Public perceptions of the use of dynamic message signs

Intelligent transportation systems have been promoted as a means to improve both the efficiency and safety of the road network. The effectiveness of advanced technologies in improving road safety has been an area of research which has thus far yielded mixed results. In order to ensure that advanced technologies deliver on their intended outcomes, more research has to be devoted to understanding road users' perceptions and reactions to these systems. This study examines drivers' perceptions of the use of dynamic message signs and their self‐reported reactions to the messages displayed. In general, drivers support the use of highway electronic boards for traffic incident reports and weather information which have an impact on traffic delays and level of service. They also think that it is a good idea to display road safety messages and to remind drivers to drive safely and be courteous on the roads. Moreover, most drivers reported that they do read and think about the messages displayed and react positively to some of the road safety messages.     

ITS Solutions and Accident Risks: Prospective and Limitations

Abstract

This article investigates the prospective and limitations in the application of potential intelligent transport system (ITS) functions to reduce accident risks, using a cause‐treatment relationship. The main causes of road accidents are described and appropriate ITS solutions (including advanced driver assistance systems and advanced traveller information systems) are presented as countermeasures. Anticipated impacts are discussed and indicate that several ITS have the potential of improving road safety and addressing specific accident causes. However, attention is required on particular aspects of their implementation as they may trigger adverse effects by imposing behavioural adaptation risks, and overestimation and over‐reliance on system capabilities. Further, user acceptability and strategic implementation issues are paramount to the successful introduction of these systems.     

A private matter: the implications of privacy regulations for intelligent transportation systems

The rapid development and deployment of Intelligent Transportation Systems (ITS) that utilize data on the movement of vehicles can greatly benefit transportation network operations and safety, but may test the limits of personal privacy. In this paper we survey the current state of legal and industry-led privacy protections related to ITS and find that the lack of existing standards, rules, and laws governing the collection, storage, and use of such information could both raise troubling privacy questions and potentially hinder implementation of useful ITS technologies. We then offer practical recommendations for addressing ITS-related privacy concerns though both privacy-by-design solutions (that build privacy protections into data collection systems), and privacy-by-policy solutions (that provide guidelines for data collection and treatment) including limiting the scope of data collection and use, assuring confidentially of data storage, and other ways to build trust and foster consumer consent.     

Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

The quest for more fuel-efficient vehicles is being driven by the increasing price of oil. Hybrid electric powertrains have established a presence in the marketplace primarily based on the promise of fuel savings through the use of an electric motor in place of the internal combustion engine during different stages of driving. However, these fuel savings associated with hybrid vehicle operation come at the tradeoff of a significantly increased initial vehicle cost due to the increased complexity of the powertrain. On the other hand, telematics-enabled vehicles may use a relatively cheap sensor network to develop information about the traffic environment in which they are operating, and subsequently adjust their drive cycle to improve fuel economy based on this information – thereby representing ‘intelligent’ use of existing powertrain technology to reduce fuel consumption. In this paper, hybrid and intelligent technologies using different amounts of traffic flow information are compared in terms of fuel economy over common urban drive cycles. In order to develop a fair comparison between the technologies, an optimal (for urban driving) hybrid vehicle that matches the performance characteristics of the baseline intelligent vehicle is used. The fuel economy of the optimal hybrid is found to have an average of 20% improvement relative to the baseline vehicle across three different urban drive cycles. Feedforward information about traffic flow supplied by telematics capability is then used to develop alternative driving cycles firstly under the assumption there are no constraints on the intelligent vehicle’s path, and then taking into account in the presence of ‘un-intelligent’ vehicles on the road. It is observed that with telematic capability, the fuel economy improvements equal that achievable with a hybrid configuration with as little as 7 s traffic look-ahead capability, and can be as great as 33% improvement relative to the un-intelligent baseline drivetrain. As a final investigation, the two technologies are combined and the potential for using feedforward information from a sensor network with a hybrid drivetrain is discussed.     

Data attribution and network representation issues in GIS and transportation

Geographic Information System (GIS) is an “intelligent” technology which integrates attribute data and spatial features and manages the relationship between them. GIS is widely used in many activities, but its application in transportation is less common. The extension of GIS into transportation (GIS‐T) offers the potential to integrate transportation data into GIS. The integration of transportation data in GIS faces a number of barriers that are discussed in the paper. These barriers can be broadly categorized into data attribution and network representation issues. This paper analyzes these issues and reviews the potential for overcoming these constraints with current GIS technology. A fully developed GIS‐T has to meet many diverse needs including transportation inventory, modeling and operational problems. If GIS is to succeed as a transportation technology, it must be capable of integrating different levels of network representation and data attribution and have the ability to link with other transportation technologies.     

Integrating GIS concepts into transportation network data structures

Transportation network data structures must be designed to meet the requirements of the analyses being conducted and must be compatible with the selected graphical user interface. Increasing interest in geographic information systems (GIS) and intelligent transportation systems (ITS) have further burdened the network data structure. It is possible to implement object oriented programming (OOP) technology to satisfy these needs, without making the data structure excessively complicated.

This paper shows how a well‐developed network data structure can incorporate major capabilities normally associated with stand‐alone GIS's. The design of a network data structure derives from both theoretical and practical considerations. A design of a network data structure, composed entirely of objects, is presented. Examples of its implementation, limitations, advantages, and possible extensions are drawn from experience with the General Network Editor (GNE).     

Impact of telecommuting and intelligent transportation systems on residential location choice

The impacts of telecommuting and intelligent transportation systems (ITS) on urban development patterns were investigated in terms of households' residential location choice decisions. A discrete choice modelling approach framework was used. A stated preference (SP) logit analysis was carried out to estimate the parameters of the utility function. An attitude survey of employees of selected public and private sector organizations in the Ottawa-Carleton Region (Canada) yielded the required data for model estimation. In addition to obtaining background information, the survey elicited SP responses by presenting a number of hypothetical residential choice scenarios defined according to the principles of SP experimental design. Results show that telecommuting and ITS measures are highly significant factors in the residential choice model. This leads to the conclusion that these reinforce dispersed residential patterns and encourage moves towards outlying sites. Implications of this conclusion for urban land development planning are noted.     

Vehicle Positioning for Improving Road Safety

Abstract

Vehicle positioning is a key requirement for many safety applications. Active safety systems require precise vehicle positioning in order to assess the safety threats accurately, especially for those systems which are developed for warning/intervention in safety critical situations. When warning drivers of a local hazard (e.g. an accident site), accurate vehicle location information is important for warning the right driver groups at the right time. Global positioning system and digital maps have become major tools for vehicle positioning providing not only vehicle location information but also geometry preview of the road being used. Advances in wireless communication have made it possible for a vehicle to share its location information with other vehicles and traffic operation centres which greatly increases the opportunities to apply vehicle positioning technologies for improving road safety. This paper presents a state‐of‐the‐art review of vehicle positioning requirements for safety applications and vehicle positioning technologies. The paper also examines key issues relating to current and potential future applications of vehicle positioning technologies for improving road safety.     

A planning methodology for intelligent urban transportation systems

Recent developments in intelligent transportation systems pose new challenges and opportunities for urban transportation planning. To meet these challenges and to exploit these opportunities, a framework for a new transportation planning methodology has been developed. The methodology operates in a computer environment, called PLANiTS (Planning and Analysis Integration for Intelligent Transportation Systems), designed to facilitate the entire planning process form problem identification, through idea generation and analysis, on to prioritization and programming. To assist in problem identification, PLANiTS provides graphic representation of current conditions, including traffic, air pollution, accidents, and projections of future conditions. A computerized knowledge base, containing information about possible strategies and their effects, and a model base, containing transportation and other analysis models, are used to guide the user in identifying potentially effective strategies and performing the appropriate analysis. To facilitate the use of these tools, PLANiTS provides computer support of group processes such as brainstorming, deliberation, and consensus seeking. PLANiTS is designed for use in urban transportation planning at the local, regional, and state levels; it is intended to support a variety of participants in the planning process including transportation professionals, decision makers in transportation agencies (often local elected officials), citizens, and interest groups. Recognizing that transportation planning is essentially a deliberative, political process, PLANiTS is designed to inform and facilitate, but not replace, the political decision-making process.     

The evolution of urban traffic control: changing policy and technology

Abstract

The history of urban traffic control (UTC) throughout the past century has been a continued race to keep pace with ever more complex policy objectives and consistently increasing vehicle demand. Many benefits can be observed from an efficient UTC system, such as reduced congestion, increased economic efficiency and improved road safety and air quality.

There have been significant advances in vehicle detection and communication technologies which have enabled a series of step changes in the capabilities of UTC systems, from early (fixed time) signal plans to modern integrated systems. A variety of UTC systems have been implemented throughout the world, each with individual strengths and weaknesses; this paper seeks to compare the leading commercial systems (and some less well known systems) to highlight the key characteristics and differences before assessing whether the current UTC systems are capable of meeting modern transport policy obligations and desires.

This paper then moves on to consider current and future transport policy and the technological landscape in which UTC will need to operate over the coming decades, where technological advancements are expected to move UTC from an era of limited data availability to an era of data abundance.     

Required navigation performance for connected and autonomous vehicles: where are we now and where are we going?

ABSTRACT

While automotive original equipment manufacturers and IT companies are developing and demonstrating self-driving cars, true autonomy will not be realised in the near future due in part to the technology readiness level of the existing systems as well as issues of ethics, security, governance and standards surrounding the implementation of autonomy for road transport. However, advances in cellular phones and networks, satellite-based positioning and communications, cloud computing, combined with a rise in the volumes of available data, allied with a reduction in their costs, offer the very real possibility of connecting vehicles, one to another and to smart city infrastructure as part of the Internet of Things (IoT). Data from connected vehicles, when combined with other information, may provide valuable intelligence to traffic managers and other stakeholders via cooperative intelligent transport system (C-ITS) platforms. Nevertheless, many issues face the implementation of a truly connected IoT in general and C-ITS in particular.     

Integrating vehicle positioning data in quality control programs in public transit: a European perspective

Abstract

The purpose of this paper was to show how vehicle positioning data collected through global positioning systems (GPS) or similar applications can be used in quality control programs of public transit operators to better assess the quality and performance of transportation services, and improve them. The paper describes the concept of the integration between quality control programs and vehicle monitoring systems, presents a case study where the concept has been successfully implemented, and discusses the benefits from the adoption of such an approach. The implementation of the concept is characterized by efficiency, accuracy, reliability, and optimization: efficiency in terms of data flow; accuracy and reliability in terms of quality and performance indicator values; and optimization in terms of optimum use of the available information technology infrastructure. The paper places particular emphasis on aspects relating to the interface between urban transportation services, vehicle positioning technology, and policy-making.     

Dynamic pricing and reservation for intelligent urban parking management

Despite rapid advances of information technologies for intelligent parking systems, it remains a challenge to optimally manage limited parking resources in busy urban neighborhoods. In this paper, we use dynamic location-dependent parking pricing and reservation to improve system-wide performance of an intelligent parking system. With this system, the parking agency is able to decide the spatial and temporal distribution of parking prices to achieve a variety of objectives, while drivers with different origins and destinations compete for limited parking spaces via online reservation. We develop a multi-period non-cooperative bi-level model to capture the complex interactions among the parking agency and multiple drivers, as well as a non-myopic approximate dynamic programming (ADP) approach to solve the model. It is shown with numerical examples that the ADP-based pricing policy consistently outperforms alternative policies in achieving greater performance of the parking system, and shows reliability in handling the spatial and temporal variations in parking demand.     

Driver information systems — A North American perspective

Driver information systems (DIS) are considered in North America as a major category of Intelligent Vehicle-Highway Systems (IVHS), which offers to improve the efficiency and safety of driving by means of an amalgamation of information technology with vehicle and highway technologies. Traditionally North America has basic strengths in a number of information technologies that are relevant to DIS. Due to a hiatus in federal funding in the early 1980s, DIS development in North America during the past decade has emphasized autonomous systems on the vehicles until recently. The current acceleration of IVHS development in the United States has resulted from a number of converging forces and has provided the impetus for developing advanced driver information systems (ADIS) that integrates the vehicle and the highway. Large-scale demonstration and implementation of ADIS will hinge on the major legislations in the near future, and on the successful development of public-private sector partnerships in IVHS.     

基于综合科技的智能交通实训系统的研制

文章介绍了集机械、液压、电子、光学、控制、计算机、传感器、PLC、信息采集等多学科技术于一体的智能交通实训系统的技术原理,阐述了所研制的基于综合科技的智能交通实训系统各子系统的组成、运作方式及教学用途。     

RFID车辆信息管理框架研究

随着智能交通和计算机技术的发展,RFID技术越来越广泛地应用在交通系统中。然而这些系统多采用集中方式进行管理,不利用车辆数量扩展和RFID技术的大规模应用。并且各系统之间兼容性较差,难以实现信息共享。对RFID车辆信息管理框架进行了研究,以EPC和ONS为基础,提出了一种适合车辆信息管理的分布式框架及相应查询机制,并对其进行了分析。     

An integrated solution for lane level irregular driving detection on highways

Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles.     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.