Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks

Kinematic Galileo and GPS Performances in Aerial, Terrestrial, and Maritime Environments

On 15 December 2016, the European Commission (EC) declared the provision of the Galileo Initial Services (IS). This marked a historical milestone in the Galileo program, towards the reaching of its Full Operational Capability. This allows users to navigate with performance-accuracy levels either matching or exceeding those obtained with other GNSS. Under the delegation of the EC, the European Union Agency for the Space Programme (EUSPA) has assumed the role of the Galileo Service Provider. As part of this service provision, the primary mission of the Galileo Reference Centre (GRC) is to provide the EUSPA and the EC with independent means for monitoring and evaluating the performance of the Galileo services, the quality of the signals in space, and the performance of other GNSS. This mission includes significant contributions from cooperating entities in the European Union (EU) Member States (MS), Norway and Switzerland. In particular, for a detailed assessment of the Galileo performance, these contributions include (but are not limited to) periodic dynamic campaigns in three different environments (aerial, terrestrial, and maritime). These campaigns were executed in the frame of the GRC-MS Project and use multi-constellation receivers to compare the navigation performance obtained with different GNSS. The objective of this paper is to present the numerical results obtained from these campaigns, together with several considerations about the experimental setup, the methodology for the estimation of the reference («actual») trajectory, and the reasons for possible performance degradations

モービルマッピングシステムと航空測量を用いた都市空間高精度３次元モデリング

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 瀬崎 薫, 東京大学教授 江崎 浩, 東京大学教授 苗村 健, 東京大学教授 柴崎 亮介, 東京大学准教授 上條 俊介, 国際電気通信基礎技術研究所 浅見 徹University of Tokyo(東京大学

Efficient deployment of satellite navigation systems in Finland : Action plan 2021-2025

Satellite navigation has become a part of our everyday life as one of the applications we use daily, and we often take the availability of exact location and time data for granted. In addition to consumer applications, many of society's key operations rely on satellite navigation systems. This means that monitoring their development and continuously adopting their new features presents an opportunity to make our everyday lives smoother, more efficient and safer. The objective of the Finnish space strategy is to make Finland the most attractive and agile space business environment by 2025, benefitting all companies operating in Finland. This operational programme follows the "Efficient deployment of satellite navigation systems in Finland, Operational programme 2017-2020" by the Ministry of Transport and Communications. The programme's objective is to ensure the efficient utilisation of satellite navigation systems in Finland in the coming years as well. The overview in the beginning describes the current state of GNSS systems and their supporting systems, space administration interest groups and the most important application areas in which services generated by GNSS systems are utilised. The final chapter of the document defines 19 concrete actions that observe Finland's objectives in international cooperation in developing GNSS systems, building national preparedness, maintaining competence and adopting the use of services offered by satellite navigation as part of end user applications

Enabling Multi-LiDAR Sensing in GNSS-Denied Environments: SLAM Dataset, Benchmark, and UAV Tracking with LiDAR-as-a-camera

The rise of Light Detection and Ranging (LiDAR) sensors has profoundly impacted industries ranging from automotive to urban planning. As these sensors become increasingly affordable and compact, their applications are diversifying, driving precision, and innovation. This thesis delves into LiDAR's advancements in autonomous robotic systems, with a focus on its role in simultaneous localization and mapping (SLAM) methodologies and LiDAR as a camera-based tracking for Unmanned Aerial Vehicles (UAV). Our contributions span two primary domains: the Multi-Modal LiDAR SLAM Benchmark, and the LiDAR-as-a-camera UAV Tracking. In the former, we have expanded our previous multi-modal LiDAR dataset by adding more data sequences from various scenarios. In contrast to the previous dataset, we employ different ground truth-generating approaches. We propose a new multi-modal multi-lidar SLAM-assisted and ICP-based sensor fusion method for generating ground truth maps. Additionally, we also supplement our data with new open road sequences with GNSS-RTK. This enriched dataset, supported by high-resolution LiDAR, provides detailed insights through an evaluation of ten configurations, pairing diverse LiDAR sensors with state-of-the-art SLAM algorithms. In the latter contribution, we leverage a custom YOLOv5 model trained on panoramic low-resolution images from LiDAR reflectivity (LiDAR-as-a-camera) to detect UAVs, demonstrating the superiority of this approach over point cloud or image-only methods. Additionally, we evaluated the real-time performance of our approach on the Nvidia Jetson Nano, a popular mobile computing platform. Overall, our research underscores the transformative potential of integrating advanced LiDAR sensors with autonomous robotics. By bridging the gaps between different technological approaches, we pave the way for more versatile and efficient applications in the future

Lane-Level Localization and Map Matching for Advanced Connected and Automated Vehicle (CAV) Applications

USDOT Grant 69A3551747114Reliable, lane-level, absolute position determination for connected and automated vehicles (CAV\u2019s) is near at hand due to advances in sensor and computing technology. These capabilities in conjunction with high-definition maps enable lane determination, per lane queue determination, and enhanced performance in applications. This project investigated, analyzed, and demonstrated these related technologies. Project contributions include: (1) Experimental analysis demonstrating that the USDOT Mapping tool achieves internal horizontal accuracy better than 0.2 meters (standard deviation); (2) Theoretical analysis of lane determination accuracy as a function of both distance from the lane centerline and positioning accuracy; (3) Experimental demonstration and analysis of lane determination along the Riverside Innovation Corridor showing that for a vehicle driven within 0.9 meters of the lane centerline, the correct lane is determined for over 90% of the samples; (4) Development of a VISSIM position error module to enable simulation analysis of lane determination and lane queue estimation as a function of positioning error; (5) Development of a lane-level intersection queue prediction algorithm; Simulation evaluation of lane determination accuracy which matched the theoretical analysis; and (6) Simulation evaluation of lane queue prediction accuracy as a function of both CAV penetration rate and positioning accuracy. Conclusions of the simulation analysis in item (6) are the following: First, when the penetration rate is fixed, higher queue length estimation error occurs as the position error increases. However, the disparity across different position error levels diminishes with the decrease of penetration rate. Second, as the penetration rate decreases, the queue length estimation error significantly increases under the same GNSS error level. The current methods that exist for queue length prediction only utilize vehicle position and a penetration rate estimate. These results motivate the need for new methods that more fully utilize the information available on CAVs (e.g., distance to vehicles in front, back, left, and right) to decrease the sensitivity to penetration rate

Precise positioning in real-time using GPS-RTK signal for visually impaired people navigation system

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 24/9/2010.This thesis presents the research carried out to investigate and achieve highly reliable and accurate navigation system of guidance for visually impaired pedestrians. The main aim with this PhD project has been to identify the limits and insufficiencies in utilising Network Real-Time Kinematic Global Navigation Satellite Systems (NRTK GNSS) and its augmentation techniques within the frame of pedestrian applications in a variety of environments and circumstances. Moreover, the system can be used in many other applications, including unmanned vehicles, military applications, police, etc. NRTK GNSS positioning is considered to be a superior solution in comparison to the conventional standalone Global Positioning System (GPS) technique whose accuracy is highly affected by the distance dependent errors such as satellite orbital and atmospheric biases. Nevertheless, NRTK GNSS positioning is particularly constrained by wireless data link coverage, delays of correction and transmission and completeness, GPS and GLONASS signal availability, etc., which could downgrade the positioning quality of the NRTK results. This research is based on the dual frequency NRTK GNSS (GPS and GLONASS). Additionally, it is incorporated into several positioning and communication methods responsible for data correction while providing the position solutions, in which all identified contextual factors and application requirements are accounted. The positioning model operates through client-server based architecture consisted of a Navigation Service Centre (NSC) and a Mobile Navigation Unit (MNU). Hybrid functional approaches were consisting of several processing procedures allowing the positioning model to operate in position determination modes. NRTK GNSS and augmentation service is used if enough navigation information was available at the MNU using its local positioning device (GPS/GLONASS receiver).The positioning model at MNU was experimentally evaluated and centimetric accuracy was generally attained during both static and kinematic tests in various environments (urban, suburban and rural). This high accuracy was merely affected by some level of unavailability mainly caused by GPS and GLONASS signal blockage. Additionally, the influence of the number of satellites in view, dilution of precision (DOP) and age corrections (AoC) over the accuracy and stability of the NRTK GNSS solution was also investigated during this research and presented in the thesis. This positioning performance has outperformed the existing GPS service. In addition, utilising a simulation evaluation facility the positioning model at MNU performance was quantified with reference to a hybrid positioning service that will be offered by future Galileo Open Service (OS) along with GPS. However, a significant difference in terms of the service availability for the advantage of the hybrid system was experienced in all remaining scenarios and environments more especially the urban areas due to surrounding obstacles and conditions. As an outcome of this research a new and precise positioning model was proposed. The adaptive framework is understood as approaching an integration of the available positioning technology into the context of surrounding wireless communication for a maintainable performance. The positioning model has the capability of delivering indeed accurate, precise and consistent position solutions, and thus is fulfilling the requirements of visually impaired people navigation application, as identified in the adaptive framework

SaPPART White paper. Better use of Global Navigation Satellite Systems for safer and greener transport

Transport and mobility services are crucial to the society that faces important challenges. Up to date, transport facilities and services have been fundamental to economic growth. However, there have significant and unacceptable negative impacts on the environment including pollution, noise and climate change. Therefore, it is paramount that the efficiency of the transport system is improved significantly including lower consumption of energy. A way of achieving this is through the concept of smart transport that exploits Intelligent Transport Systems (ITS) technology. ITS are built on three technology pillars: information, communication and positioning technologies. Of the three technologies, positioning could be argued to be the least familiar amongst transport stakeholders. However, a quick investigation reveals that there are a wide variety of transport and related services often associated with communication technologies that are supported by positioning. Currently, the positioning is provided in the majority of the cases by Global Navigation Satellite System (GNSS), among which the Global Positioning System (GPS) is the pioneer and still the most widely used system. The other current fully operational stand-alone system is Russia’s GLONASS. As these operational systems were not originally and specifically designed for transport applications, the actual capabilities and limitations of the current GNSS are not fully understood by many stakeholders. Therefore, better knowledge of these limitations and their resolution should enable a much more rapid deployment of ITS. This white paper is produced by the members of the COST Action SaPPART with two principal aims. The first is to explain the principles, state-of-the-art performance of GNSS technology and added value in the field of transport. The second aim is to deliver key messages to the stakeholders to facilitate the deployment of GNSS technology and thus contribute to the development of smarter and greener transport systems. The first chapter highlights the important role of positioning in today transport systems and the added value of accurate and reliable positioning for critical systems. The second chapter is about positioning technologies for transport: GNSS and their different aiding and augmentation methods are described, but the other complementary technologies are also introduced. The third and last chapter is about the management of performances inside a positioning-based intelligent transport system, between the positioning system itself and the application-specific part of the system which processes the raw position for delivering its service