Showing papers on "Intelligent transportation system published in 2011"

Data-Driven Intelligent Transportation Systems: A Survey

Abstract: For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system (D2ITS) : a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, D2ITS is trending to become a privacy-aware people-centric more intelligent system. In this paper, we provide a survey on the development of D2ITS, discussing the functionality of its key components and some deployment issues associated with D2ITS Future research directions for the development of D2ITS is also presented.

Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing

Abstract: Since traditional radar signals are “unintelligent,” regarding the amount of information they convey on the bandwidth they occupy, a joint radar and wireless communication system would constitute a unique platform for future intelligent transportation networks effecting the essential tasks of environmental sensing and the allocation of ad-hoc communication links, in terms of both spectrum efficiency and cost-effectiveness. In this paper, approaches to the design of intelligent waveforms, that are suitable for simultaneously performing both data transmission and radar sensing, are proposed. The approach is based on classical phase-coded waveforms utilized in wireless communications. In particular, requirements that allow for employing such signals for radar measurements with high dynamic range are investigated. Also, a variety of possible radar processing algorithms are discussed. Moreover, the applicability of multiple antenna techniques for direction-of-arrival estimation is considered. In addition to theoretical considerations, the paper presents system simulations and measurement results of complete “RadCom” systems, demonstrating the practical feasibility of integrated communications and radar applications.

Real-time road traffic prediction with spatio-temporal correlations

Abstract: Real-time road traffic prediction is a fundamental capability needed to make use of advanced, smart transportation technologies. Both from the point of view of network operators as well as from the point of view of travelers wishing real-time route guidance, accurate short-term traffic prediction is a necessary first step. While techniques for short-term traffic prediction have existed for some time, emerging smart transportation technologies require the traffic prediction capability to be both fast and scalable to full urban networks. We present a method that has proven to be able to meet this challenge. The method presented provides predictions of speed and volume over 5-min intervals for up to 1 h in advance.

A Review of Computer Vision Techniques for the Analysis of Urban Traffic

Abstract: Automatic video analysis from urban surveillance cameras is a fast-emerging field based on computer vision techniques. We present here a comprehensive review of the state-of-the-art computer vision for traffic video with a critical analysis and an outlook to future research directions. This field is of increasing relevance for intelligent transport systems (ITSs). The decreasing hardware cost and, therefore, the increasing deployment of cameras have opened a wide application field for video analytics. Several monitoring objectives such as congestion, traffic rule violation, and vehicle interaction can be targeted using cameras that were typically originally installed for human operators. Systems for the detection and classification of vehicles on highways have successfully been using classical visual surveillance techniques such as background estimation and motion tracking for some time. The urban domain is more challenging with respect to traffic density, lower camera angles that lead to a high degree of occlusion, and the variety of road users. Methods from object categorization and 3-D modeling have inspired more advanced techniques to tackle these challenges. There is no commonly used data set or benchmark challenge, which makes the direct comparison of the proposed algorithms difficult. In addition, evaluation under challenging weather conditions (e.g., rain, fog, and darkness) would be desirable but is rarely performed. Future work should be directed toward robust combined detectors and classifiers for all road users, with a focus on realistic conditions during evaluation.

Vehicular Channel Characterization and Its Implications for Wireless System Design and Performance

Abstract: To make transportation safer, more efficient, and less harmful to the environment, traffic telematics services are currently being intensely investigated and developed. Such services require dependable wireless vehicle-to-infrastructure and vehicle-to-vehicle communications providing robust connectivity at moderate data rates. The development of such dependable vehicular communication systems and standards requires accurate models of the propagation channel in all relevant environments and scenarios. Key characteristics of vehicular channels are shadowing by other vehicles, high Doppler shifts, and inherent nonstationarity. All have major impact on the data packet transmission reliability and latency. This paper provides an overview of the existing vehicular channel measurements in a variety of important environments, and the observed channel characteristics (such as delay spreads and Doppler spreads) therein. We briefly discuss the available vehicular channel models and their respective merits and deficiencies. Finally, we discuss the implications for wireless system design with a strong focus on IEEE 802.11p. On the road towards a dependable vehicular network, room for improvements in coverage, reliability, scalability, and delay are highlighted, calling for evolutionary improvements in the IEEE 802.11p standard. Multiple antennas at the onboard units and roadside units are recommended to exploit spatial diversity for increased diversity and reliability. Evolutionary improvements in the physical (PHY) and medium access control (MAC) layers are required to yield dependable systems. Extensive references are provided.

A Survey of Intelligent Transportation Systems

Abstract: With the rapid increase of modern economical and technical development, the Intelligent Transportation System (ITS) becomes more and more important and essential for a country. Practice shows that relying only on the construction of transport infrastructure and expansion does not fundamentally solve the existing transportation problems and sometimes it even makes such problems more severe. So every country is actively exploring ITS technology to solve traffic problems. But due to the different situations of the fund investment, current technology merit and the various traffic problems for each country, the development level of ITS and research areas are distinct. This paper focuses on the comparison and analysis of international ITS research and integrates the ITS technologies to design an integration model. We regard the traffic problem as not only a problem for individual countries, but also a global topic. Countries should improve the technology communication, update and enhance ITS techniques.

Providing accident detection in vehicular networks through OBD-II devices and Android-based smartphones

Abstract: The increasing activity in the Intelligent Transportation Systems (ITS) area faces a strong limitation: the slow pace at which the automotive industry is making cars "smarter". On the contrary, the smartphone industry is advancing quickly. Existing smartphones are endowed with multiple wireless interfaces and high computational power, being able to perform a wide variety of tasks. By combining smartphones with existing vehicles through an appropriate interface we are able to move closer to the smart vehicle paradigm, offering the user new functionalities and services when driving. In this paper we propose an Android-based application that monitors the vehicle through an On Board Diagnostics (OBD-II) interface, being able to detect accidents. Our proposed application estimates the G force experienced by the passengers in case of a frontal collision, which is used together with airbag triggers to detect accidents. The application reacts to positive detection by sending details about the accident through either e-mail or SMS to pre-defined destinations, immediately followed by an automatic phone call to the emergency services. Experimental results using a real vehicle show that the application is able to react to accident events in less than 3 seconds, a very low time, validating the feasibility of smartphone based solutions for improving safety on the road.

Towards autonomous vehicular clouds

Abstract: The dawn of the 21st century has seen a growing interest in vehicular networking and its myriad potential applications. The initial view of practitioners and researchers was that radio-equipped vehicles could keep the drivers informed about potential safety risks and increase their awareness of road conditions. The view then expanded to include access to the Internet and associated services. This position paper proposes and promotes a novel and more comprehensive vision namely, that advances in vehicular networks, embedded devices, and cloud computing will enable the formation of autonomous clouds of vehicular computing, communication, sensing, power and physical resources. Hence, we coin the term, Autonomous Vehicular Clouds (AVCs). A key features distinguishing AVCs from conventional cloud computing is that mobile AVC resources can be pooled dynamically to serve authorized users and to enable autonomy in real-time service sharing and management on terrestrial, aerial, or aquatic pathways or theatres of operations. In addition to general-purpose AVCs, we also envision the emergence of specialized AVCs such as mobile analytics laboratories. Furthermore, we envision that the integration of AVCs with ubiquitous smart infrastructures including intelligent transportation systems, smart cities, and smart electric power grids, will have an enormous societal impact enabling ubiquitous utility cyber-physical services at the right place, right time, and with right-sized resources.

Automated On-Ramp Merging System for Congested Traffic Situations

Abstract: Traffic merging in urban environments is one of the main causes of traffic congestion. From the driver's point of view, the difficulty arises along the on-ramp where the merging vehicle's driver has to discern whether he should accelerate or decelerate to enter the main road. In parallel, the drivers of the vehicles already on the major road may have to modify their speeds to permit the entrance of the merging vehicle, thus affecting the traffic flow. This paper presents an approach to merging from a minor to a major road in congested traffic situations. An automated merging system that was developed with two principal goals, i.e., to permit the merging vehicle to sufficiently fluidly enter the major road to avoid congestion on the minor road and to modify the speed of the vehicles already on the main road to minimize the effect on that already congested main road, is described. A fuzzy controller is developed to act on the vehicles' longitudinal control - throttle and brake pedals - following the references set by a decision algorithm. Data from other vehicles are acquired using wireless vehicle-to-infrastructure (V2I) communication. A system installed in the infrastructure that is capable of assessing road traffic conditions in real time is responsible for transmitting the data of the vehicles in the surrounding area. Three production vehicles were used in the experimental phase to validate the proposed system at the facilities of the Centro de Automatica y Robotica with encouraging results.

Traffic control and intelligent vehicle highway systems: a survey

Abstract: Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle highway systems (IVHS) that distribute intelligence between roadside infrastructure and vehicles and that - in particular on the longer term - are one of the most promising solutions to the traffic congestion problem. In this study, the authors present a survey on traffic management and control frameworks for IVHS. First, they give a short overview of the main currently used traffic control methods for freeways. Next, they discuss IVHS-based traffic control measures. Then, various traffic management architectures for IVHS such as PATH, Dolphin, Auto21 CDS etc. are discussed and a comparison of the various frameworks is presented. Finally, the authors sketch how existing traffic control methodologies could fit in an IVHS-based traffic control set-up. © 2011 The Institution of Engineering and Technology.

On the Effectiveness of an Opportunistic Traffic Management System for Vehicular Networks

Abstract: Road congestion results in a huge waste of time and productivity for millions of people. A possible way to deal with this problem is to have transportation authorities distribute traffic information to drivers, which, in turn, can decide (or be aided by a navigator) to route around congested areas. Such traffic information can be gathered by relying on static sensors placed at specific road locations (e.g., induction loops and video cameras) or by having single vehicles report their location, speed, and travel time. While the former approach has been widely exploited, the latter has come about only more recently; consequently, its potential is less understood. For this reason, in this paper, we study a realistic test case that allows the evaluation of the effectiveness of such a solution. As part of this process, (a) we designed a system that allows vehicles to crowd-source traffic information in an ad hoc manner, allowing them to dynamically reroute based on individually collected traffic information; (b) we implemented a realistic network-mobility simulator that allowed us to evaluate such a model; and (c) we performed a case study that evaluates whether such a decentralized system can help drivers to minimize trip times, which is the main focus of this paper. This study is based on traffic survey data from Portland, OR, and our results indicate that such navigation systems can indeed greatly improve traffic flow. Finally, to test the feasibility of our approach, we implemented our system and ran some real experiments at UCLA's C-Vet test bed.

SmartParking: A Secure and Intelligent Parking System

Abstract: Parking is costly and limited in almost every major city in the world. Innovative parking systems for meeting near-term parking demand are needed. This paper proposes a novel, secure, and intelligent parking system (SmartParking) based on secured wireless network and sensor communication. From the point of users' view, SmartParking is a secure and intelligent parking service. The parking reservation is safe and privacy preserved. The parking navigation is convenient and efficient. The whole parking process will be a non-stop service. From the point of management's view, SmartParking is an intelligent parking system. The parking process can be modeled as birth-death stochastic process and the prediction of revenues can be made. Based on the prediction, new business promotion can be made, for example, on-sale prices and new parking fees. In SmartParking, new promotions can be published through wireless network. We address hardware/software architecture, implementations, and analytical models and results. The evaluation of this proposed system proves its efficiency.

Provable Systemwide Safety in Intelligent Intersections

Abstract: The automation of driving tasks is of increasing interest for highway traffic management. The emerging technologies of global positioning and intervehicular wireless communications, combined with in-vehicle computation and sensing capabilities, can potentially provide remarkable improvements in safety and efficiency. We address the problem of designing intelligent in-tersections, where traffic lights and stop signs are removed, and cars negotiate the intersection through an interaction of centralized and distributed decision making. Intelligent intersections are representative of complex hybrid systems that are increasingly of interest, where the challenge is to design tractable distributed algorithms that guarantee safety and provide good performance. Systems of automatically driven vehicles will need an under lying collision avoidance system with provable safety properties to be acceptable. This condition raises several challenges. We need to ensure perpetual collision avoidance so that cars do not get into future problematic positions to avoid an immediate collision. The architecture needs to allow distributed freedom of action to cars yet should guard against worst-case behavior of other cars to guarantee collision avoidance. The algorithms should be tractable both computationally and in information requirements and robust to uncertainties in sensing and communication. To address these challenges, we propose a hybrid architecture with an appropriate interplay between centralized coordination and distributed freedom of action. The approach is built around a core where each car has an infinite horizon contingency plan, which is updated at each sampling instant and distributed by the cars, in a computationally tractable manner. We also define a dynamically changing partial-order relation between cars, which specifies, for each car, a set of cars whose worst-case behaviors it should guard against. The architecture is hybrid, involving a centralized component that coordinates intersection traversals. We prove the safety and liveness of the overall scheme. The mathematical challenge of accurately quantifying performance remains as a difficult challenge; therefore, we conduct a simulation study that shows the benefits over stop signs and traffic lights. It is hoped that our effort can provide methodologies for the design of tractable solutions for complex distributed systems that require safety and liveness guarantees.

Cloud Computing for Agent-Based Urban Transportation Systems

Abstract: Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to use traffic strategy agents and mass transport data effectively. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multiagent technology.

Mobility and handoff management in vehicular networks: a survey

Abstract: Mobility management is one of the most challenging research issues for vehicular networks to support a variety of intelligent transportation system (ITS) applications. The traditional mobility management schemes for Internet and mobile ad hoc network (MANET) cannot meet the requirements of vehicular networks, and the performance degrades severely due to the unique characteristics of vehicular networks (e.g., high mobility). Therefore, mobility management solutions developed specifically for vehicular networks would be required. This paper presents a comprehensive survey on mobility management for vehicular networks. First, the requirements of mobility management for vehicular networks are identified. Then, classified based on two communication scenarios in vehicular networks, namely, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, the existing mobility management schemes are reviewed. The differences between host-based and network-based mobility management are discussed. To this end, several open research issues in mobility management for vehicular networks are outlined. Copyright © 2009 John Wiley & Sons, Ltd.

A novel multi-hop clustering scheme for vehicular ad-hoc networks

Abstract: Vast applications introduced by Vehicular Ad-Hoc Networks (VANETs), such as intelligent transportation, roadside advertisement, make VANETs become an important component of metropolitan area networks. In VANETs, mobile nodes are vehicles which are equipped with wireless antennas; and they can communicate with each others by wireless communication on ad-hoc mode or infrastructure mode. Compared with Mobile Ad-Hoc Networks, VANETs have some inherent characteristic, such as high speed, sufficient energy, etc. According to previous research, clustering vehicles into different groups can introduce many advantages for VANETs. However, because a VANET is a high dynamic scenario, it is hard to find a solution to divide vehicles into stable clusters. In this paper, a novel multi-hop clustering scheme is presented to establish stable vehicle groups. To construct multi-hop clusters, a new mobility metric is introduced to represent relative mobility between vehicles in multi-hop distance. Extensive simulation experiments are run using ns2 to demonstrate the performance of our clustering scheme. To test the clustering scheme under different scenarios, both the Manhattan mobility model and the freeway mobility model are used to generate the movement paths for vehicles.

Autonomous Intersection Management: Multi-intersection optimization

Abstract: Advances in autonomous vehicles and intelligent transportation systems indicate a rapidly approaching future in which intelligent vehicles will automatically handle the process of driving. However, increasing the efficiency of today's transportation infrastructure will require intelligent traffic control mechanisms that work hand in hand with intelligent vehicles. To this end, Dresner and Stone proposed a new intersection control mechanism called Autonomous Intersection Management (AIM) and showed in simulation that by studying the problem from a multiagent perspective, intersection control can be made more efficient than existing control mechanisms such as traffic signals and stop signs. We extend their study beyond the case of an individual intersection and examine the unique implications and abilities afforded by using AIM-based agents to control a network of interconnected intersections. We examine different navigation policies by which autonomous vehicles can dynamically alter their planned paths, observe an instance of Braess' paradox, and explore the new possibility of dynamically reversing the flow of traffic along lanes in response to minute-by-minute traffic conditions. Studying this multiagent system in simulation, we quantify the substantial improvements in efficiency imparted by these agent-based traffic control methods.

Cascade Architecture for Lateral Control in Autonomous Vehicles

Abstract: Research on intelligent transport systems (ITSs) is steadily leading to safer and more comfortable control for vehicles. Systems that permit longitudinal control have already been implemented in commercial vehicles, acting on throttle and brake. Nevertheless, lateral control applications are less common in the market. Since a too-sudden turn of the steering wheel can cause an accident in a few seconds, good speed and position control of the steering wheel is essential. We present here a new cascade control architecture based on fuzzy logic controllers that emulate a human driver's behavior. The control architecture was tested on a real vehicle at different vehicle speeds. The results showed the use of a straightforward and intuitive fuzzy controller to give good performance.

Intelligent disaster management system based on cloud-enabled vehicular networks

Abstract: The importance of emergency response systems cannot be overemphasized today due to the many manmade and natural disasters in the recent years such as September 2001 and the recent Japan earthquake and tsunami disaster. The overall cost of the Japan disaster alone is estimated to have exceeded 300 billion USD. Transportation and telecommunications play a critical role in disaster response and management in order to minimize loss of human life, economic cost and disruptions. Our research is concerned with developing emergency response systems for disasters of various scales with a focus on transportation systems which exploit ICT developments. In this paper, we leverage Intelligent Transportation Systems (ITS) including VANETs (Vehicular Ad hoc Networks), mobile and Cloud computing technologies to propose an intelligent disaster management system. The system is intelligent because it is able to gather information from multiple sources and locations, including from the point of incident, and is able to make effective strategies and decisions, and propagate the information to vehicles and other nodes in real-time. The effectiveness of our system is demonstrated through modelling the impact of a disaster on a real city transport environment and comparing it with the case where our disaster management system was in place. We report great benefits derived from the adoption of our proposed system in terms of improved and balanced traffic flow and smooth evacuation.

V-Cloud: vehicular cyber-physical systems and cloud computing

Abstract: The widespread use of smart phone devices and their ubiquity has brought up new application domains. One such interesting domain is vehicular networks. Furthermore, cloud computing is a next-generation information and communication technology that is gaining popularity due to its pay-as-you-go service model. In this paper, we propose our novel V-Cloud architecture which includes vehicular cyber-physical system (VCPS), vehicle-to-vehicle network (V2V) and vehicle-to-infrastructure network (V2I) layers. Each of these layers is explained in further details. We discuss research challenges in V-Cloud domain and introduce new services to show wide potential of such intelligent transportation system to meet safety and comfort requirements for driver.

Optimization of Transit Priority in the Transportation Network Using a Genetic Algorithm

Abstract: This paper proposes a detailed formulation to optimize transit road space priority at the network level and utilizes an efficient heuristic method to find the optimum solution. Previous approaches to transit priority have a localized focus in which only limited combinations of transit exclusive lanes could be assessed. The aim of this work is to reallocate the road space between private car and transit modes so that the system is optimized. A bilevel programming approach is adapted for this purpose. The upper level involves an objective function from the system managers' perspective, whereas at the lower level, a users' perspective is modeled. To take into account the major effects of a priority provision, three models are used: 1) a modal split; 2) a user equilibrium traffic assignment; and 3) a transit assignment. A genetic algorithm (GA) approach is used, which enables the method to be applied to large networks. Application of a parallel GA is also demonstrated in the solution method, which has a considerably shorter execution time. The methodology is applied to an example network, and results are discussed. It is found that the proposed methodology can successfully consider benefits of all stakeholders in the introduction of transit lanes. Furthermore, using parallel GA enables the methodology to be used for real-world-network scale in a shorter computer processing time.

Robust Inference of Principal Road Paths for Intelligent Transportation Systems

Abstract: Over the last few years, electronic vehicle guidance systems have become increasingly more popular. However, despite their ubiquity, performance will always be subject to availability of detailed digital road maps. Most current digital maps are still inadequate for advanced applications in unstructured environments. Lack of up-to-date information and insufficient refinement of the road geometry are among the most important shortcomings. The massive use of inexpensive Global Positioning System (GPS) receivers, combined with the rapidly increasing availability of wireless communication infrastructure, suggests that large amounts of data combining both modalities will be available in the near future. The approach presented here draws on machine-learning techniques and processes logs of position traces to consistently build a detailed and fine-grained representation of the road network by extracting the principal paths followed by the vehicles. Although this work addresses the road-building problem in dynamic environments such as open-pit mines, it is also applicable to urban environments. New contributions include a fully unsupervised segmentation method for sampling roads and inferring the network topology, which is a general technique for extracting detailed information about road splits, merges, and intersections, as well as a robust algorithm that articulates these two. Experimental results with data from large mining operations are presented to validate the new algorithm.

A survey of cross-layer design for VANETs

Abstract: Recently, vehicular communication systems have attracted much attention, fueled largely by the growing interest in Intelligent Transportation Systems (ITS). These systems are aimed at addressing critical issues like passenger safety and traffic congestion, by integrating information and communication technologies into transportation infrastructure and vehicles. They are built on top of self organizing networks, known as a Vehicular Ad hoc Networks (VANET), composed of mobile vehicles connected by wireless links. While the solutions based on the traditional layered communication system architectures such as OSI model are readily applicable, they often fail to address the fundamental problems in ad hoc networks, such as dynamic changes in the network topology. Furthermore, many ITS applications impose stringent QoS requirements, which are not met by existing ad hoc networking solutions. The paradigm of cross-layer design has been introduced as an alternative to pure layered design to develop communication protocols. Cross-layer design allows information to be exchanged and shared across layer boundaries in order to enable efficient and robust protocols. There has been several research efforts that validated the importance of cross-layer design in vehicular networks. In this article, a survey of recent work on cross-layer communication solutions for VANETs is presented. Major approaches to cross-layer protocol design is introduced, followed by an overview of corresponding cross-layer protocols. Finally, open research problems in developing efficient cross-layer protocols for next generation transportation systems are discussed.

A Comprehensive approach to WSN-based ITS applications: a survey.

Abstract: In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios.

Intervehicle Transmission Rate Control for Cooperative Active Safety System

Abstract: We propose an intervehicle communication framework for the cooperative active safety system (CASS) whose operation is based on the dissemination of each vehicle's state information through a wireless network. Such a CASS requires each subject vehicle to be aware of its surroundings, particularly of the motion and position of other vehicles in its proximity. In this paper, we assume that all vehicles are equipped with onboard communication devices. In such situations, the wireless channel is simultaneously shared by a large number of vehicles, and one of the most difficult challenges in designing CASS is to maintain real-time tracking accuracy of neighboring vehicles while avoiding network congestion and failure. To address this issue, we analyze the problem that multiple scalar linear time-invariant dynamical systems track each other over a multiaccess channel, and then, we propose a rate adaptation algorithm to distributively control the self-information broadcast behavior of each vehicle. The proposed algorithm uses a closed-loop control concept and accounts for the lossy channel. Simulation results show that, if the message generation rate is dynamically adjusted in an on-demand fashion, more accurate and robust tracking performance can be achieved under various traffic conditions.