A Study on Vehicle Trajectory Analysis

Successful developments of effective real-time traffic management and information systems demand high quality real time traffic information. In the era of intelligent transportation convergence, traffic monitoring requires traffic sensory technologies. The present analysis extracted data from Mobile Century experiment. The data obtained in the experiment was pre-processed. Based on the pre processed data experimental road map has generated. Individual vehicle tracking has done using trajectory analysis. Finally an attempt has been made for extracting association rules from mobile century dataset using Apriori algorithm

Advanced Map Matching Technologies and Techniques for Pedestrian/Wheelchair Navigation

Due to the constantly increasing technical advantages of mobile devices (such as smartphones), pedestrian/wheelchair navigation recently has achieved a high level of interest as one of smartphones’ potential mobile applications. While vehicle navigation systems have already reached a certain level of maturity, pedestrian/wheelchair navigation services are still in their infancy. By comparing vehicle navigation systems, a set of map matching requirements and challenges unique in pedestrian/wheelchair navigation is identified. To provide navigation assistance to pedestrians and wheelchair users, there is a need for the design and development of new map matching techniques. The main goal of this research is to investigate and develop advanced map matching technologies and techniques particular for pedestrian/wheelchair navigation services. As the first step in map matching, an adaptive candidate segment selection algorithm is developed to efficiently find candidate segments. Furthermore, to narrow down the search for the correct segment, advanced mathematical models are applied. GPS-based chain-code map matching, Hidden Markov Model (HMM) map matching, and fuzzy-logic map matching algorithms are developed to estimate real-time location of users in pedestrian/wheelchair navigation systems/services. Nevertheless, GPS signal is not always available in areas with high-rise buildings and even when there is a signal, the accuracy may not be high enough for localization of pedestrians and wheelchair users on sidewalks. To overcome these shortcomings of GPS, multi-sensor integrated map matching algorithms are investigated and developed in this research. These algorithms include a movement pattern recognition algorithm, using accelerometer and compass data, and a vision-based positioning algorithm to fill in signal gaps in GPS positioning. Experiments are conducted to evaluate the developed algorithms using real field test data (GPS coordinates and other sensors data). The experimental results show that the developed algorithms and the integrated sensors, i.e., a monocular visual odometry, a GPS, an accelerometer, and a compass, can provide high-quality and uninterrupted localization services in pedestrian/wheelchair navigation systems/services. The map matching techniques developed in this work can be applied to various pedestrian/wheelchair navigation applications, such as tracking senior citizens and children, or tourist service systems, and can be further utilized in building walking robots and automatic wheelchair navigation systems

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Investigation of Shadow Matching for GNSS Positioning in Urban Canyons

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

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

A survey on acoustic positioning systems for location-based services

Positioning systems have become increasingly popular in the last decade for location-based services, such as navigation, and asset tracking and management. As opposed to outdoor positioning, where the global navigation satellite system became the standard technology, there is no consensus yet for indoor environments despite the availability of different technologies, such as radio frequency, magnetic field, visual light communications, or acoustics. Within these options, acoustics emerged as a promising alternative to obtain high-accuracy low-cost systems. Nevertheless, acoustic signals have to face very demanding propagation conditions, particularly in terms of multipath and Doppler effect. Therefore, even if many acoustic positioning systems have been proposed in the last decades, it remains an active and challenging topic. This article surveys the developed prototypes and commercial systems that have been presented since they first appeared around the 1980s to 2022. We classify these systems into different groups depending on the observable that they use to calculate the user position, such as the time-of-flight, the received signal strength, or the acoustic spectrum. Furthermore, we summarize the main properties of these systems in terms of accuracy, coverage area, and update rate, among others. Finally, we evaluate the limitations of these groups based on the link budget approach, which gives an overview of the system's coverage from parameters such as source and noise level, detection threshold, attenuation, and processing gain.Agencia Estatal de InvestigaciónResearch Council of Norwa

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Applications across Co-located Devices

We live surrounded by many computing devices. However, their presence has yet to be fully explored to create a richer ubiquitous computing environment. There is an opportunity to take better advantage of those devices by combining them into a unified user experience. To realize this vision, we studied and explored the use of a framework, which provides the tools and abstractions needed to develop applications that distribute UI components across co-located devices. The framework comprises the following components: authentication and authorization services; a broker to sync information across multiple application instances; background services that gather the capabilities of the devices; and a library to integrate web applications with the broker, determine which components to show based on UI requirements and device capabilities, and that provides custom elements to manage the distribution of the UI components and the multiple application states. Collaboration between users is supported by sharing application states. An indoor positioning solution had to be developed in order to determine when devices are close to each other to trigger the automatic redistribution of UI components. The research questions that we set out to respond are presented along with the contributions that have been produced. Those contributions include a framework for crossdevice applications, an indoor positioning solution for pervasive indoor environments, prototypes, end-user studies and developer focused evaluation. To contextualize our research, we studied previous research work about cross-device applications, proxemic interactions and indoor positioning systems. We presented four application prototypes. The first three were used to perform studies to evaluate the user experience. The last one was used to study the developer experience provided by the framework. The results were largely positive with users showing preference towards using multiple devices under some circumstances. Developers were also able to grasp the concepts provided by the framework relatively well.Vivemos rodeados de dispositivos computacionais. No entanto, ainda não tiramos partido da sua presença para criar ambientes de computação ubíqua mais ricos. Existe uma oportunidade de combiná-los para criar uma experiência de utilizador unificada. Para realizar esta visão, estudámos e explorámos a utilização de uma framework que forneça ferramentas e abstrações que permitam o desenvolvimento de aplicações que distribuem os componentes da interface do utilizador por dispositivos co-localizados. A framework é composta por: serviços de autenticação e autorização; broker que sincroniza informação entre várias instâncias da aplicação; serviços que reúnem as capacidades dos dispositivos; e uma biblioteca para integrar aplicações web com o broker, determinar as componentes a mostrar com base nos requisitos da interface e nas capacidades dos dispositivos, e que disponibiliza elementos para gerir a distribuição dos componentes da interface e dos estados de aplicação. A colaboração entre utilizadores é suportada através da partilha dos estados de aplicação. Foi necessário desenvolver um sistema de posicionamento em interiores para determinar quando é que os dispositivos estão perto uns dos outros para despoletar a redistribuição automática dos componentes da interface. As questões de investigação inicialmente colocadas são apresentadas juntamente com as contribuições que foram produzidas. Essas contribuições incluem uma framework para aplicações multi-dispositivo, uma solução de posicionamento em interiores para computação ubíqua, protótipos, estudos com utilizadores finais e avaliação com programadores. Para contextualizar a nossa investigação, estudámos trabalhos anteriores sobre aplicações multi-dispositivo, interação proxémica e sistemas de posicionamento em interiores. Apresentámos quatro aplicações protótipo. As primeiras três foram utilizadas para avaliar a experiência de utilização. A última foi utilizada para estudar a experiência de desenvolvimento com a framework. Os resultados foram geralmente positivos, com os utilizadores a preferirem utilizar múltiplos dispositivos em certas circunstâncias. Os programadores também foram capazes de compreender a framework relativamente bem

Sensors and Systems for Indoor Positioning

This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications