中国智慧城市、智慧交通和智能汽车(SCSTSV)——发展战略、系统构架和应用

汽车制造商(OEM)和供应商的全球创新者正在加速智能网联汽车(ICV)的创新,包括美国,欧洲和日本.中国是全球最大的汽车市场,中国智能网联汽车产业创新联盟(CAICV)宣布了中国ICV愿景.联合国的报告指出,到2050年将有68％的人口居住在城市中.系统架构和市场应用是实现中国智慧城市、智慧交通和智慧车辆(SCSTSV...     

A robust method for estimating transit passenger trajectories using automated data

Development of an origin-destination demand matrix is crucial for transit planning. The development process is facilitated by automated transit smart card data, making it possible to mine boarding and alighting patterns on an individual basis. This research proposes a novel trip chaining method which uses Automatic Fare Collection (AFC) and General Transit Feed Specification (GTFS) data to infer the most likely trajectory of individual transit passengers. The method relaxes the assumptions on various parameters used in the existing trip chaining algorithms such as transfer walking distance threshold, buffer distance for selecting the boarding location, time window for selecting the vehicle trip, etc. The method also resolves issues related to errors in GPS location recorded by AFC systems or selection of incorrect sub-route from GTFS data. The proposed trip chaining method generates a set of candidate trajectories for each AFC tag to reach the next tag, calculates the probability of each trajectory, and selects the most likely trajectory to infer the boarding and alighting stops. The method is applied to transit data from the Twin Cities, MN, which has an open transit system where passengers tap smart cards only once when boarding (or when alighting on pay-exit buses). Based on the consecutive tags of the passenger, the proposed algorithm is also modified for pay-exit cases. The method is compared to previous methods developed by the researchers and shows improvement in the number of inferred cases. Finally, results are visualized to understand the route ridership and geographical pattern of trips.     

Demand-driven timetable design for metro services

Timetable design is crucial to the metro service reliability. A straightforward and commonly adopted strategy in daily operation is a peak/off-peak-based schedule. However, such a strategy may fail to meet dynamic temporal passenger demand, resulting in long passenger waiting time at platforms and over-crowding in trains. Thanks to the emergence of smart card-based automated fare collection systems, we can now better quantify spatial–temporal demand on a microscopic level. In this paper, we formulate three optimization models to design demand-sensitive timetables by demonstrating train operation using equivalent time (interval). The first model aims at making the timetable more dynamic; the second model is an extension allowing for capacity constraints. The third model aims at designing a capacitated demand-sensitive peak/off-peak timetable. We assessed the performance of these three models and conducted sensitivity analyzes on different parameters on a metro line in Singapore, finding that dynamical timetable built with capacity constraints is most advantageous. Finally, we conclude our study and discuss the implications of the three models: the capacitated model provides a timetable which shows best performance under fixed capacity constraints, while the uncapacitated model may offer optimal temporal train configuration. Although we imposed capacity constraints when designing the optimal peak/off-peak timetable, its performance is not as good as models with dynamical headways. However, it shows advantages such as being easier to operate and more understandable to the passengers.     

A geometry-based algorithm to provide guidance for electric vehicle charging

Electric vehicles (EVs) have been regarded as effective options for solving the environmental and energy problems in the field of transportation. However, given the limited driving range and insufficient charging stations, searching and selecting charging stations is an important issue for EV drivers during trips. A smart charging service should be developed to help address the charging issue of EV drivers, and a practical algorithm for charging guidance is required to realise it. This study aims to design a geometry-based algorithm for charging guidance that can be effectively applied in the smart charging service. Geographic research findings and geometric approaches are applied to design the algorithm. The algorithm is practical because it is based on the information from drivers’ charging requests, and its total number of calculations is significantly less than that of the conventional shortest-first algorithm. The algorithm is effective because it considers the consistency of direction trend between the charging route and the destination in addition to the travel distance, which conforms to the travel demands of EV drivers. Moreover, simulation examples are presented to demonstrate the proposed algorithm. Results of the proposed algorithm are compared with those of the other two algorithms, which show that the proposed algorithm can obtain a better selection of charging stations for EV drivers from the perspective of entire travel chains and take a shorter computational time.     

Optimization and integration of ground vehicle systems

This article deals with the optimal design of ground vehicles and their subsystems, with particular reference to 'active' safety and comfort. A review of state-of-the-art optimization methods for solving vehicle system design problems, including the integration of electronic controls, is given, thus further encouraging the use of such methods as standard tools for automotive engineers. Particular attention is devoted to the class of methods pertaining to complex system design optimization, as well as approaches for the optimal design of complex systems under uncertainty. Some examples of design optimizations are given in the fields of vehicle system dynamics, powertrain/internal combustion engine design, active safety and ride comfort, vehicle system design and lightweight structures, advanced automotive electronics, and smart vehicles.     

从公交IC卡收费系统走向城市一卡通系统

本文以当前国内普遍应用的公交IC卡收费系统为基础,探讨了使之升级改造为符合国家标准的城市一卡通系统的关键点和对策以及实施策略.     

长江“智能航道”系统架构与关键技术

在对长江"数字航道"发展状况和国内外智能水路系统现状的研究基础上,提出长江"智能航道"的基本组成和总体结构。通过长江"智能航道"系统基本特征和所具优势的分析,指出长江"智能航道"系统的若干关键技术,并对长江"智能航道"系统发展方向进行展望。最后提出了发展长江"智能航道"系统的若干建议。     

基于.net智能客户端技术的新型调度命令系统

研究和分析了在分散自律调度集中系统中调度命令管理部分的用户需求、系统特点,并论述了在新的.net平台下,以智能客户端技术为基础,采用面向服务的SOA架构及数据库技术,实现新型调度命令管理系统的设计方案和实现策略,并重点讨论了新系统中为了实现系统的高可用性而采取的一系列技术措施和人性化设计。     

移动支付在轨道交通自动售检票系统中的设计与应用

介绍移动支付自动售检票（AFC）的设计,在现有传统地铁AFC系统基础上,设计基于移动支付方式的新型AFC系统,对移动支付AFC系统设计的目标和各参与对接方的要求进行深入分析,对车票管理业务、车票应用业务、数据交换业务等移动支付AFC系统,以及系统对接设计、移动支付车票发行系统、数据交换子系统的业务进行设计与分析,最后给出系统的接口设计和系统的部署方案,体现了移动支付AFC系统的可靠性、安全性和优越性。     

Hierarchical evaluation scheme on technology sourcing for advanced public transport systems

Advanced public transport system (APTS) technologies have received much attention from industry researchers in recent years for their evident importance to economic growth. The development of critical APTS technology, such as the contact-less smart card (CSC), in newly industrialized areas receives its impetus from the experience of developed countries. The evaluation of technology sourcing with a higher growth potential in CSC technology has become a critical issue for Taiwanese firms. However, past research rarely emphasized it. This paper utilizes the grey statistical method with survey techniques and the analytic hierarchy process to develop an integrated evaluation model for solving the technology-sourcing problem. An empirical case of the CSC technology sourcing in Taiwan was chosen to demonstrate the application of the proposed model on this issue. The research results suggest that the application of the model provides a sensible path for company policy makers to effectively cope with the technology-sourcing evaluation problem.