Special issue on intelligent transportation systems,big data and intelligent technology

ABSTRACT

Based on the increasing demands of transportation development, the concept of an Intelligent Transportation System (ITS) has received increasing attention in both academic and industry arenas. It integrates information, communications, computers and other technologies, and applies them in the field of transportation to build an integrated system of people, roads and vehicles by utilizing advanced data communication technologies. It can establish a large, fully functioning, real-time, accurate and efficient transportation management system. Intelligent transportation systems shift the focus from road managers to road users. In order to achieve this purpose, intelligent transportation systems use advanced technology to provide drivers with convenient information to help reduce traffic congestion and to increase available road capacity. This special issue is dedicated to exploring the most recent advances in intelligent transportation systems and big data based on intelligent technology.     

Behavioral monitoring of public transport users through a mobile communication system

There are various activities now taking place in ITS research and development in Japan. Advanced information and communication technologies have been applied to improve public transport systems, as well as automated highway systems. In the first part of this paper, we show three examples of public transport systems recently developed in ITS environment. These transport systems are operated in local cities and towns in Japan: the travel information system for tram users in Hiroshima, the demand responsive bus system in Nakamura and the co‐operative use of electric vehicle in Ebina. In the second part of the paper, we explain how we have monitored individual passenger on public transport using cellular phones for location positioning. Location positioning technology for mobile object is essential for the operation and management of ITS supported public transport systems. Furthermore, such accurate and detailed positioning data can be utilized for travel behaviour analysis in demand modeling. The mobile instrument and monitoring systems shown in this paper can be combined with any of the case studies of ITS application to public transport systems.     

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

Recent developments of information and communication technologies (ICT) have enabled vehicles to timely communicate with each other through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Nevertheless, unreliable vehicular communications also introduce packet loss and transmission delay when vehicular kinetic information or control commands are disseminated among vehicles, which brings more challenges in the system modeling and optimization. Currently, no data has been yet available for the calibration and validation of a model for ITS, and most research has been only conducted for a theoretical point of view. Along this line, this paper focuses on the (theoretical) development of a more general (microscopic) traffic model which enables the cooperative driving behavior via a so-called inter-vehicle communication (IVC). To this end, we design a consensus-based controller for the cooperative driving system (CDS) considering (intelligent) traffic flow that consists of many platoons moving together. More specifically, the IEEE 802.11p, the de facto vehicular networking standard required to support ITS applications, is selected as the IVC protocols of the CDS, in order to investigate how the vehicular communications affect the features of intelligent traffic flow. This study essentially explores the relationship between IVC and cooperative driving, which can be exploited as the reference for the CDS optimization and design.     

Modelling Externalities using Dynamic Traffic Assignment Models: A Review

Recently, there has been a growing interest in externalities in our society, mainly in the context of climate and air quality, which are of importance when policy decisions are made. For the assessment of externalities in transport, often the output of static traffic assignment models is used in combination with so-called effect models. Due to the rapidly increasing possibilities of using dynamic traffic assignment (DTA) models for large-scale transportation networks and the application of traffic measures, already several models have been developed to assess the externalities using DTA models more precisely. Different research projects have shown that there is a proven relation between the traffic dynamics and externalities, such as emissions of pollutants and traffic safety. This means that the assessment of external effects can be improved by using temporal information about flow, speed and density, which is the output of DTA models. In this paper, the modelling of traffic safety, emissions and noise in conjunction with DTA models is reviewed based on an extensive literature survey. This review shows that there are still gaps in knowledge in assessing traffic safety, much research is available concerning emissions, and although little research has been conducted concerning the assessment of noise using DTA models, the methods available can be used to assess the effects. Most research so far has focused on the use of microscopic models, while mesoscopic or macroscopic models may have a high potential for improving the assessment of these effects for larger networks.     

西部地区在役中小跨径桥梁承载力快速检评技术研究

《西部地区在役中小跨径桥梁承载力快速检评技术研究》项目结合国内外在役中小跨径桥梁的技术特点,本着科学、实用、创新的原则,重点研究基于可获取的模态测试数据,以达到承载能力快速评定的目的。本篇介绍了该项目的主要研究内容和研究方法,总结提炼了其研究成果和创新点,旨在使这项技术在今后中小跨径桥梁承载力评定过程中逐步取代传统的荷载试验法,并促使该技术在西部省份乃至全国范围内推广应用。     

埋地长输管道的防腐与防护

长输管道的防腐是保证管道安全运行的重要手段之一.管道防腐蚀技术已经有了很大的发展,出现了许多新的防腐蚀材料和技术,但管道的腐蚀问题仍未从根本上得到解决.文中从埋地钢质管道的腐蚀因素出发,论述了管道的防护技术,为今后的研究及发展提供了参考方向.     

Online license plate matching procedures using license-plate recognition machines and new weighted edit distance

License-plate recognition (LPR) technology has been widely applied in many different transportation applications such as enforcement, vehicle monitoring, and access control. Recently, there has been effort to exploit an LPR database for vehicle tracking using popular template matching procedures. Existing template matching procedures assume that the true reference string is always available. However, under a two-point LPR survey, a vehicle could have its plate misread at both locations generating a pair of misread strings (or templates) with no reference for matching. To compensate for LPR misreading problem, we propose a new weight function based on a probability model to match the observed outcomes of a dual LPR setup. Also, considering that reversal errors are never made in LPR machines, new editing constraints as a function of the string lengths are proposed to avoid compensation for reversal errors. These editing constraints are incorporated into the constraint edit distance formulation to improve the performance of the matching procedure. Finally, considering that previous template matching procedures do not take advantage of passage time information available in LPR databases, we present an online tracking procedure that considers the properties of probability distribution of vehicle journey times in order to increase the probability of correct matches. Experimental results show that our proposed procedure can improve the accuracy of LPR systems and achieve up to 97% of positive matches with no false matches. Further research is needed to extend the ideas proposed herein to plate-matching with multiple, i.e., more than two, LPR units.     

A three-stage decision-making model for selecting electric vehicle battery technology

This study proposes a three-stage decision-making model for the selection of electric vehicle battery technology. Data used for analysis include surveys completed by 45 technology experts from industry, academia, and research throughout Taiwan. A three-stage model that includes developing multiple-criteria during the first stage, integrating the importance of criteria assessment using the fuzzy analytical hierarchy process in the second stage, and using patent analysis tools to further identify the patent portfolio of the technology selected by experts in the third stage are employed. The empirical results indicate that power source management technology and battery module technology are the key technologies for development by the electric vehicle industry. Battery energy storage management and cooling technology are found to be the key for building patent portfolios. When faced with substantial technical and market uncertainty, multiple-criteria for research and development (R&D) selection and stage-wise integration of decision tool must be employed by battery firms to effectively allocate the resources for R&D decisions.     

Impact of interviewing by proxy in travel survey conducted by telephone

Telephone‐interview surveys are a very efficient way of conducting large‐scale travel surveys. Recent advancements in computer technology have made it possible to improve upon the quality of data collected by telephone surveys through computerization of the entire sample‐control process, and through the direct recording of the collected data into a computer. Notwithstanding these technological advancements, potential sources of bias still exist, including the reliance on an adult member of the household to report the travel information of other household members. Travel data collected in a recent telephone interview survey in the Toronto region is used to examine this issue. The statistical tool used in the research was the Analysis of Variance (ANOVA) technique as implemented within the general linear model framework in SAS. The study‐results indicate that reliance on informants to provide travel information for non‐informant members of their respective households led to the underreporting of some categories of trips. These underreported trip categories were primarily segments of home‐based discretionary trips, and non home‐based trips. Since these latter two categories of trips are made primarily outside the morning peak period, estimated factors to adjust for their underreporting were time‐period sensitive. Further, the number of vehicles available to the household, gender, and driver license status respectively were also found to be strongly associated with the underreporting of trips and thus were important considerations in the determination of adjustment factors. Work and school trips were found not to be underreported, a not surprising result giving the almost daily repetitiveness of trips made for these purposes and hence the ability of the informant to provide relatively more precise information on them.     

Construction of traffic state vector using mutual information for short-term traffic flow prediction

Short-term traffic flow prediction is an integral part in most of Intelligent Transportation Systems (ITS) research and applications. Many researchers have already developed various methods that predict the future traffic condition from the historical database. Nevertheless, there has not been sufficient effort made to study how to identify and utilize the different factors that affect the traffic flow. In order to improve the performance of short-term traffic flow prediction, it is necessary to consider sufficient information related to the road section to be predicted. In this paper, we propose a method of constructing traffic state vectors by using mutual information (MI). First, the variables with different time delays are generated from the historical traffic time series, and the spatio-temporal correlations between the road sections in urban road network are evaluated by the MI. Then, the variables with the highest correlation related to the target traffic flow are selected by using a greedy search algorithm to construct the traffic state vector. The K-Nearest Neighbor (KNN) model is adapted for the application of the proposed state vector. Experimental results on real-world traffic data show that the proposed method of constructing traffic state vector provides good prediction accuracy in short-term traffic prediction.     

An integrated sea–land transportation system model and its theory

To enhance the efficiency of intermodal transportation for large quantities of goods, the current sea–land transportation system has been reviewed and systematically analyzed, and a bottleneck is pinpointed in the linkage or goods transfer between the waterway and railway. The bottleneck impacts the efficiency of the goods through transportation combining the two modes. To eliminate the existing bottleneck and inefficiency towards intermodality, a new type of flexible double-rail track has recently been invented together with innovations both in trestle bridges and in train ferries. The outcomes of the research in progress show that the flexible double-rail track is feasible from the viewpoints of both geometry and engineering mechanics, it can be used to improve the compatibility of a trestle bridge with various types of train ferries and hence it can support the development of train ferries on a large scale. Based on the innovations, an integrated sea–land transportation system model is proposed as a systematic solution, which is expected to effectively overcome the existing bottleneck and to enhance the efficiency of the whole sea–land combined transportation. Further research on this system model and its major components is also addressed in the paper.     

Exploring ‘weak signals’' as potential challenges in transport: an inventory of potential future technology developments

This article assesses the most likely technological developments in transport, not only by investigating current innovations but also by observing different approaches to confronting future developments. The article discusses technology forecasting and the meaning of environmentally sound technologies; some insights into technology development and the relevance of technological forecasting; the factors that influence technology development in transport; and, in this context, differentiation between exploration, expectation and forecasting. It goes on to identify, from four different perspectives, major developments of strategic relevance for the transport sector that might arise in the longer term. An assessment is made of the consequences of these observations for the implementation of innovations in transport.     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

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.     

Impact of ITS measures on public transport: A Case study

Intelligent Transport Systems (ITS) have a wide range of applications. They range from the more traditional signal coordination system to concepts such as smart cars and smart roads. This paper describes transit‐based ITS measures in Singapore. The island‐state has plans to double the current 90 km rail network over the next ten years and has also implemented or committed to implement many ITS initiatives that impact upon the public transport systems. The aim of these investments is to achieve a high transit modal share using a comprehensive transit network. ITS measures that can promote this aim include: automatic vehicle location systems for buses and taxis, integrated transit fare systems using contactless smart cards, rail information systems, multi‐modal travel guides on Internet and electronic road pricing. The potential impacts of these measures are delay reduction, more comfort, productivity gain and better network accessibility. ITS measures do not necessarily add physical capacity to a public transport system but are excellent supporting measures to encourage the modal shift to transit, particularly if a quality transit system is already in place.     

Real-time trip purpose prediction using online location-based search and discovery services

The use of smartphone technology is increasingly considered a state-of-the-art practice in travel data collection. Researchers have investigated various methods to automatically predict trip characteristics based upon locational and other smartphone sensing data. Of the trip characteristics being studied, trip purpose prediction has received relatively less attention. This research develops trip purpose prediction models based upon online location-based search and discovery services (specifically, Google Places API) and a limited set of trip data that are usually available upon the completion of the trip. The models have the potential to be integrated with smartphone technology to produce real-time trip purpose prediction. We use a recent, large-scale travel behavior survey that is augmented by downloaded Google Places information on each trip destination to develop and validate the models. Two statistical and machine learning prediction approaches are used, including nested logit and random forest methods. Both sets of models show that Google Places information is a useful predictor of trip purpose in situations where activity- and person-related information is uncollectable, missing, or unreliable. Even when activity- and person-related information is available, incorporating Google Places information provides incremental improvements in trip purpose prediction.     

Comparing smart scheme effects for congested highways

A high level objective for many international governments and local operators is that highways should be managed in a way that is sustainable in terms of a Low Carbon Energy future. Recent initiatives such as the Strategic Transport Technology Plan and the policy and legal framework promoted by the European Commissions’ Intelligent Transport System (ITS) Directive and ITS Action Plan may assist with this objective. However, many levels of complexity are inherent within the (ITS) schemes that are now part of highway management, due to the linkage of various technological components to complex systems and services. Maintaining efficient, sustainable co-operative performance is therefore a major task, with inconsistencies between product suppliers, network managers and operators. As a result, it is of considerable interest to the highway operators and high level policy makers to be able to assess the performance of individual ITS schemes and furthermore, to be able to compare performance between ITS schemes. In this paper, an illustration is provided of a methodology that can be used to assess the performance of ITS schemes according to a set of sustainability criteria. A case study is introduced which compares the performance of anticipated Active Traffic Management (ATM) schemes for what the road network operator (Highways England) perceive to be the four most congested highways in England (in terms of annual average daily traffic flows). Appropriate action can then be taken to improve the energy and sustainable management of Information Communication Technology (ICT) and transport systems for the benefit of a smarter, sustainable and efficient future.     

Understanding connectivity to international markets: a systematic review

Improving freight connectivity is increasingly a topic at the centre of the international trade and transport policy agendas. An examination of available documents and studies in both the policy-making and the academic fields shows that the concept of freight connectivity has often been defined in different ways, and thus has taken a variety of meanings. This poses the question on what connectivity is and what are its determinants in the context of international trade. We are not aware of any studies that have analysed, in a systematic way, the different perspectives and determinants of freight connectivity so as to increase access to international markets. This paper seeks to fill this gap by performing a systematic literature review that spans disciplines such as Transport Engineering, Transport and International Economics, and Supply Chain Management. The outcome of this examination is a multidisciplinary framework that hopefully will help stakeholders to understand freight connectivity to international markets better, as well as guide future research and analysis in policy-making.     

Requirements from vehicle routing software: perspectives from literature,developers and the freight industry

Routing and scheduling software is part of the information and technology systems available to support the transport industry, and uses complex algorithms along with geographical representations of the road network to allow better planning of daily collection and delivery schedules. This paper reviews the evolution of routing and scheduling software, the algorithms used along with reported barriers to wider take-up and potential industry-driven improvements that could be made. A survey of transport companies in the U.K. was conducted in order to validate and prioritise the software capabilities that require the most development according to the new challenges that the industry is facing. Responses suggested that companies required improved route optimisation to tackle congestion based on time-dependent data and models, and greater accuracy in the representation of the road network. Not considering congestion leads to the underestimation of travel times and the production of inaccurate schedules. Literature shows that operational research techniques are available to solve problems that represent real-world conditions, but research into the relative merits of using time-dependent models needs to be undertaken. Data might be improved by cooperation between government and private sector.     

Experimental evaluation of CAM and DENM messaging services in vehicular communications

The Cooperative Awareness Basic Service and Decentralized Environmental Notification Basic Service have been standardized by the European Telecommunications Standards Institute (ETSI) to support vehicular safety and traffic efficiency applications needing continuous status information about surrounding vehicles and asynchronous notification of events, respectively. These standard specifications detail not only the packet formats for both the Cooperative Awareness Message (CAM) and Decentralized Environmental Notification Message (DENM), but also the general message dissemination rules. These basic services, also known as facilities, have been developed as part of a set of standards in which both ISO and ETSI describe the Reference Communication Architecture for future Intelligent Transportation Systems (ITS). By using a communications stack that instantiates this reference architecture, this paper puts in practice the usage of both facilities in a real vehicular scenario. This research work details implementation decisions and evaluates the performance of CAM and DENM facilities through a experimental testbed deployed in a semi-urban environment that uses IEEE 802.11p (ETSI G5-compliant), which is a WiFi-like communication technology conceived for vehicular communications. On the one hand, this validation considers the development of two ITS applications using CAM and DENM functionalities for tracking vehicles and disseminating traffic incidences. In this case, CAM and DENM have demonstrated to be able to offer all the necessary functionality for the study case. On the other hand, both facilities have been also validated in a extensive testing campaign in order to analyze the influence in CAM and DENM performance of aspects such as vehicle speed, signal quality or message dissemination rules. In these tests, the line of sight, equipment installation point and hardware capabilities, have been found as key variables in the network performance, while the vehicle speed has implied a slight impact.