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Intelligent Transport Systems, IET

Issue 1 • Date March 2011

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Displaying Results 1 - 10 of 10
  • Vision-based detection and tracking of vehicles to the rear with perspective correction in low-light conditions

    Page(s): 1 - 10
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (391 KB)  

    In this study, the authors present a video-processing system that utilises a camera to detect and track vehicles to the rear at night. Vehicle detection is a pivotal component of camera-based advanced driver assistance systems (ADAS) such as collision warning, blind-spot monitoring and overtaking vehicle detection. When driving in dark conditions, vehicles to the rear are primarily visible by their headlamps. This system implements a low, static camera exposure to ensure headlamps appear distinct and not as enlarged bloomed regions. We further describe a method to identify vehicle headlamp pairs using region-growing thresholding and cross-correlation bilateral symmetry analysis. Images of vehicles at different yaw angles to the camera image plane, such as those turning, or engaging road bends, suffer from perspective distortion, which interferes with the symmetry between lamps. We perform a perspective transformation to correct for this, ensuring consistent detection performance throughout all road manoeuvres. False positives resulting from multiple vehicle situations are considered and addressed. Detected target vehicles are tracked using a Kalman filter which is updated by inter-frame cross-correlation. View full abstract»

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  • Vehicle infrastructure integration system using vision sensors to prevent accidents in traffic flow

    Page(s): 11 - 20
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1126 KB)  

    This study describes the development of a vision sensor for detecting shock waves which is one of the main factors of accidents in highway traffic flow. The major contributions of this research are development of vehicle tracking and detection of shock wave in saturated traffic. Moreover, realisation of a vehicle infrastructure integration (VII) system for providing arrival information of such propagation to drivers is proposed. The experiment on the analysis of the propagation with the developed image sensor has shown that an error might occur in the arrival time information of the propagation provided to the driver. Therefore a prediction technique at the arrival time of the propagation is integrated in the authors' system. By using this prediction technique and taking the error tolerance of drivers into account, the experimental results show that prediction success rates are improved by about 5%. View full abstract»

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  • Using real-world data to calibrate a driving simulator measuring lateral driving behaviour

    Page(s): 21 - 31
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (873 KB)  

    This study presents the development of a driving simulator for studying lateral driving behaviour to support the development of lateral active safety systems. A comparative analysis was carried out of the differences in lateral driving behaviour in the driving simulator and in the real-world environment. Based on the analysis, the authors proposed a model that enables the driving simulator to be used for the study of lateral driving behaviour in replacement of the instrumented vehicle in real traffic. The model can be considered reliable after further four driver's tests. The research results show that the developed driving simulator, after calibration using the real-world tests, provides an adequate (with a 10% margin of error) evaluation and analysis tool for the development of in-vehicle lateral safety systems. View full abstract»

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  • Speed-measurement model utilising embedded triple-loop sensors

    Page(s): 32 - 37
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (463 KB)  

    Vehicle speed is an important parameter in the measurement of road traffic. At present, double-loop sensors are generally used for vehicular speed measurement. However, these sensors incur errors caused by scanning time, spacing between double loops, irregular vehicle trajectories and the presence of multiple vehicles in the detection zone. In this study, the authors suggest a new model for vehicular speed measurement that uses a set of triple-loop sensors and an error-filtering algorithm to improve the accuracy of speed measurements. In the field tests performed in this study, all percentage errors of vehicular speeds measured by the proposed model were within the limit of error tolerance (±5%). Moreover, the variance of percentage errors was reduced. Consequently, the proposed model significantly improves the measuring accuracy of vehicle speed. View full abstract»

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  • Traffic control and intelligent vehicle highway systems: a survey

    Page(s): 38 - 52
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (459 KB)  

    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. View full abstract»

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  • Ecological interface design inspired human machine interface for advanced driver assistance systems

    Page(s): 53 - 59
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (297 KB)  

    The development and evaluation of an integrated advisory interface for several advanced driver assistance systems (ADAS) is focused here. It was developed using an ecological interface design (EID) approach and was combined with the type of auditory warnings used in vehicles today to investigate multiple-staged warnings. The warning combination was evaluated using a fixed-base medium-fidelity driving simulator. The results suggest that the development of driver interfaces based on EID could benefit by being combined with the iterative nature of the user-centred design methods to make accurate assumptions on how the design is suitable for end-users in the context of use. Simulator results also show that participants drove with greater safety margins to lead vehicles and maintained better lateral positioning when driving with the interface, indicating that integrated multiple-staged warnings can have a positive effect on driver behaviour if correctly designed. View full abstract»

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  • Limitations of positioning systems for developing digital maps and locating vehicles according to the specifications of future driver assistance systems

    Page(s): 60 - 69
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (668 KB)  

    Some advanced driver assistance systems require on-the-lane vehicle positioning on accurate digital maps. The combination of high precision global navigation satellite systems and inertial measurement is the most common technique to carry out this precise positioning since in some areas global positioning systems (GPS) signals are lost or degraded. However, real experimental validation of the navigation algorithms (beyond simulation) is one of the most important shortcomings in the state-of-the-art. In this study, a wide set of real experiments have been carried out on real roads, in urban and rural environments, using an instrumented car. A theoretical approach based on the uncertainty propagation law has been set out to evaluate the errors when using only inertial measurement systems and the maximum distance that can be travelled before exceeding the admissible error limits. Results show that it is better to correct GPS positioning when its signal is degraded than to wait until the signal is definitively lost. Furthermore, inertial measurement systems and GPS receivers of different levels of accuracy have been compared in order to determine whether they are suitable for new assistance applications. Experimental data are consistent with the theoretical approach. View full abstract»

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  • Agent-based approach to model commuter behaviour's day-to-day dynamics under pre-trip information

    Page(s): 70 - 79
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (737 KB)  

    This study reports on the tentative use of a multi-agent micro-simulation framework to address the issue of assessing commuter behaviour's day-to-day dynamics under pre-trip information. A Bayesian updating model is adopted to capture the reasoning mechanism by which commuters update their travel time perceptions from one day to the next in light of information and their previous experience. The population of commuters is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. The reasoning mechanism of commuters is modelled by means of a Belief, Desire and Intention architecture, which has been a central theme in the multi-agent systems literature since the early 1990s. Each part of this architecture is specified by a multi-agent programming language named as AgentSpeak (L). A simple simulation scenario was devised using a combination of Jason (a multi-agent simulator) and Paramics (a traffic simulator). The simulation results show that the overall performance of the system is very likely affected by exogenous information and personal travel experiences; also, accurate information can greatly affect driver's switching activities and improve daily commuting conditions. Moreover, the combination of micro-simulation and agent-based modelling technique shows a great potential to represent more realistic and more complex driver's behaviour under intelligent transport system environment. View full abstract»

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  • Potential for in-car speed assistance systems: results of a large-scale survey in Belgium and the Netherlands

    Page(s): 80 - 89
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (698 KB)  

    Speeding is generally considered to be a major cause of road traffic accidents. In-car speed assistance systems aim at reducing speeding. Several trials with different types of in-car speed assistance systems, in particular intelligent speed assistance (ISA), have shown that ISA can be an effective way to reduce speeding. A basic condition for achieving significant improvements in safety involves the adaptation of ISA among vehicle drivers on a large scale. This study focuses on the issue of acceptability of ISA. It is based on a large-scale survey of 6370 individuals in Belgium (Flanders region) and 1158 persons in the Netherlands. The respondents indicated that they believed that their own driving behaviour is of great influence on accidents and traffic safety, and that contextual issues like infrastructure or other drivers are less important. Almost 95% of the respondents are in favour of ISA: seven out of ten drivers state that they want to have some informative or warning system. Three out of ten drivers even wanted to go further; they indicated a preference for a restricting type of ISA. However, drivers would only choose for more restricting systems if the penetration rates of such systems in the vehicle market were high enough. View full abstract»

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  • Optimised random structure vehicular sensor network

    Page(s): 90 - 99
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (664 KB)  

    Providing proper coverage is one of the main applications of wireless sensor networks. In many working environments, it is necessary to take advantage of mobile sensor networks (MSNs), with the capability of having cooperation between sensor nodes and moving into appropriate positions, to provide the required coverage. However, in some applications such as intelligent transport system (ITS), where sensors are applied in complex dense urban environments, traditional MSN cannot properly cover the defined area. In this study, the authors study the use of a few unreserved selected cars as a vehicular sensor network (VSN) to cover a defined area and in this scenario, the sensors movements are assumed to be random from the network viewpoint. In the proposed random structure VSN, the coverage property is managed and controlled by introducing a suggested method for resource allocation and coverage control based on the real vehicle mobility model. Major advantages of this VSN are considering the real car mobility model, compatibility with the deployed infrastructure and processing simplicity and efficiency. The implementation results of suggested method verify the analytical results that are mentioned in the simulation section. View full abstract»

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Aims & Scope

IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of intelligent transport systems and infrastructures.

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