Agent-intermediated electronic markets in international freight transportation

In many industries, agent-intermediated markets are inefficient because information about latent demand and supply never gets to market. We demonstrate how information technology (IT) in the form of an agent-intermediated electronic market (EM) alleviates this problem by enhancing the agent-as-market-maker using the international freight transportation industry as an example. We find that an EM increases agent participation and investment thereby increasing demand and supply. Because of tradeoffs between incentives for investment, the EM chooses a profit allocation between agents resulting in limited agent participation. In addition, when price depends on demand and supply balances, price and volume in the market can increase simultaneously.     

地图匹配技术及其在智能交通系统中的应用

地图匹配(Map Matching)技术利用电子地图和定位信息来确定车辆在道路上的准确位置,是一种软件纠错技术。该文在引入地图匹配问题的基础上,分析讨论了目前主要的地图匹配算法,并结合智能交通系统(ITS)的需求,探讨了车辆所在道路上具体位置的识别方法,最后对地图匹配技术在ITS中的应用进行了回顾和展望。     

智能车辆定位系统设计

车辆定位与导航系统是智能交通系统中当前需求较为迫切、应用比较广泛的一个重要的应用系统,是国际上公认的解决城市交通问题的有效途径之一。本文通过分析给出了智能车辆定位与导航系统的组成,并详细分析了核心技术。最后,给出了系统的硬件平台。     

Multi-objective discrete urban road network design

This paper addresses the problem of designing urban road networks in a multi-objective decision making framework. Given a base network with only two-way links, and the candidate lane addition and link construction projects, the problem is to find the optimal combination of one-way and two-way links, the optimal selection of network capacity expansion projects, and the optimal lane allocations on two-way links to optimize the reserve capacity of the network, and two new travel time related performance measures. The problem is considered in two variations; in the first scenario, two-way links may have different numbers of lanes in each direction and in the second scenario, two-way links must have equal number of lanes in each direction. The proposed variations are formulated as mixed-integer programming problems with equilibrium constraints. A hybrid genetic algorithm, an evolutionary simulated annealing, and a hybrid artificial bee colony algorithm are proposed to solve these two new problems. A new measure is also proposed to evaluate the effectiveness of the three algorithms. Computational results for both problems are presented.     

Design of human–machine interactions in light of domain-dependence of human-centered automation

This paper discusses that human-centered automation for traffic safety can vary depending on transportation mode. Quality of human operators and time-criticality are factors characterizing the domain-dependence. The questions asked in this paper are: (1) Does the statement that, “The human must be in command,” have to hold at all times and on every occasion, and in every transportation mode? and (2) What the automation may do when it detected the human’s inappropriate behavior or performance while monitoring the human? Is it allowed only to give some warnings? Or, is it allowed to act autonomously to resolve the detected problem? This paper also argues that human-centered automation must be multi-layered, by taking into account not only enhancement of situation awareness but also trading of authority between humans and machines.     

Influence of back angle on the quality of sleep in seats

Nocturnal sleep was assessed electroencephalographically in 9 males aged between 29 and 48 (mean 36·5) years in bed and in three seats with back angles to the vertical of 49·5° (sleeperette), 37·0° (reclining seat) and 17·5° (armchair).

Sleep in the sleeperette did not differ from that in bed, but in the reclining seat the duration of sleep was reduced and the amount of awake activity was increased. Sleep in the armchair was markedly worse than in any of the other three conditions. Total sleep time was shorter and awake activity was increased with more awakenings. Sleep efficiency was also reduced.

It would appear that adequate sleep may be obtained in seats as long as the back angle with the vertical approaches 40°.     

Transit network timetabling and vehicle assignment for regulating authorities

In the literature on transit planning, network timetabling and vehicle scheduling are usually treated as separate problems. In this paper, we focus on combining important features of these two steps and propose a simultaneous solution approach to redefine timetables with the objective of bringing improvements to both quality of service and vehicle costs incurred. This includes the objectives of quantity and quality of the transfers proposed, evenness of the line headways, fleet size and length of the deadheads. The model proposed for this simultaneous approach is adapted to the problem faced by regulating authorities, encouraging intermodality and taking into account a variety of practical features. We introduce an optimization procedure based on Iterated Local Search and present computational experiments carried out on data from a large existing transit network, showing substantial improvements in both quality of service and level of resources compared to the current practice.     

An intelligence-based route choice model for pedestrian flow in a transportation station

This study proposes a method that uses an artificial neural network (ANN) to mimic human decision-making about route choice in a crowded transportation station. Although ANN models have been developed rapidly and widely adopted in various fields in the last three decades, their application to predict human decision-making in pedestrian flows is limited, because the video clip technology used to collect pedestrian movement data in crowded conditions is still primitive. Data collection must be carried out manually or semi-manually, which requires extensive resources and is time consuming. This study adopts a semi-manual approach to extract data from video clips to capture the route choice behaviour of travellers, and then applies an ANN to mimic such decision-making. A prediction accuracy of 86% (ANN model with ensemble approach) is achieved, which demonstrates the feasibility of applying the ANN approach to decision-making in pedestrian flows.     

城市智能交通系统技术发展现状及趋势

城市化的快速发展带来一系列的交通问题,智能交通系统(Intelligent Transportation Systems,ITS)是解决交通问题的有效途径之一。本文主要介绍了智能交通系统的概念与内涵、我国城市智能交通系统技术发展与智能交通管控系统应用现状,在上述内容的基础上,总结了我国城市智能交通系统未来的发展趋势。     

加快智能交通发展思路的探讨

随着智能交通的应用逐步覆盖和深入到交通运输领域,智能交通系统的地位和作用已逐步得到加强和重视。本文分析了陕西省道智能交通发展的必要性,提出了陕西省智能交通发展的思路及其重点任务。