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Intelligent Transport Systems, IET

Popular Articles (March 2015)

Includes the top 50 most frequently downloaded documents for this publication according to the most recent monthly usage statistics.
  • 1. Personal security in travel by public transport: the role of traveller information and associated technologies

    Publication Year: 2015 , Page(s): 167 - 174
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (424 KB)

    This study focuses on the role of traveller information and associated technologies in supporting personal security in travel by public transport. It reports research undertaken via a workshop involving SWOT analysis and scenario planning and a series of expert interviews. These research activities created a baseline understanding of how personal security issues are currently addressed, and identified potential future issues and how they might be tackled. Information is a major source of confidence and reassurance when travelling and can greatly support perceptions of personal security in travel. There have been significant advances in recent years in the quantity of information available and in delivery mechanisms. However, significant issues remain, particularly in terms of information quality, its representation in the public realm and its ability to support the needs of users. The differences in the relationship between information requirements and related commercial imperatives is shown to be perhaps the critical factor in determining the alternative pathways and associated services, technologies and personal security outcomes which emerge under the different scenarios. View full abstract»

    Open Access
  • 2. Routing systems to extend the driving range of electric vehicles

    Publication Year: 2013 , Page(s): 327 - 336
    Cited by:  Papers (4)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (723 KB)  

    This study develops a more accurate range prediction for electric vehicles (EVs) resulting in a routing system that could extend the driving range of EVs through calculating the minimum energy route to a destination, based on topography and traffic conditions of the road network. Energy expenditure of EVs under different conditions is derived using high-resolution real-world data from the SwitchEV trial. The SwitchEV trial has recorded the second-by-second driving events of 44 all-electric vehicles covering a distance of over 400 000 miles across the North East of England, between March 2010 and May 2013. Linear models are used to determine the energy expenditure equations and Dijkstra's graph search algorithm is used to find the route minimising energy consumption. The results from this study are being used to better inform the decisions of the smart navigation and eco-driving assist systems in EVs, thus improving the intelligent transport systems provisions for EV drivers. The outputs of the research are twofold: providing more accurate estimations of available range and supporting drivers' optimisation of energy consumption and as a result extending their driving range. Both outputs could help mitigate range anxiety and make EVs a more attractive proposition to potential customers. View full abstract»

    Open Access
  • 3. Video-based traffic data collection system for multiple vehicle types

    Publication Year: 2014 , Page(s): 164 - 174
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (897 KB)  

    Traffic data of multiple vehicle types are important for pavement design, traffic operations and traffic control. A new video-based traffic data collection system for multiple vehicle types is developed. By tracking and classifying every passing vehicle under mixed traffic conditions, the type and speed of every passing vehicle are recognised. Finally, the flows and mean speeds of multiple vehicle types are output. A colour image-based adaptive background subtraction is proposed to obtain more accurate vehicle objects, and a series of processes like shadow removal and setting road detection region are used to improve the system robustness. In order to improve the accuracy of vehicle counting, the cross-lane vehicles are detected and repeated counting for one vehicle is avoided. In order to reduce the classification errors, the space ratio of the blob and data fusion are used to reduce the classification errors caused by vehicle occlusions. This system was tested under four different weather conditions. The accuracy of vehicle counting was 97.4% and the error of vehicle classification was 8.3%. The correlation coefficient of speeds detected by this system and radar gun was 0.898 and the mean absolute error of speed detection by this system was only 2.3 km/h. View full abstract»

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  • 4. Architecture for parking management in smart cities

    Publication Year: 2014 , Page(s): 445 - 452
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (466 KB)  

    Parking is becoming an expensive resource in almost any major city in the world, and its limited availability is a concurrent cause of urban traffic congestion, and air pollution. In old cities, the structure of the public parking space is rigidly organised and often in the form of on-street public parking spots. Unfortunately, these public parking spots cannot be reserved beforehand during the pre-trip phase, and that often lead to a detriment of the quality of urban mobility. Addressing the problem of managing public parking spots is therefore vital to obtain environmentally friendlier and healthier cities. Recent technological progresses in industrial automation, wireless network, sensor communication along with the widespread of high-range smart devices and new rules concerning financial transactions in mobile payment allow the definition of new intelligent frameworks that enable a convenient management of public parking in urban area, which could improve sustainable urban mobility. In such a scenario, the proposed intelligent parking assistant (IPA) architecture aims at overcoming current public parking management solutions. This study discusses the conceptual architecture of IPA and the first prototype-scale simulations of the system. View full abstract»

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  • 5. Autonomous collision avoidance system based on accurate knowledge of the vehicle surroundings

    Publication Year: 2015 , Page(s): 105 - 117
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1128 KB)

    In this study, a collision avoidance system is presented, based on the information provided by a laser-scanner sensor, in which two actions could be taken in case of danger. Firstly, the system tries to stop the vehicle in order to avoid the accident. If a reduction in speed is not sufficiently effective, the control system takes control of the steering and deviates the vehicle's trajectory in order to escape from the hazardous situation. The control system evaluates the situation and decides the most appropriate action in each case considering free areas on the surroundings using the information of a detailed digital map. This system has been implemented in a vehicle and has been tested with pedestrians and vehicles circulating along the private test track with satisfactory results. View full abstract»

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  • 6. On creating vision-based advanced driver assistance systems

    Publication Year: 2015 , Page(s): 59 - 66
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (411 KB)

    In this study, the authors analyse the exponential growth of advanced driver assistance systems based on video processing in the past decade. Specifically, they focus on how research and innovative ideas can finally reach the market as cost-effective solutions. They explore well-known computer vision methods for services like lane departure warning systems, collision avoidance systems and point out potential future trends according to a review of the state-of-the-art. Along this study, the authors' own contributions are described as examples of such systems from the perspective of real-time by design, pursuing a trade-off between the accuracy and reliability of the designed algorithms and the restrictive computational, economical and design requisites of embedded platforms. View full abstract»

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  • 7. Multi-model direct generalised predictive control for automatic train operation system

    Publication Year: 2015 , Page(s): 86 - 94
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (437 KB)

    The authors propose a novel multi-model direct generalised predictive control based on predictive function control (PFC) algorithm for automatic train operation system. The proposed method facilitates autonomous driving of a train through a given guidance trajectory. Firstly, they present a multi-model architecture based on fuzzy c-means clustering algorithm. In order to obtain the optimal number of sub-linear models, they apply Xie-Beni cluster validity index. In this regards, the multi-model set is established off-line. Secondly, the proper sub-linear model is selected as the predictive model by using switching performance index at each time slot. The control variables are calculated by direct generalised predictive controller based on PFC. The control algorithm is simple, and can reduce the on-line computation time by directly identifies the unknown parameters in the controller. It can avoid recursively solving the Diophantine equations. The calculation of compensation value becomes simple by introducing PFC. Finally, simulation results are provided to show the effectiveness of the proposed scheme. View full abstract»

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  • 8. Required range of electric vehicles – an analysis of longitudinal mobility data

    Publication Year: 2015 , Page(s): 119 - 127
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (477 KB)

    Conventional cars allow their users to decide about a journey's modalities largely independent. Electric vehicles (EVs) also must ensure this to be a real substitute from the user's point of view. This study focuses on range as a crucial technical feature of EVs. Many of the existing studies underestimate range requirements, as they are based on (i) one-day analyses and on (ii) mean values of daily trip distances. These data are not appropriate to answer questions on user needs; longitudinal mobility data are more suitable. This study analyses both, existing mobility data and new recorded global positioning system (GPS) data with regard to range requirements. Particularly, it was analysed whether or not identified daily driving cycles can be fulfilled with EVs assuming different charging opportunities. The analysis shows that GPS-recorded driving cycles of 80% of small-scale vehicles, 67% of midsized vehicles and 40% of sport utility vehicles can be realised with EVs. View full abstract»

    Open Access
  • 9. Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel

    Publication Year: 2014 , Page(s): 43 - 50
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (525 KB)  

    Real time driver health condition monitoring system with drowsiness alertness was proposed. A new embedded electrocardiogram (ECG) sensor with electrically conductive fabric electrodes on the steering wheel of a car was designed to monitor the driver's health condition. The ECG signals were measured at a sampling rate of 100 Hz from the driver's palms as they stay on a pair of conductive fabric electrodes located on the steering wheel. Practical tests were conducted using an embedded ECG sensor with a wireless sensor node, and their performance was assessed under non-stop 2 h driving test. The ECG signals were measured and transmitted wirelessly to a base station connected to a server PC in personal area network environment. The driver's health condition such as the normal, fatigued and drowsy states was analysed by evaluating the heart rate variability in the time and frequency domains. View full abstract»

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  • 10. Active collision avoidance system for steering control of autonomous vehicles

    Publication Year: 2014 , Page(s): 550 - 557
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (556 KB)  

    The study proposes an active collision avoidance system to allow safe lane-changing manoeuvres by self-steering vehicles in the presence of the uncertainties associated with nearby vehicles and the surrounding environment. This system integrates estimation of conflict probability, model predictive control and dedicated short-range communications (DSRC) techniques to ensure a collision-free operation. To accomplish this, the proposed system uses model predictive control to predict the future positions of vehicles and estimates the conflict probability so as to reduce the risk of collision. The system also exploits DSRC techniques to facilitate the gathering of information from nearby vehicles so that potential conflicts can be detected at an earlier stage. Autonomous vehicles can thus make adjustments based on the acquired data to avoid collisions in a real communication environment. The effectiveness of the method has been verified under experimental conditions. The influences of key parameters in the control method are examined. View full abstract»

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  • 11. Monovision-based vehicle detection, distance and relative speed measurement in urban traffic

    Publication Year: 2014 , Page(s): 655 - 664
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (721 KB)

    This study presents a monovision-based system for on-road vehicle detection and computation of distance and relative speed in urban traffic. Many works have dealt with monovision vehicle detection, but only a few of them provide the distance to the vehicle which is essential for the control of an intelligent transportation system. The system proposed integrates a single camera reducing the monetary cost of stereovision and RADAR-based technologies. The algorithm is divided in three major stages. For vehicle detection, the authors use a combination of two features: the shadow underneath the vehicle and horizontal edges. They propose a new method for shadow thresholding based on the grey-scale histogram assessment of a region of interest on the road. In the second and third stages, the vehicle hypothesis verification and the distance are obtained by means of its number plate whose dimensions and shape are standardised in each country. The analysis of consecutive frames is employed to calculate the relative speed of the vehicle detected. Experimental results showed excellent performance in both vehicle and number plate detections and in the distance measurement, in terms of accuracy and robustness in complex traffic scenarios and under different lighting conditions. View full abstract»

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  • 12. Fuzzy-based blended control for the energy management of a parallel plug-in hybrid electric vehicle

    Publication Year: 2015 , Page(s): 30 - 37
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (413 KB)

    The growing interest in reducing fuel consumption and gas emissions provides an incentive for the automotive industry to innovate in the field of hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). The two embedded power sources in these vehicles require an intelligent controller in order to make the best decision on the power distribution. Actually these controllers, often called energy management systems, are very important and greatly influence the achievable fuel economy. Compared with an HEV, a PHEV allows battery discharge over a complete trip. As a consequence the optimal control of a PHEV implies a stronger dependence on the total driving cycle. Many authors have studied the possibility of fuzzy-based systems for both HEV and PHEV as they have proved to be robust, reliable and simple. However, classical fuzzy rule-based strategies demonstrate a lack of optimality because their design is focused on the actual vehicle state rather than the driving conditions. This study proposes a blended control strategy based on fuzzy logic for a PHEV. The proposed controller is fed with driving condition information in order to increase the controller effectiveness in every situation. The efficiency of the proposed controller is demonstrated through simulations. View full abstract»

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  • 13. Segmentation of vehicle detector data for improved k-nearest neighbours-based traffic flow prediction

    Publication Year: 2015 , Page(s): 264 - 274
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (845 KB)

    This study presents a data segmentation method, which was intended to improve the performance of the k-nearest neighbours algorithm for making short-term traffic volume predictions. According to the introduced method, selected segments of vehicle detector data are searched for records similar to the current traffic conditions, instead of the entire database. The data segments are determined on the basis of a segmentation procedure, which aims to select input data that are useful for the prediction algorithm. Advantages of the proposed method were demonstrated in experiments on real-world traffic data. Experimental results show that the proposed method not only improves the accuracy of the traffic volume prediction, but also significantly reduces its computational cost. View full abstract»

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  • 14. Method for estimating the energy consumption of electric vehicles and plug-in hybrid electric vehicles under real-world driving conditions

    Publication Year: 2013 , Page(s): 138 - 150
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (968 KB)  

    This study presents a novel framework by which the energy consumption of an electric vehicle (EV) or the zero-emissions range of a plug-in hybrid electric vehicle (PHEV) may be predicted over a route. The proposed energy prediction framework employs a neural network and may be used either `off-line' for better estimating the real-world range of the vehicle or `on-line' integrated within the vehicle's energy management control system. The authors propose that this approach provides a more robust representation of the energy consumption of the target EVs compared to standard legislative test procedures. This is particularly pertinent for vehicle fleet operators that may use EVs within a specific environment, such as inner-city public transport or the use of urban delivery vehicles. Experimental results highlight variations in EV range in the order of 50% when different levels of traffic congestion and road type are included in the analysis. The ability to estimate the energy requirements of the vehicle over a given route is also a pre-requisite for using an efficient charge blended control strategy within a PHEV. Experimental results show an accuracy within 20-30% when comparing predicted and measured energy consumptions for over 800 different real-world EV journeys. View full abstract»

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  • 15. Short-term forecasting of available parking space using wavelet neural network model

    Publication Year: 2015 , Page(s): 202 - 209
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (473 KB)

    The technique to forecast available parking spaces (APSs) is the foundation theory of parking guidance information systems (PGISs). This study utilises data collected on parking availability at several off-street parking garages in Newcastle upon Tyne, England, to investigate the changing characteristics of APS. Using these baseline data the research reported here aims to build up a short-term APS forecasting model and applies the wavelet neural network (WNN) method to the PGIS problem. After selecting optimal preferences, including training set size, delay time and embedding dimension, the APS short-term forecasting model based on WNN is built and tested using the real-world dataset. By experimental tests conducted using the same dataset, WNN's prediction performance is compared with the largest Lyapunov exponents (LEs) method in the aspects of accuracy, efficiency and robustness. It is found that WNN prevails through a more efficient structure and employs, barely half of the computational cost compared to the largest LEs method, which could be significant if applied to real-time operation. Moreover, WNN enjoys a more accurate performance, for its prediction average mean square error (MSE) is 6.4 ± 3.1 (in a parking building with 492 parking lots) for workdays and 8.5 ± 6.2 for weekends, compared to the MSE of largest LEs method, 18.7 and 29.0, respectively. View full abstract»

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  • 16. A framework for real-time emissions trading in large-scale vehicle fleets

    Publication Year: 2015 , Page(s): 275 - 284
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (602 KB)

    In this study a framework for the real-time trading of budgeted emission rights between a fleet of participating vehicles is presented. The trading problem is formulated as a utility maximisation or as a utility fairness problem, which can be solved in real time either in a centralised or in a distributed manner. In both cases, the authors illustrate the basic issues that arise when such a framework is realised in practice, and they show the efficacy of the approaches by providing several simulation examples and a realistic case study. View full abstract»

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  • 17. Night-time pedestrian classification with histograms of oriented gradients-local binary patterns vectors

    Publication Year: 2015 , Page(s): 75 - 85
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (653 KB)

    The use of night vision systems in vehicles is becoming increasingly common, not just in luxury cars but also in the more cost sensitive sectors. Numerous approaches using infrared sensors have been proposed in the literature to detect and classify pedestrians in low visibility situations. However, the performance of these systems is limited by the capability of the classifier. This paper presents a novel method of classifying pedestrians in far-infrared automotive imagery. Regions of interest are segmented from the infrared frame using seeded region growing. A novel method of filtering the region growing results based on the location and size of the bounding box within the frame is described. This results in a smaller number of regions of interest for classification, leading to a reduced false positive rate. Histograms of oriented gradient features and local binary pattern features are extracted from the regions of interest and concatenated to form a feature for classification. Pedestrians are tracked with a Kalman filter to increase detection rates and system robustness. Detection rates of 98%, and false positive rates of 1% have been achieved on a database of 2000 images and streams of video; this is a 3% improvement on previously reported detection rates. View full abstract»

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  • 18. Robust detection system of illegal lane changes based on tracking of feature points

    Publication Year: 2013 , Page(s): 20 - 27
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (890 KB)  

    This study proposes a robust real-time system to detect vehicles that change lanes illegally based on tracking feature points. The algorithm in the system does not need to switch depending on the illumination conditions, such as day and night. The camera is assumed to be heading in the opposite direction to the traffic flow. Before starting, the system manager should initially designate several regions that are utilised for detection. Then, the proposed algorithm consists of three stages, such as extracting feature points of corners, tracking the feature points attached to vehicles and detecting a vehicle that violates legal lane changes. For the feature extraction stage, the authors used a robust and fast algorithm that can provide stable corners without distinguishing between day and night or weather conditions. Salient points are selected among the corner points for registration and tracking. Normalised cross-correlation is used to track the registered feature points. Finally, illegal change-of-lane is determined by the information obtained from the tracked corners without grouping them for segmentation. The proposed system showed excellent performance in terms of the accuracy and the computation speed. View full abstract»

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  • 19. Vision-based detection and tracking of vehicles to the rear with perspective correction in low-light conditions

    Publication Year: 2011 , Page(s): 1 - 10
    Cited by:  Papers (5)
    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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  • 20. Clustering multi-hop information dissemination method in vehicular ad hoc networks

    Publication Year: 2013 , Page(s): 464 - 472
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (960 KB)  

    As a special case of mobile ad hoc networks, vehicular ad hoc networks (VANETs) have attracted great interest in the research community. With the help of wireless communication, many of the safety related and non-safety related applications can be realised in VANETs. In the multi-hop and dynamic topology networks, building and maintaining a route is very challenging. To disseminate information among the vehicles and the infrastructures efficiently, a position-based clustering multi-hop routing method is proposed. The method hierarchically organises VANETs based on the competitive learning Hebb neural network, which partitions the vehicles into clusters, and these clusters are represented by virtual cluster-heads. The method is evaluated using NS2 and compared with typical ad hoc routing protocol Ad hoc On-Demand Distance Vector, Distance Routing Effect Algorithm for Mobility. The simulation results prove that the method is efficient. View full abstract»

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  • 21. Cost effective railway signalling by wireless communication among onboard controllers and switch controllers

    Publication Year: 2015 , Page(s): 67 - 74
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (401 KB)

    The signalling system is one of the most costly systems in the railway infrastructure. The cost of the trackside controllers is particularly high because high-performance failsafe hardware and software are needed to supervise and control the many pieces of the field equipment. A signalling system is described that has a lower projected cost because of the application of the traditional token block mechanism to the virtual blocks dividing each controlled section. Its basic mechanism is the sharing by the wireless communication of the information about the exclusive rights with the virtual blocks, the status of the switches and the instructions for controlling the switches in the controlled section among the onboard controllers and the switch controllers, respectively. A telegram for each controlled section is circulated in turn among these controllers for the sharing. This mechanism provides an automatic train protection and an interlocking function without using the trackside controllers. Its application to a very high-density line might reduce the train operation density because of the telegram circulation time, but the reduction would be no greater than 20% on the highest density line if the current radio technology was used. A cost evaluation based on a 20-km double-track line showed that this system is about three times more cost effective than the communication-based train control system. View full abstract»

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  • 22. A Gaussian mixturemodel and support vector machine approach to vehicle type and colour classification

    Publication Year: 2014 , Page(s): 135 - 144
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (859 KB)  

    The authors describe their approach to segmenting moving road vehicles from the colour video data supplied by a stationary roadside closed-circuit television (CCTV) camera and classifying those vehicles in terms of type (car, van and heavy goods vehicle) and dominant colour. For the segmentation, the authors use a recursively updated Gaussian mixture model approach, with a multi-dimensional smoothing transform. The authors show that this transform improves the segmentation performance, particularly in adverse imaging conditions, such as when there is camera vibration. The authors then present a comprehensive comparative evaluation of shadow detection approaches, which is an essential component of background subtraction in outdoor scenes. For vehicle classification, a practical and systematic approach using a kernelised support vector machine is developed. The good recognition rates achieved in the authors' experiments indicate that their approach is well suited for pragmatic vehicle classification applications. View full abstract»

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  • 23. Understanding drivers' perspective on parking guidance information

    Publication Year: 2014 , Page(s): 398 - 406
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (318 KB)  

    Parking guidance and information (PGI) systems are thought to enable a more efficient control and management of the traffic and the use of the available car park in urban areas. Despite the installation of PGI systems in many cities and their operation for a number of years, the levels of usage of PGI remain much lower than expected. To guide investment and operational decisions, this study examines the existing PGI systems from the drivers' perspective. The results show that PGI is not efficiently used and often ignored by drivers because of the inaccurate or out-of-date nature of the information it is displaying. Habitual behaviour also played an important role in the choices of a car park. However, the results of the research also show that there is a desire for more accurate, dynamic and personalised parking information through different means at pre-trip stage and en-route stage. The results of this survey should provide some guidance in the design of future PGI systems. View full abstract»

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  • 24. Interaction design of automatic steering for collision avoidance: challenges and potentials of driver decoupling

    Publication Year: 2015 , Page(s): 95 - 104
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (419 KB)

    Studies concerning collision avoidance show that most drivers tend to brake, even if evasive manoeuvres were better. Automatic steering for collision avoidance would help here. Studies in the EU project interactIVe observed that drivers show a tendency to hold the steering wheel and disturb the automatic steering when kept in the control loop. A strategy of driver decoupling, for example, by means of steer-by-wire systems could improve the automatic steering performance. However, the major challenge of using steer-by-wire systems is to enable the driver to compensate false system activation, for example, evasion into oncoming traffic. A time-dependent strategy of driver decoupling using steer-by-wire combined with override recognition by counter steering above a certain threshold was implemented in a research vehicle. The interaction strategy was tested with 45 participants on a test track in two different scenarios; a collision situation with justified evasion and a false alert scenario with unjustified system activation. In a between-subject design the decoupling strategy (using steer-by-wire) was compared against automatic steering with fully coupled driver and force feedback on the steering wheel and against Manual Driving without automatic steering. When the driver was temporarily decoupled, the obstacle avoidance performance was better but the driver was less able to counteract a false avoidance manoeuvre. The analysis of driver behaviour revealed options to improve the interaction strategy. View full abstract»

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  • 25. Intelligent transport systems and effects on road traffic accidents: state of the art

    Publication Year: 2007 , Page(s): 81 - 88
    Cited by:  Papers (16)  |  Patents (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (109 KB)  

    The results from several reviews have been presented and the aspects of road safety associated with intelligent transport systems (ITS) applications have been addressed. The attempt is to make a state-of-the-art regarding effects on accidents by categorising systems according to levels of evaluations methods that have been applied. These categories are effects on behaviour, effects on accidents by proxy/surrogate methods, accident studies from real traffic, effects on accident types and finally by meta-analysis where weighted estimates of effects on accidents can be calculated. Thirty-three IT systems including driver assistance systems/advanced driver assistance systems, in-vehicle information systems, in-vehicle data-collection systems and road telematics have been listed. Effects based on meta-analysis are estimated for 11 systems, and single accident studies are found for an additional 2 systems. For the remaining 20 systems, no studies from real road traffic have been identified. Effects on accidents of antilocking brake systems and electronic stability control (ESC) are presented in more detail according to their effects on certain accident types. ESC appears to be very efficient in reducing the number of accidents. Behavioural adaptations to ITS are considered and discussed, especially in terms of compensation mechanisms. Four hypotheses regarding prediction of effects on accidents are stated according to whether systems increase or decrease 'windows of opportunities' by calling upon a driver behaviour model where emotions play a central role View full abstract»

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  • 26. Vehicle-to-infrastructure communication-based adaptive traffic signal control

    Publication Year: 2013 , Page(s): 351 - 360
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (380 KB)  

    This study presents a method that combines travel-time estimation and adaptive traffic signal control. The proposed method explores the concept of vehicle-to-infrastructure communication, through which real-time vehicle localisation data become available to traffic controllers. This provides opportunity to frequently sample vehicle location and speed for online travel-time estimation. The control objective is to minimise travel time for vehicles in the system. The proposed method is based on approximate dynamic programming, which allows the controller to learn from its own performance progressively. The authors use micro-traffic simulation to evaluate the control performance against benchmark control methods in an idealistic environment, where errors in sampling vehicle location and speed are not considered. The results show that the proposed method outperforms benchmarking methods substantially and consistently. View full abstract»

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  • 27. Real-time urban traffic monitoring with global positioning system-equipped vehicles

    Publication Year: 2010 , Page(s): 113 - 120
    Cited by:  Papers (4)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (269 KB)  

    Real-time traffic conditions are useful information based on which many adaptive traffic solutions work. In this study, the authors present a new approach for real-timely monitoring urban traffic with global positioning system (GPS)-equipped vehicles, which provides estimation of urban traffic conditions in real time. The approach first real-timely collects GPS trace data from GPS-equipped vehicles on the urban road network. Then, it periodically clusters the collected data of several minutes, calculates estimated space mean speed (eSMS) and translates eSMS to smooth indexes (denoting traffic conditions). Compared with existing work, the presented one: (i) applies an effective map matching method to cluster GPS trace data; (ii) excludes traffic signal's misleading influences on traffic condition estimation and (iii) judges traffic conditions based on an estimated critical traffic flow characteristic. Some experiments based on GPS taxi scheduling data of Shanghai, China are provided to demonstrate performance of this work. View full abstract»

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  • 28. Analysing the impact of weather on bus ridership using smart card data

    Publication Year: 2015 , Page(s): 221 - 229
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (427 KB)

    This study investigates the impact of weather on bus ridership using smart card data collected in Fengxian, Shanghai. The ridership data are categorised into three representative groups by the cluster analysis. The ridership data for each cluster are further divided according to the four seasons. Twelve separate multiple linear regression models with four weather variables and two dummy variables are constructed and calibrated. All four weather variables, namely humidity, wind speed, rainfall and temperature are found to have statistically significant negative effects on bus ridership. The magnitude of the impact varies depending on bus route types, seasons and mode share characteristics. Our analysis provides a valuable case study on weather's impact on bus ridership and concludes that there is no one-size-fits-all conclusion about the relationships between weather attributes and bus ridership, and it is critical to investigate those relationships in different geographical contexts. The results of this study can be used not only for long-term transit policy making but also as a decision making tool for short-term ridership forecasting. View full abstract»

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  • 29. Optimisation of energy efficiency based on average driving behaviour and driver's preferences for automated driving

    Publication Year: 2015 , Page(s): 50 - 58
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (361 KB)

    The implementation of anticipating driving styles in adaptive cruise control systems promises to considerably reduce fuel consumption of vehicles. As drivers have to accept the optimised driving styles of such systems, which implement longitudinally automated driving, the optimisation results should not deviate strongly from the average driving behaviour. This work presents an approach to the optimisation of the vehicle's longitudinal dynamics, which is based on a predicted average driving profile. The proposed approach ensures that the optimisation results meet the expectations of drivers by directly accounting for driver's preferences on weighting up travel time against fuel consumption relative to the average driving profile. Based on human decision finding, rational and intuitive planning decisions are modelled in a cost function and represent optimisation constraints. The approach generally includes information from vehicle-to-vehicle and vehicle-to-infrastructure communication (V2X), which is an extension to the state-of-the-art. This study describes the optimisation approach and presents a method to determine suitable optimisation parameters in order to consider driver's preferences. The optimisation approach is applied in a simulated test drive and improvements in fuel economy are analysed. Finally, the authors sketch a reference system architecture to prove the feasibility of the presented approach. View full abstract»

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  • 30. Vehicle detection and tracking under various lighting conditions using a particle filter

    Publication Year: 2012 , Page(s): 1 - 8
    Cited by:  Papers (4)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (474 KB)  

    The authors propose a vision-based automatic system to detect preceding vehicles on the highway under various lighting and different weather conditions. To adapt to different characteristics of vehicle appearance under various lighting conditions, four cues including underneath shadow, vertical edge, symmetry and taillight are fused for the vehicle detection. The authors achieve this goal by generating probability distribution of vehicle under particle filter framework through the processes of initial sampling, propagation, observation, cue fusion and evaluation. Unlike normal particle filter focusing on single target distribution in a state space, the authors detect multiple vehicles with a single particle filter through a high-level tracking strategy using clustering. In addition, the data-driven initial sampling technique helps the system detect new objects and prevent the multi-modal distribution from collapsing to the local maxima. Experiments demonstrate the effectiveness of the proposed system. View full abstract»

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  • 31. Detection of potholes in autonomous vehicle

    Publication Year: 2014 , Page(s): 543 - 549
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (725 KB)  

    Pothole avoidance may be considered similar to other obstacle avoidance, except that the potholes are depressions rather than extrusions from a surface. This study discusses a solution for detection of potholes in the path of an autonomous vehicle operating in an unstructured environment. Here, a vision approach is used since the simulated potholes are significantly different from the background surface. Furthermore, using this approach, pothole can only be detected in case of uniform lighting conditions. The solution to the problem is developed in a systematic manner. Initially, a specific camera and frame grabber are chosen, then camera is mounted on top of the autonomous vehicle and the images will be acquired. Then, a software solution is designed using MATLAB. The method is tested under real-time conditions and results demonstrate its reasonable efficiency. View full abstract»

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  • 32. Effect of intelligent speed adaptation technology on older drivers’ driving performance

    Publication Year: 2015 , Page(s): 343 - 350
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (356 KB)

    Excess speeding on roads with a low-speed limit is a key error in drivers of all ages although the reasons for speeding can be significantly different. Drivers aged over 60 are generally more cautious, and take fewer risks than younger aged drivers. This study investigates whether Intelligent Speed Adaptation (ISA) technology can assist older drivers in maintaining vehicle speed. The technology can be employed in three ways: advisory (AISA), differential (DISA) and mandatory (MISA). Twenty-six drivers aged over 60 years old participated along with a comparison group of 16 experienced younger drivers aged under 60. All drivers completed four driving tasks in a driving simulator with and without ISA. Results show improvements in speed and lane-keeping performance vary depending on the type of ISA and driver age and training in effective use of ISA is needed for drivers of all ages. The study is one component of a wider research programme exploring how ITS could potentially help older people overcome some of the difficulties they experience with driving as they age and hopefully help them remain safe drivers for longer, a benefit both to the individual and society. View full abstract»

    Open Access
  • 33. Dynamic scene modelling and anomaly detection based on trajectory analysis

    Publication Year: 2014 , Page(s): 526 - 533
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (729 KB)  

    A real-time scene modelling approach is presented that recognises temporary and permanent road structure change resulting from construction, accident or lane expansion and other obstructions. The system defined utilises a two-phase approach to modelling the scene. In the transitional phase, a dominant set-based graphical clustering approach is applied to understand the current scene structure from trajectory groupings, whereas the operational phase analyses the trajectories in real-time to detect anomalies such as u-turns, wrong-way or erratic drivers based on the acquired model of the scene structure and normal traffic patterns. In addition, the concept of dynamic traffic flow analysis is utilised to identify and remember temporary additions and removals of paths due to construction and accidents, as well as permanent road structure changes. An intuitive equal-arc-length sampling is applied to extract only the spatial information from the trajectory comparisons, since the spatial characteristics alone are sufficient for road structure understanding. A distance metric is developed to measure spatial difference and directional change of the path with entrance and exit awareness. Results for a publicly available dataset are provided, demonstrating that the method can efficiently model the scene, detect anomalies and capture both temporary and permanent scene reconstructions. View full abstract»

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  • 34. On-line map-matching framework for floating car data with low sampling rate in urban road networks

    Publication Year: 2013 , Page(s): 404 - 414
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1050 KB)  

    The performance of map matching has a significant effect on obtaining real-time traffic information. The floating car data (FCD) is of low-sampling rate, and urban road networks such as multi-layer roads can be particularly complex. Most of the current low-sampling-rate map-matching approaches use a fixed time interval, which can result in a lack of efficiency and accuracy if the initial point is not correctly matched. Moreover, the issue of handling data relating to multi-layer road networks remains open. To address these issues, a new on-line map-matching framework is proposed, comprising the confidence point and the maximum delay constraint dynamic time window. The framework performs map matching by self-adaptively choosing the appropriate timing and matching method according to the complexity of the local network to which the positioning point belongs. To distinguish elevated roads from normal roads, vehicle behaviour patterns on elevated roads are taken into account. Comparisons of the proposed algorithm, hidden Markov model algorithm, incremental algorithm and point-to-curve algorithm are conducted on two datasets. The empirical results show that the proposed algorithm outperforms the other algorithms. When the behaviour pattern on elevated roads is considered, the accuracy of these algorithms is also improved. View full abstract»

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  • 35. Reinforcement learning-based multi-agent system for network traffic signal control

    Publication Year: 2010 , Page(s): 128 - 135
    Cited by:  Papers (15)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (331 KB)  

    A challenging application of artificial intelligence systems involves the scheduling of traffic signals in multi-intersection vehicular networks. This paper introduces a novel use of a multi-agent system and reinforcement learning (RL) framework to obtain an efficient traffic signal control policy. The latter is aimed at minimising the average delay, congestion and likelihood of intersection cross-blocking. A five-intersection traffic network has been studied in which each intersection is governed by an autonomous intelligent agent. Two types of agents, a central agent and an outbound agent, were employed. The outbound agents schedule traffic signals by following the longest-queue-first (LQF) algorithm, which has been proved to guarantee stability and fairness, and collaborate with the central agent by providing it local traffic statistics. The central agent learns a value function driven by its local and neighbours' traffic conditions. The novel methodology proposed here utilises the Q-Learning algorithm with a feedforward neural network for value function approximation. Experimental results clearly demonstrate the advantages of multi-agent RL-based control over LQF governed isolated single-intersection control, thus paving the way for efficient distributed traffic signal control in complex settings. View full abstract»

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  • 36. Driving behaviour-based event data recorder

    Publication Year: 2014 , Page(s): 361 - 367
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (433 KB)  

    A general event data recorder is a device installed in automobiles to record information related to vehicle crashes or accidents. The data provide a better understanding of how certain crashes come about. This study made a prototype of a driving behaviour-based event data recorder (DBEDR), which provides the information of driving behaviours and a danger level. The authors approach is to recognise the seven behaviours: normal driving, acceleration, deceleration, changing to the left lane or right lane, zigzag driving and approaching the car in front by the hidden Markov models. All data were collected from a real vehicle and evaluated in a real road environment. The experimental results show that the proposed method achieved an average detection ratio of 95% for behaviour recognition. The danger level is inferred by fuzzy rules involved with the above behaviours. DBEDR recorded the recognised driving behaviours and the danger level, and the places were stored with the assistance of a global positioning system receiver. By integrating Google Maps, the locations, the driving behaviour occurrences, the danger level on the travel routes and the recorded images, the proposed DBEDR could be more useful compared with the traditional EDRs. View full abstract»

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  • 37. Bus rapid transit system deployment for high quality and cost-effective transit service: a comprehensive review and comparative analysis

    Publication Year: 2015 , Page(s): 175 - 183
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (653 KB)

    This study aims to provide a comprehensive review of bus rapid transit (BRT) systems as an effective alternative transport mode which will benefit urban transportation knowledge for creating a BRT system. BRT can be seen as a feasible solution to traffic congestion and is designed using delicate transportation design strategies, such as, dedicated lanes, adequate station design, master planning of service and operation, faster toll collection, up-to-date intelligent transportation systems applications. BTR systems will improve time, safety and cost-effectiveness by accomplishing the goals of increasing speed and ridership. Unlike rail, BRT is a flexible transit design system. BRT acceptance is determined with algorithms such as logistic modelling and ridership data. Optimum potential determination of a system is possible by looking at international and local studies examining BRT problems and strengths. Problems consist of conflicts with other transportation modes and population booms. Determining if a system will be used also heavily falls on the quality. Most transit systems are perceived eyesores and inefficient modes with over-congestion, these barriers can be overcome with proper design that gives a captivating addition to the community. View full abstract»

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  • 38. Homography-based ground plane detection using a single on-board camera

    Publication Year: 2010 , Page(s): 149 - 160
    Cited by:  Papers (9)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (624 KB)  

    This study presents a robust method for ground plane detection in vision-based systems with a non-stationary camera. The proposed method is based on the reliable estimation of the homography between ground planes in successive images. This homography is computed using a feature matching approach, which in contrast to classical approaches to on-board motion estimation does not require explicit ego-motion calculation. As opposed to it, a novel homography calculation method based on a linear estimation framework is presented. This framework provides predictions of the ground plane transformation matrix that are dynamically updated with new measurements. The method is specially suited for challenging environments, in particular traffic scenarios, in which the information is scarce and the homography computed from the images is usually inaccurate or erroneous. The proposed estimation framework is able to remove erroneous measurements and to correct those that are inaccurate, hence producing a reliable homography estimate at each instant. It is based on the evaluation of the difference between the predicted and the observed transformations, measured according to the spectral norm of the associated matrix of differences. Moreover, an example is provided on how to use the information extracted from ground plane estimation to achieve object detection and tracking. The method has been successfully demonstrated for the detection of moving vehicles in traffic environments. View full abstract»

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  • 39. Development of a real-time bus arrival prediction system for Indian traffic conditions

    Publication Year: 2010 , Page(s): 189 - 200
    Cited by:  Papers (6)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (356 KB)  

    The accuracy of Bus Traveler Information Systems (BTIS) depends on several factors such as accuracy of the input data, speed of data transfer, data quality control and performance of the prediction scheme. A majority of the existing BTIS in India does not take into account the real-time data and the quality control of data. Also, there is a scope for improving the performance of the underlying prediction schemes. There are several studies on real-time bus arrival time prediction under homogeneous traffic conditions. However, the traffic condition in India is different and direct implementation of those studies may not yield the best results. One of the main components of bus travel time is the delay time at bus stops, in addition to the other common delays. These delays need to be incorporated in the prediction scheme for better accuracy, which is not the case currently in most studies. Also, there is a need to develop an accurate automated bus arrival time prediction system using real-time data under heterogeneous traffic conditions. This study presents a model-based algorithm that uses real-time data from field and takes delays automatically into account for an accurate prediction of bus arrival time. The results obtained are compared with the currently adopted field method and show a clear improvement in the prediction accuracy. View full abstract»

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  • 40. Improving short-term traffic forecasts: to combine models or not to combine?

    Publication Year: 2015 , Page(s): 193 - 201
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (383 KB)

    This study compares the performance of statistical and Bayesian combination models with classical single time series models for short-term traffic forecasting. Combinations are based on fractionally integrated autoregressive time series models of travel speed with exogenous variables that consider speed's spatio-temporal evolution, and volume and weather conditions. Several statistical hypotheses on the effectiveness of combinations compared to the single models are also tested. Results show that, in the specific application, linear regression combination techniques may provide more accurate forecasts than Bayesian combination models. Moreover, combining models with different degrees of spatio-temporal complexity and exogeneities is most likely to be the best choice in terms of accuracy. Moreover, the risk of combining forecasts is lower than the risk of choosing a single model with increased spatio-temporal complexity. View full abstract»

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  • 41. 3D vehicle detection using a laser scanner and a video camera

    Publication Year: 2008 , Page(s): 105 - 112
    Cited by:  Papers (21)  |  Patents (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (530 KB)  

    A new approach for vehicle detection performs sensor fusion of a laser scanner and a video sensor. This combination provides enough information to handle the problem of multiple views of a car. The laser scanner estimates the distance as well as the contour information of observed objects. The contour information can be used to identify the discrete sides of rectangular objects in the laser scanner coordinate system. The transformation of the three-dimensional coordinates of the most visible side to the image coordinate system allows for a reconstruction of its original view. This transformation also compensates size differences in the video image, which are caused by different distances to the video sensor. Afterwards, a pattern recognition algorithm can classify the object's sides based on contour and shape information. Since the number of available object hypotheses is enormously reduced by the laser scanner, the system is applicable in real time. In addition, video-based vehicle detection and additional laser scanner features are fused in order to create a consistent vehicle environment description. View full abstract»

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  • 42. Stochastic effects of traffic randomness on the determination of signal change and clearance intervals at signalised intersections

    Publication Year: 2015 , Page(s): 250 - 263
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1189 KB)

    Conventional methods of intergreen time design are based on deterministic traffic flow theory and are difficult to fully reflect traffic randomness especially driver's decision differences. This study is to develop a probabilistic model to extensively investigate the effects of traffic flow randomness and driver's decision errors on the determination of intergreen times. An analytical framework was proposed based on a safety reliability model earlier developed by the authors and validated based on field data at a typical high-speed intersection in Shanghai. Then, comprehensive sensitivity analysis was performed to look into the fluctuation of safety reliability towards critical variables as well as their variations and correlations. Two logistic regression models were developed to quantify the effects of each random component on the probabilities of risky behaviour and clearance failure, that is, safety reliability indicators for intergreen intervals. To facilitate easy applications of the proposed approach, a set of scenario analysis were done to calculate the required intergreen intervals under different traffic conditions and safety reliability levels. Application tables were finally provided for signal design, which are able to recommend more sophisticated intergreen times and thus aid the practitioners to select proper intergreen times according to local conditions without complicated calculation. View full abstract»

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  • 43. Can ride-sharing become attractive? A case study of taxi-sharing employing a simulation modelling approach

    Publication Year: 2015 , Page(s): 210 - 220
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (775 KB)

    Improved urban mobility can be attained through more efficient vehicle usage and better road network utilisation, namely through increased vehicle occupancy and new operation modes. In this study, the authors focus on a dynamic and distributed taxi-sharing system that takes advantage of nowadays widespread availability of communication and distributed computation to provide a cost-efficient, door-to-door and flexible service, offering a quality of service similar to conventional taxis. This system has been evaluated following a simulation modelling approach, including a realistic and accurate replication of the taxi operation in the city of Porto using empirical data (real origin/destination data and average occupancy rates). Simulation results show improved performance in terms of reduced fares (up to 8%), reduced total travel distance (up to 9%) and smaller operation costs. Furthermore, they proposed that several trade-offs (e.g. service performance against passengers' transit times) should be considered during the system deployment and operation. In this study, it was also shown that increased system penetration rate and demand level can even further improve the system performance. View full abstract»

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  • 44. Modelling and simulating worm propagation in static and dynamic traffic

    Publication Year: 2014 , Page(s): 155 - 163
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1147 KB)  

    Vehicular ad hoc networks (VANETs) have no fixed infrastructure and instead relies on the vehicles themselves to provide network functionality. An attack scenario with potentially catastrophic consequences is the outbreak of mobile worm epidemic in these networks. This paper analyses the snapshot spreading results under an urban scenario with equilibrium traffic through modelling the mobility pattern, the communication channel, the medium access control (MAC) mechanism and the worm propagation process. The extensive Monte Carlo simulations uncovered the effects of the transmission range (from a typical minimum to a maximum), the minimum velocity and the maximum velocity (from the free flow to the congested traffic), the vehicle density (from a sparse topology to a dense spatial relation) and the MAC mechanism (from presence to absence) on epidemic spreading of such worms in VANETs. Furthermore, the authors simulate the wireless worm propagation in dynamic traffic with the same scenario as the static traffic by using a network simulation tool. The authors discuss the correlation between snapshot results and evolutive outcome, also analyse the reasons resulting in the local differences and finally uncover the interrelations between the affected rate and network parameters. The results are expected to help engineers design intelligent and automatic detection prevention strategies for VANETs. View full abstract»

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  • 45. Wireless sensor networks for traffic management and road safety

    Publication Year: 2012 , Page(s): 67 - 77
    Cited by:  Papers (9)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (788 KB)  

    Wireless sensor networks (WSN) employ self-powered sensing devices that are mutually interconnected through wireless ad-hoc technologies. This study illustrates the basics of WSN-based traffic monitoring and summarises the possible benefits in Intelligent Transport Systems (ITS) applications for the improvement of quality and safety of mobility. Compared with conventional infrastructure-based monitoring systems, this technology facilitates a denser deployment of sensors along the road, resulting in a higher spatial resolution of traffic parameter sampling. An experimental data analysis reported in this study shows how the high spatial resolution can enhance the reliability of traffic modelling as well as the accuracy of short-term traffic state prediction. The analysis uses the data published by the freeway performance measurement system of the University of California-Berkeley and the California Department of Transportation. A microscopic cellular automata model is used to estimate traffic flow and occupancy over time on a road segment in which a relevant traffic-flow anomaly is detected. The analysis shows that the estimate accuracy improves for increasing number of active sensors, as feasible in the case of WSN-based monitoring systems. View full abstract»

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  • 46. Traffic sensor location approach for flow inference

    Publication Year: 2015 , Page(s): 184 - 192
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (441 KB)

    Traffic sensors serve an important function in obtaining traffic information. In this paper, a novel traffic sensor location approach is proposed to determine the maximum number of traffic flows by considering the time-spatial correlation. The problem is formulated as three 0-1 programming models to maximise the number of obtained flows under different cases. To solve these novel sensor location problems, an ant colony optimisation algorithm with a local search procedure is designed. Numerical experiments are conducted in both a simulated network and in the Sioux-Falls network. Results demonstrate the effectiveness and robustness of the proposed algorithm, which is believed to possess potential applicability in real surveillance network design. View full abstract»

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  • 47. Potential impacts of ecological adaptive cruise control systems on traffic and environment

    Publication Year: 2014 , Page(s): 77 - 86
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (702 KB)  

    In this contribution, we put forward a modelling framework for generic Advanced Driver Assistance Systems (ADAS) based on rolling horizon optimal control and design control algorithms for an Ecological Adaptive Cruise Control (EcoACC) system under this framework. The accelerations of EcoACC vehicles are determined by minimizing some predicted cost, and the optimal control problem is solved using a dynamic programming approach. The proposed algorithm is applied on a single lane ring road to examine the impacts of the EcoACC system employing the Eco-driving strategy comparison with a system employing an Efficient-driving strategy. Simulation results show that the Eco-driving strategy results in smoother vehicle behaviour compared to the driving strategies that only consider travel efficiency (Efficient-driving strategy). At the macroscopic level, the Eco-driving strategy results in a lower speed and lower flow at free traffic conditions, but a higher speed and higher flow at moderate congested conditions compared to the Efficient-driving strategy. From an environment perspective, the Eco-driving strategy results in a lower spatial CO2 emission rate. However, in the ring-road scenario where the demand is not fixed, the impact of the EcoACC system on total CO2 emissions is negative at moderate congested conditions, due to the high flow it supports. View full abstract»

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  • 48. Automotive standards-grade lane departure warning system

    Publication Year: 2012 , Page(s): 44 - 57
    Cited by:  Papers (7)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (694 KB)  

    The increasing trend towards the use of image sensors in transportation is driven both by legislation and consumer demands for higher safety and a better-driving experience. Awareness of the environment that surrounds a vehicle can make driving and manoeuvring of the vehicle much safer for all road users. The authors present an image processing method to detect lane departure in forward-facing video specifically designed to be in accordance with proposed automotive lane departure warning standards. Our system uses a novel lane-marking segmentation algorithm in accordance with national standards for lane markings. This method does not demand the high computational requirements of inverse perspective mapping unlike methods proposed in related research. The authors present a method for lane boundary modelling based on subtractive clustering and Kalman filtering in the Hough transform domain, which is within the constraints of automotive standards. Finally, using the cameras intrinsic and extrinsic parameters, the width of the vehicle and guidelines issued by the International Organisation for Standardisation, we show how lane departure can be identified. Results are presented that verify the systems high detection rate and robustness to various background interference, lighting conditions and road environments. View full abstract»

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  • 49. Reliability of an in-vehicle warning system for railway level crossings - a user-oriented analysis

    Publication Year: 2014 , Page(s): 9 - 20
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (641 KB)  

    This study analyses the reliability of an in-vehicle warning system developed in Finland during 2008-2010. The system is based on the positioning of trains using GPS, calculation of the states of level crossings on a server and in-vehicle equipment that retrieves information about the states of level crossings from the server. Information about the reliability of the system is very relevant for accurate estimation of the impacts of the system and for estimating the potential for improvements to it. The study starts with a description of the system under analysis, continues by defining the concept of reliability and provides an estimate for the reliability of the system from the user point of view. To achieve this objective, the study defines the relevant concepts and describes a methodology for analysis of the reliability of the system. The main input to the analysis of reliability includes a brief overview of existing concepts related to the reliability of in-vehicle ITS systems and empirical data obtained in a field test carried out in southern Finland. The analysis shows that the expected functionality has been achieved, but the reliability level of the pilot system needs improvement, especially reduction in the share of missed alarms. View full abstract»

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  • 50. Automated on-ramp merging control algorithm based on internet-connected vehicles

    Publication Year: 2013 , Page(s): 371 - 379
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (681 KB)  

    With the rapid development of Information and Communication Technologies, vehicular networks that communicate with each other will have an innovative application in traffic safety and congestion. This study describes a preliminary study on an automated on-ramp merging control algorithm for vehicles on freeways under condition of Internet-connected vehicles. On the basis of vehicular operation characteristics during the merging process analysis, a cooperative driving algorithm based on Internet of vehicles was designed to achieve ramp merging without collision. Then two on-ramp merging cases, including one vehicle and two vehicles merging into the platoon on main lane, were discussed in detail. Simulation works were carried out and the results proved that the on-ramp merging algorithm was effective, but the vehicle following the leading vehicle on ramp lane is disturbed seriously by the leading vehicle. At the same time, the simulation results also showed the scenario that merging a platoon into the two vehicles on main lane affects the traffic flow more seriously than letting each individual vehicle on ramp lane consecutively to merge in between the two vehicles in the main lane under the same initial condition. 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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