Online ISSN
1751-9578
Print ISSN
1751-956X
IET Intelligent Transport Systems
Volume 6, Issue 2, June 2012
Volumes & issues:
Volume 6, Issue 2
June 2012
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- Author(s): H. Al-Deek ; T.W.P. Lochrane ; C.V. Srinivasa Ravi Chandra ; A. Khattak
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 97 –106
- DOI: 10.1049/iet-its.2010.0163
- Type: Article
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Dynamic message signs (DMS) are electronic signs displayed on roadways, providing travel times, traffic congestion, AMBER alerts, and special events. Orlando-Orange County Expressway Authority (OOCEA) in Florida added 29 fixed DMS to their toll road network between 2006 and 2008. The research issues investigated in this study are: 1) whether use of dynamic information on toll roads is associated with route diversions, and 2) are users satisfied with the available dynamic information? The instrument used to analyse travellers' perception of DMS and traffic information was a survey conducted in Central Florida region in May 2008 using Computer Aided Telephone Interview. Respondents answered questions on knowledge of DMS on OOCEA toll roads, satisfaction with travel information provided on the network and with different aspects of messages, route diversion (revealed and stated preferences), and demographics. A multinomial logit model was estimated to quantify the odds of choosing different diversion alternative over the alternative of ‘stay’ that elucidated the differences in diversion behaviour. Results showed that factors associated with greater route diversion are longer travel times, longer delays, information sources, network familiarity, and trip characteristics. Respondents were generally satisfied with DMS. Hazard warnings and accuracy of dynamic information were deemed important for satisfaction. - Author(s): V. Huth ; R. Lot ; F. Biral ; S. Rota
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 107 –114
- DOI: 10.1049/iet-its.2011.0130
- Type: Article
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Given that intersections represent particularly hazardous situations for riders of powered two wheelers, an intelligent intersection support system has been developed. This system provides a warning whenever the rider approaches an intersection at an unsafe speed. This study reports the results of a pilot evaluation of the system from a human factors perspective. In a motorcycle simulator, the system was tested with two alternative rider interfaces: a force feedback throttle and a haptic glove. Riding with the system versions was compared with riding without support. Although the number of potentially critical situations did not decrease when using the system, the results confirm that the warnings by both system versions led to a significantly reduced approach speed to the intersection, at least in a rural scenario. The riders perceived more benefits from riding with the intersection support when the warning was transmitted by the haptic glove than when they received the alert by the force feedback throttle. Accordingly, the acceptance of the latter system version was much lower. Relevant factors for the safety potential of the intersection support system are discussed and further research needs are deduced from the limitations of the study. - Author(s): H. Ghaffarian ; M. Fathy ; M. Soryani
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 115 –123
- DOI: 10.1049/iet-its.2010.0207
- Type: Article
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Traffic management, especially in intersections, is an important part of intelligent transportation systems (ITS). In this study, a new traffic controller is proposed which removes traffic lights in intersections. The heart of the proposed controller is a simple integer linear program (ILP) code. This program manages safe driving patterns crossing a junction while it tries to maximise number of passed vehicles across the intersection. The demanded data are prepared by vehicular ad hoc networks (VANET). The proposed safe driving pattern assures the safety of moving vehicles and avoiding any accident. Simulation results show that the proposed controller performs efficiently. The average queue lengths and also tolerated delay by vehicles are far better than traditional approaches. Also, for different probabilities of output selection, the proposed approach remains stable yet. - Author(s): J.J. Blum and T.V. Mathew
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 124 –131
- DOI: 10.1049/iet-its.2011.0021
- Type: Article
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The transit route network design problem is a computationally intractable optimisation problem that seeks a set of bus routes and frequencies that minimises the operator cost while maximising passenger utility. Previous attempts to optimise this problem have used metaheuristic and heuristic techniques to find solutions that allow for a complete redesign of the transit network. In reality, however, a complete redesign of the network may encounter political resistance from existing transit users if the routes that they use are eliminated. Here, an intelligent agent optimisation system is used to optimise the transit route network redesign (TRNR) problem, which is subject to the additional constraint that existing routes in the network remain, although perhaps serviced with lower frequency. When applied to the transit network in Mumbai, India, the optimisation system found significant improvement in the route network, even when subject to these constraints. In a scenario in which the current routes were maintained with frequency of stops reduced by no more than 50%, operator cost could be improved by 18.1% while maintaining the current level of passenger utility. On the other hand, passenger utility could be improved by 5.5% at current levels of operator cost. - Author(s): S.-S. Huang
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 132 –138
- DOI: 10.1049/iet-its.2011.0048
- Type: Article
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This study presents a vision-based occupant classification method which is essential for developing a system that can intelligently decide when to turn on airbags based on vehicle occupancy. To circumvent intra-class variance, this work considers the empty class as a reference and describes the occupant class by using appearance difference rather than the traditional methods of using appearance itself. Each class in this work is modelled using a set of representative parts called patches. Each patch is represented by a Gaussian distribution. This approach successfully alleviates the mis-classification problem resulting from severe lighting change which makes the image locally overexposed or underexposed. Instead of using maximum likelihood for patch selection and estimating the parameters of the proposed generative models, the proposed method discriminatively learns models through a boosting algorithm by minimising training error. Experimental results from many videos (approximately 1 630 000 frames) from a camera deployed on a moving platform demonstrate the effectiveness of the proposed approach. - Author(s): B.X. Weis and A. Sandweg
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 139 –144
- DOI: 10.1049/iet-its.2011.0096
- Type: Article
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A new paradigm named GuideWeb for networks based on vehicle-to-vehicle (v2v) communication is presented. GuideWeb is a support network for vehicle navigation and guidance. It is constituted by the cooperation of a multitude of autonomous MapSynthesiser nodes located in vehicles. A MapSynthesiser, being the autonomous core of GuideWeb, receives over radio communication traffic flow information using information-enhanced maps (called map syntheses) from other GuideWeb participants’ MapSynthesiser. From received map syntheses and the information of its own travel route it creates a new map synthesis, which is then broadcasted. MapSynthesiser provides timely and accurate information on traffic flow and density as well as traversability everywhere within a radius of ∼100 km to a navigation system for driver assistance. MapSynthesiser cooperation is based on short-range radio communication (e.g. Wireless Local Area Network – WLAN) and/or mobile communication networks. GuideWeb deploys the simple method of broadcast for network formation and thus, avoids the time lags arising from setting up and maintaining a connection-oriented ad hoc network. By the map-based data design, data security and privacy are ensured. Therefore, GuideWeb can serve as a commercially viable introductory phase for full-fledged v2v communication networks. The lessons learned from GuideWeb deployment provide insights for a v2v network design. - Author(s): S. Trommer and A. Höltl
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 145 –152
- DOI: 10.1049/iet-its.2011.0154
- Type: Article
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Assessing the perceived usefulness of eco-driving assistance systems is of high interest for system developers and researchers in the development stage of such systems. This applies especially to systems that try to influence the driver's behaviour in everyday situations and generating their greatest benefit if regularly used. This study presents results of a survey simultaneously conducted in 11 European countries with more than 5000 respondents aiming at collecting needs and requirements for future eco-driving assistance systems. Such systems have the potential of changing driving behaviour in the long run for supporting a more fuel-efficient driving and reducing emissions caused by motorised traffic. Three different driver assistance systems are considered covering inefficiencies in pre-trip, on-trip and post-trip situations. Each system is assessed according to the factors of perceived usefulness, the expected environmental impact and the user's willingness to pay for it. The study will show that in general car drivers welcome the deployment of eco-driving assistance systems and rate them as useful. It likewise demonstrates that the acceptance of additional costs for the user is very low. - Author(s): H. Jianming ; M. Qiang ; W. Qi ; Z. Jiajie ; Z. Yi
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 153 –160
- DOI: 10.1049/iet-its.2011.0124
- Type: Article
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Accurate and real-time traffic information is the foundation of intelligent transportation systems (ITS). In general, density, velocity and flow are used to describe traffic status of certain road segment. However, these macroscopic parameters are not able to reflect detailed traffic scenarios. It is more valuable to detect traffic congestion, which can be the basis of dynamic control and real-time guidance. This study proposes a novel approach towards traffic congestion identification based on vehicle trajectories in intelligent vehicle infrastructure co-operation system (IVICS). Considering spatial–temporal trajectories as image, this study uses self-correlation to extract propagation speed of congestion wave. Based on this, this study constructs congestion template; by matching algorithm, congestion is further identified as well as its intensity. Simulations on next generation simulation (NGSim) dataset verify the effectiveness of the above methods. - Author(s): C.H. Zhao ; B.L. Zhang ; J. He ; J. Lian
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 161 –168
- DOI: 10.1049/iet-its.2011.0116
- Type: Article
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An efficient feature extraction approach for driving postures from a video camera, which consists of Homomorphic filtering, skin-like regions segmentation and contourlet transform (CT), was proposed. With features extracted from a driving posture dataset created at Southeast University (SEU), holdout and cross-validation experiments on driving posture classification were then conducted using random forests (RF) classifier. Compared with a number of commonly used classification methods including linear perceptron classifier, k-nearest-neighbour classifier and multilayer perceptron (MLP) classifier, the experiments results showed that the RF classifier offers the best classification performance among the four classifiers. Among the four predefined classes, that is, grasping the steering wheel, operating the shift gear, eating and talking on a cellular phone, the class of eating is the most difficult to classify. With RF classifier, the classification accuracies of eating are over 88% in holdout and cross-validation experiments, thus demonstrating the effectiveness of the proposed feature extraction method and the importance of RF classifier in automatically understanding and characterising driver's behaviours towards human-centric driver assistance systems. - Author(s): S. Edwards ; G. Evans ; P. Blythe ; D. Brennan ; K. Selvarajah
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 169 –176
- DOI: 10.1049/iet-its.2011.0002
- Type: Article
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This study provides an overview of CVHS and a detailed description of the contribution it can make to transport safety applications, with reference to selected experiments from the EU-funded EMMA, TRACKSS and SAVE ME projects. - Author(s): J. Guevara ; F. Barrero ; E. Vargas ; J. Becerra ; S. Toral
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 177 –186
- DOI: 10.1049/iet-its.2010.0205
- Type: Article
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The Intelligent Transportation Systems (ITS) concept has been recently introduced to define modern embedded systems with enhanced digital connectivity, combining people, vehicles and public infrastructure. The smart transducer concept has been also established by the IEEE 1451 Standard to simplify the scalability of networked electronic equipments. Both of them, smart transducers and ITS, have become a reality in the last decade. This study describes the design and implementation of an environmental wireless sensor network that characterises air quality in Asuncion, Paraguay. Mobile sensor devices in public transport vehicles provide an effective mechanism to develop an efficient solution for this characterisation. The development of the sensor network is presented and experimental results obtained for the characterisation of the proposed environmental monitoring system are provided. - Author(s): Q. Wang ; J. Hu ; J. Zhang
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 187 –196
- DOI: 10.1049/iet-its.2010.0131
- Type: Article
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Intelligent transportation systems are based on the acquisition and dissemination of traffic information timely and accurately. Wireless communication technology has made this possible. Vehicles equipped with communication module and road-side stations constitute vehicular ad hoc network (VANET), in which traffic information is collected and shared. On the basis of the most forward within radius (MFR) routing protocol, this article studies the connectivity of information propagation in inter-vehicle communication, mainly focuses on packet loss rate, packet transmission distance and effective coverage range of road-side station. We use such indicators to evaluate the performance of inter-vehicle communication for different equipped rates, wireless communication ranges and typical distributions of vehicle space headway, which can be reference in practical deployment of VANET. Simulation results are shown as well. - Author(s): B. Waterson and S. Box
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 197 –203
- DOI: 10.1049/iet-its.2010.0113
- Type: Article
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This study investigates theoretical signal control algorithms based solely on probe vehicle data. Through development of a simulation system that can model urban signalised junction control using localisation probe data from all vehicles in the local area, improvements in junction operational efficiency that result from the improved input data are demonstrated for both isolated and coordinated junctions. Results from the isolated junction scenario show that the richness of the information contained within probe vehicle data means that control algorithms based just on positions and velocities of vehicles can produce 25% reductions in average delay compared to the current standard control algorithm MOVA. Results from the twin junction scenario confirm the importance of using high-level synchronisation to coordinate closely connected junctions, achieving reductions in average delays (compared to independent control approaches) of up to 40% through a process of weighting the probe vehicle data to reflect prior stage decisions of other parts of the junction. Critical to achieving these benefits, however, is the availability of high localisation accuracy probe data, with results indicating that the levels of accuracy necessary are representative of the typical performance of current in-vehicle global positioning system units, except when those vehicles are operating in urban canyon environments. - Author(s): A. Khattak ; X. Wang ; H. Zhang
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 204 –214
- DOI: 10.1049/iet-its.2011.0013
- Type: Article
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Unreliability of travel times in urban areas is partly caused by traffic incidents. Traffic operations can be further hindered by the occurrence of secondary incidents and associated traffic delays. Understanding the characteristics of incidents that occur on urban freeways and forecasting their impacts can help decision-makers select better operational strategies. Using roadway inventory and traffic incident data provided by the Hampton Roads Traffic Operations Center, this study analyses traffic incidents and presents an online tool (called iMiT-incident management integration tool) that can dynamically predict incident durations, secondary incident occurrence and associated incident delays. This prediction tool was developed based on rigorous statistical models for incident duration and secondary incident occurrence, and uses a theoretically based deterministic queuing model to estimate associated delays; iMiT relies on available inputs about the roadway conditions, and incoming incident information, for example, location, time of day and weather conditions. It can aid incident management by generating information about primary and secondary incidents and help effectively assign incident management resources. - Author(s): A. Ramezani ; B. Moshiri ; A.R. Kian ; B.N. Aarabi ; B. Abdulhai
- Source: IET Intelligent Transport Systems, Volume 6, Issue 2, p. 215 –222
- DOI: 10.1049/iet-its.2010.0189
- Type: Article
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In this study a distributed maximum likelihood estimator (MLE) has been presented to estimate ML function of traffic flow and mean traffic speed in a freeway. This algorithm uses traffic measurements including volume, occupancy and mean speed which gathered by some inductive loop detectors. These traffic detectors (traffic sensors) located in certain distances in the freeway network such that they establish a distributed sensor network (DSN). The presented distributed estimator has employed a distributed expectation maximisation algorithm to calculate MLE. In the E-step of this algorithm, each sensor node independently calculates local sufficient statistics by using local observations. A consensus filter is used to diffuse local sufficient statistics to neighbours and estimate global sufficient statistics in each node. In the M-step of this algorithm, each sensor node uses the estimated global sufficient statistics to update model parameters of the Gaussian mixtures, which can maximise the log-likelihood in the same way as in the standard EM algorithm. As the consensus filter only requires each node to communicate with its neighbours, the distributed algorithm is scalable and robust. A set of field traffic data from Minnesota freeway network has been used to simulate and verify the proposed distributed estimator performance.
Diversion during unexpected congestion on toll roads: the role of traffic information displayed on dynamic message signs
Intelligent intersection support for powered two-wheeled riders: a human factors perspective
Vehicular ad hoc networks enabled traffic controller for removing traffic lights in isolated intersections based on integer linear programming
Implications of the computational complexity of transit route network redesign for metaheuristic optimisation systems
Discriminatively trained patch-based model for occupant classification
GuideWeb: a conceptually infrastructure-free vehicle navigation system
Perceived usefulness of eco-driving assistance systems in Europe
Traffic congestion identification based on image processing
Recognition of driving postures by contourlet transform and random forests
Wireless technology applications to enhance traveller safety
Environmental wireless sensor network for road traffic applications
Performance evaluation of information propagation in vehicular ad hoc network
Quantifying the impact of probe vehicle localisation data errors on signalised junction control
Incident management integration tool: dynamically predicting incident durations, secondary incident occurrence and incident delays
Distributed maximum likelihood estimation for flow and speed density prediction in distributed traffic detectors with Gaussian mixture model assumption
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