 1A Ice-Class Panamax tanker vessel sailing through the NSR compared to a Panamax tanker vessel sailing through the SCR. It concludes that the NSR provides a competitive advantage in the months from August to November when conservative assumptions on ice conditions (higher bound) are considered for the level of ice thickness encountered along the route and from July to November when a lower bound is assumed.     

Consistent formulation of network equilibrium with stochastic flows

Traffic flows in real-life transportation systems vary on a daily basis. According to traffic flow theory, such variability should induce a similar variability in travel times, but this “internal consistency” is generally not captured by existing network equilibrium models. We present an internally-consistent network equilibrium approach, which considers two potential sources of flow variability: (i) daily variation in route choice and (ii) daily variation in origin–destination demand. We particularly aspire to a flexible formulation that permits alternative statistical assumptions, which allows the best fit to be made to observed variability data in particular applications. Joint probability distributions of route—and therefore link—flows are derived under several assumptions concerning stochastic driver behavior. A stochastic network equilibrium model with stochastic demands and route choices is formulated as a fixed point problem. We explore limiting cases which allow an equivalent convex optimization problem to be defined, and finally apply this method to a real-life network of Kanazawa City, Japan.     

Distributed coordinated in-vehicle online routing using mixed-strategy congestion game

This study proposes a coordinated online in-vehicle routing mechanism for smart vehicles with real-time information exchange and portable computation capabilities. The proposed coordinated routing mechanism incorporates a discrete choice model to account for drivers’ behavior, and is implemented by a simultaneously-updating distributed algorithm. This study shows the existence of an equilibrium coordinated routing decision for the mixed-strategy routing game and the convergence of the distributed algorithm to the equilibrium routing decision, assuming individual smart vehicles are selfish players seeking to minimize their own travel time. Numerical experiments conducted based on Sioux Falls city network indicate that the proposed distributed algorithm converges quickly under different smart vehicle penetrations, thus it possesses a great potential for online applications. Moreover, the proposed coordinated routing mechanism outperforms traditional independent selfish-routing mechanism; it reduces travel time for both overall system and individual vehicles, which represents the core idea of Intelligent Transportation Systems (ITS).     

On the value of highway travel time information systems

After the widespread deployment of Advanced Traveler Information Systems, there exists an increasing concern about their profitability. The costs of such systems are clear, but the quantification of the benefits still generates debate. This paper analyzes the value of highway travel time information systems. This is achieved by modeling the departure time selection and route choice with and without the guidance of an information system. The behavioral model supporting these choices is grounded on the expected utility theory, where drivers try to maximize the expected value of their perceived utility. The value of information is derived from the reduction of the unreliability costs as a consequence of the wiser decisions made with information. This includes the reduction of travel times, scheduling costs and stress. This modeling approach allows assessing the effects of the precision of the information system in the value of the information.Different scenarios are simulated in a generic but realistic context, using empirical data measured on a highway corridor accessing the city of Barcelona, Spain. Results show that travel time information only has a significant value in three situations: (1) when there is an important scheduled activity at the destination (e.g. morning commute trips), (2) in case of total uncertainty about the conditions of the trip (e.g. sporadic trips), and (3) when more than one route is possible. Information systems with very high precision do not produce better results. However, an acceptable level of precision is completely required, as information systems with very poor precision may even be detrimental. The paper also highlights the difference between the user value and the social value of the information. The value of the information may not benefit only the user. For instance, massive dissemination of travel time information contributes to the reduction of day-to-day travel time variance. This favors all drivers, even those without information. In these situations travel time information has the property that its social benefits exceed private benefits (i.e. information has positive externalities). Of course, drivers are only willing to cover costs equal or smaller than their private benefits, which in turn may justify subsidies for information provision.     

A bi-objective user equilibrium model of travel time reliability in a road network

Travel time, travel time reliability and monetary cost have been empirically identified as the most important criteria influencing route choice behaviour. We concentrate on travel time and travel time reliability and review two prominent user equilibrium models incorporating these two factors. We discuss some shortcomings of these models and propose alternative bi-objective user equilibrium models that overcome the shortcomings. Finally, based on the observation that both models use standard deviation of travel time within their measure of travel time reliability, we propose a general travel time reliability bi-objective user equilibrium model. We prove that this model encompasses those discussed previously and hence forms a general framework for the study of reliability related user equilibrium. We demonstrate and validate our concepts on a small three-link example.     

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。     

枢纽机场航线网络优化研究

枢纽机场航线网络优化主要解决由于航线网络结构与功能定位不匹配而导致的机场连通性低、航线网络同质化竞争严重、运行效率低下的问题。通过改进引力模型对城市对间的客流量进行预测,以此为预测的客流量为依据之一,以提高机场连通性为目的,构建航线网络优化模型,并进行求解。实现提高枢纽机场连通性、构建符合功能定位的层级网络的目标。并以位于我国中部,具有"连接南北,贯穿东西"地理优势的西安咸阳国际机场为例进行分析。由于国际航线受客观因素较多,本文主要研究国内客运航线,国际及货运不在本文研究之列。     

城市中心区停车诱导系统规划设计研究——以虹口区四川北路商业区为例

该文以上海市四川北路商业区停车诱导系统规划设计为例,结合四川北路商业区的交通特征和停车问题,以及国内外停车诱导系统的规划设计经验,提出停车诱导系统规划设计的总体理念和原则。然后,就停车诱导系统规划设计时遇到停车诱导系统架构、停车信息发布屏的版面设计、停车泊位采集装置的选用和信息传输方式等问题进行了探讨,为停车诱导系统的规划设计提供了一个良好的借鉴与思路。     

质心干扰毫米波末制导反坦克导弹的战术计算

针对对采用毫米波末制导技术的反坦克导弹实施质心干扰的行动,构建了箔条诱饵干扰模型,给出了成功实施质心干扰的条件。推导了坦克分队纵队行进和横队冲击时有效实施质心干扰的数学表达式。