621 research outputs found

    Improving performance of pedestrian positioning by using vehicular communication signals

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    Pedestrian-to-vehicle communications, where pedestrian devices transmit their position information to nearby vehicles to indicate their presence, help to reduce pedestrian accidents. Satellite-based systems are widely used for pedestrian positioning, but have much degraded performance in urban canyon, where satellite signals are often obstructed by roadside buildings. In this paper, we propose a pedestrian positioning method, which leverages vehicular communication signals and uses vehicles as anchors. The performance of pedestrian positioning is improved from three aspects: (i) Channel state information instead of RSSI is used to estimate pedestrian-vehicle distance with higher precision. (ii) Only signals with line-of-sight path are used, and the property of distance error is considered. (iii) Fast mobility of vehicles is used to get diverse measurements, and Kalman filter is applied to smooth positioning results. Extensive evaluations, via trace-based simulation, confirm that (i) Fixing rate of positions can be much improved. (ii) Horizontal positioning error can be greatly reduced, nearly by one order compared with off-the-shelf receivers, by almost half compared with RSSI-based method, and can be reduced further to about 80cm when vehicle transmission period is 100ms and Kalman filter is applied. Generally, positioning performance increases with the number of available vehicles and their transmission frequency

    FUTURE GLOBAL NAVIGATION SATELLITE SYSTEMS (GNSS)

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    Global Positioning System (GPS) has been widely used worldwide for a variety of applications such as air, land and sea. The GPS and the Russian GLONASS are the only fully operational Global Navigation Satellite System (GNSS). Due to its several advantages, such as simplicity of use, successful implementation and global availability, this has been considered as the cornerstone of positioning in navigation system applications for the people who are visually impaired. However, due to standalone single frequency service, the positioning performance has not been sufficient for some accuracy and precision demanding applications. The problems of obtaining high accuracy real time positions in the field have led the navigation community to develop a GNSS augmentation system. However, several questions have been raised with this new development, such as how good the new method is? During any satellite configuration, would it be able to provide the accuracy at the same level? In a reliable way, would it be able to replace conventional GPS method? In this paper, a detailed review of all necessary understandings concerning GNSS and with a focal point on the GPS, GLONASS, Galileo, Beidou and GNSS augmentation systems positioning performance, is provided. The enormous demand to further improve positioning, navigation, and timing capabilities for both civil and military users on existing GNSS systems has directed efforts to modernise the GPS and GLONASS system and introduce new systems such as Galileo navigation system

    FUTURE GLOBAL NAVIGATION SATELLITE SYSTEMS (GNSS)

    Get PDF
    Global Positioning System (GPS) has been widely used worldwide for a variety of applications such as air, land and sea. The GPS and the Russian GLONASS are the only fully operational Global Navigation Satellite System (GNSS). Due to its several advantages, such as simplicity of use, successful implementation and global availability, this has been considered as the cornerstone of positioning in navigation system applications for the people who are visually impaired. However, due to standalone single frequency service, the positioning performance has not been sufficient for some accuracy and precision demanding applications. The problems of obtaining high accuracy real time positions in the field have led the navigation community to develop a GNSS augmentation system. However, several questions have been raised with this new development, such as how good the new method is? During any satellite configuration, would it be able to provide the accuracy at the same level? In a reliable way, would it be able to replace conventional GPS method? In this paper, a detailed review of all necessary understandings concerning GNSS and with a focal point on the GPS, GLONASS, Galileo, Beidou and GNSS augmentation systems positioning performance, is provided. The enormous demand to further improve positioning, navigation, and timing capabilities for both civil and military users on existing GNSS systems has directed efforts to modernise the GPS and GLONASS system and introduce new systems such as Galileo navigation system

    Investigation of Shadow Matching for GNSS Positioning in Urban Canyons

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    All travel behavior of people in urban areas relies on knowing their position. Obtaining position has become increasingly easier thanks to the vast popularity of ‘smart’ mobile devices. The main and most accurate positioning technique used in these devices is global navigation satellite systems (GNSS). However, the poor performance of GNSS user equipment in urban canyons is a well-known problem and it is particularly inaccurate in the cross-street direction. The accuracy in this direction greatly affects many applications, including vehicle lane identification and high-accuracy pedestrian navigation. Shadow matching is a new technique that helps solve this problem by integrating GNSS constellation geometries and information derived from 3D models of buildings. This study brings the shadow matching principle from a simple mathematical model, through experimental proof of concept, system design and demonstration, algorithm redesign, comprehensive experimental tests, real-time demonstration and feasibility assessment, to a workable positioning solution. In this thesis, GNSS performance in urban canyons is numerically evaluated using 3D models. Then, a generic two-phase 6-step shadow matching system is proposed, implemented and tested against both geodetic and smartphone-grade GNSS receivers. A Bayesian technique-based shadow matching is proposed to account for NLOS and diffracted signal reception. A particle filter is designed to enable multi-epoch kinematic positioning. Finally, shadow matching is adapted and implemented as a mobile application (app), with feasibility assessment conducted. Results from the investigation confirm that conventional ranging-based GNSS is not adequate for reliable urban positioning. The designed shadow matching positioning system is demonstrated complementary to conventional GNSS in improving urban positioning accuracy. Each of the three generations of shadow matching algorithm is demonstrated to provide better positioning performance, supported by comprehensive experiments. In summary, shadow matching has been demonstrated to significantly improve urban positioning accuracy; it shows great potential to revolutionize urban positioning from street level to lane level, and possibly meter level

    Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application

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    While the development of Vehicle-to-Vehicle (V2V) safety applications based on Dedicated Short-Range Communications (DSRC) has been extensively undergoing standardization for more than a decade, such applications are extremely missing for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between VRUs and vehicles was the main reason for this lack of attention. Recent developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this perspective. Leveraging the existing V2V platforms, we propose a new framework using a DSRC-enabled smartphone to extend safety benefits to VRUs. The interoperability of applications between vehicles and portable DSRC enabled devices is achieved through the SAE J2735 Personal Safety Message (PSM). However, considering the fact that VRU movement dynamics, response times, and crash scenarios are fundamentally different from vehicles, a specific framework should be designed for VRU safety applications to study their performance. In this article, we first propose an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection based on the most common and injury-prone crash scenarios. The details of our VRU safety module, including target classification and collision detection algorithms, are explained next. Furthermore, we propose and evaluate a mitigating solution for congestion and power consumption issues in such systems. Finally, the whole system is implemented and analyzed for realistic crash scenarios

    Location-based technologies for learning

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    Emerging technologies for learning report - Article exploring location based technologies and their potential for educatio

    Use Of Smartphones for Ensuring Vulnerable Road User Safety through Path Prediction and Early Warning: An In-Depth Review of Capabilities, Limitations and Their Applications in Cooperative Intelligent Transport Systems

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    The field of cooperative intelligent transport systems and more specifically pedestrians to vehicles could be characterized as quite challenging, since there is a broad research area to be studied, with direct positive results to society. Pedestrians to vehicles is a type of cooperative intelligent transport system, within the group of early warning collision/safety system. In this article, we examine the research and applications carried out so far within the field of pedestrians to vehicles cooperative transport systems by leveraging the information coming from vulnerable road users’ smartphones. Moreover, an extensive literature review has been carried out in the fields of vulnerable road users outdoor localisation via smartphones and vulnerable road users next step/movement prediction, which are closely related to pedestrian to vehicle applications and research. We identify gaps that exist in these fields that could be improved/extended/enhanced or newly developed, while we address future research objectives and methodologies that could support the improvement/development of those identified gaps
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