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

Implicit Cooperative Positioning in Vehicular Networks

Absolute positioning of vehicles is based on Global Navigation Satellite Systems (GNSS) combined with on-board sensors and high-resolution maps. In Cooperative Intelligent Transportation Systems (C-ITS), the positioning performance can be augmented by means of vehicular networks that enable vehicles to share location-related information. This paper presents an Implicit Cooperative Positioning (ICP) algorithm that exploits the Vehicle-to-Vehicle (V2V) connectivity in an innovative manner, avoiding the use of explicit V2V measurements such as ranging. In the ICP approach, vehicles jointly localize non-cooperative physical features (such as people, traffic lights or inactive cars) in the surrounding areas, and use them as common noisy reference points to refine their location estimates. Information on sensed features are fused through V2V links by a consensus procedure, nested within a message passing algorithm, to enhance the vehicle localization accuracy. As positioning does not rely on explicit ranging information between vehicles, the proposed ICP method is amenable to implementation with off-the-shelf vehicular communication hardware. The localization algorithm is validated in different traffic scenarios, including a crossroad area with heterogeneous conditions in terms of feature density and V2V connectivity, as well as a real urban area by using Simulation of Urban MObility (SUMO) for traffic data generation. Performance results show that the proposed ICP method can significantly improve the vehicle location accuracy compared to the stand-alone GNSS, especially in harsh environments, such as in urban canyons, where the GNSS signal is highly degraded or denied.Comment: 15 pages, 10 figures, in review, 201

Benets of tight coupled architectures for the integration of GNSS receiver and Vanet transceiver

Vehicular adhoc networks (VANETs) are one emerging type of networks that will enable a broad range of applications such as public safety, traffic management, traveler information support and entertain ment. Whether wireless access may be asynchronous or synchronous (respectively as in the upcoming IEEE 8021.11p standard or in some alternative emerging solutions), a synchronization among nodes is required. Moreover, the information on position is needed to let vehicular services work and to correctly forward the messages. As a result, timing and positioning are a strong prerequisite of VANETs. Also the diffusion of enhanced GNSS Navigators paves the way to the integration between GNSS receivers and VANET transceiv ers. This position paper presents an analysis on potential benefits coming from a tightcoupling between the two: the dissertation is meant to show to what extent Intelligent Transportation System (ITS) services could benefit from the proposed architectur

Open Platforms for Connected Vehicles

L'abstract è presente nell'allegato / the abstract is in the attachmen

SAI: safety application identifier algorithm at MAC layer for vehicular safety message dissemination over LTE VANET networks

Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks have been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission parameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-Term Evolution (LTE) under single cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE under multicell and multipath fading environment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. The urban vehicular radio environment has a significant impact and decreases the probability for end-to-end delay to be ≤100 ms from 93%–97% to 76%–78% compared to the Friis radio environment. The proposed algorithm reduces the amount of vehicular application traffic from 21 Mbps to 13 Mbps, while improving the probability of end-to-end delay being ≤100 ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%

Dissemination of contextual information for assisted driving

Mestrado em Engenharia Electrónica e TelecomunicaçõesDriver assistance systems can be used to improve road and car safety, reduce driving fatigue and provide a more e cient driving experience. An important part of these systems is the communication between vehicles, and vehicle-to-infrastructure communication. This work presents mechanisms enabling driving support, exploring the vehicular network to provide information about the drivers neighborhood. The network is composed by vehicles, tra c signals and xed stations along the road. Each car is equipped with a recording camera, a GPS receiver, as well as communication modules such as WiFi, WAVE and 3G/4G, allowing the exchange of data between the various nodes. The data exchanged is composed by positional data of neighboring vehicles, sensor information from tra c signals and video images incoming from other vehicles. This data is used to facilitate the driver in decision making, but can also provide an overview of the tra c density in the neighborhood. The tra c signals broadcast their position and if they are dynamic (such as tra c lights), their status is also transmitted. The xed stations are equipped with numerous sensors and are used to provide environmental data. The driver can access all the collected data via visual information, on a display screen that contains a map of the neighborhood along with the information available of the nearby nodes. The proposed system is evaluated through real vehicular experiments in two distinct scenarios: urban and highway. The results show that the communication delay is higher in the highway scenario, mainly due to the distance between vehicles and travelling speeds. However, promising results regarding the maximum delay and the average number of retransmissions foresee important inputs for future services of assisted-driving, in general, and carovertaking assistance, in particular.Os sistemas de condução assistida podem ser utilizados para melhorar a segurança rodoviária e automóvel, reduzir a fadiga da condução e proporcionar uma experiência de condução mais e ciente. Uma parte importante desses sistemas e a comunicação entre veículos e comunicação veiculo infraestrutura. Este trabalho propõe mecanismos que permitem o suporte a condução, explorando a rede de veicular para fornecer informações sobre a vizinhança do condutor. A rede e composta por veículos, sinais de transito e estações fixas ao longo da estrada. Cada carro esta equipado com uma camera de gravação, um receptor GPS, bem como módulos de comunicação, como WiFi, WAVE e 3G/4G, permitindo a troca de dados entre os vários nos. Os dados trocados são compostos por dados posicionais de veículos vizinhos, informações sensoriais de sinais de trânsito e imagens de vídeo provenientes de outros veículos. Esses dados s~ao usados para facilitar a tomada de decisões, mas também podem fornecer uma vis~ao geral da densidade de tráfego na vizinhança. Os sinais de transito transmitem a sua posição e, no caso de serem dinâmicos (como semáforos), o seu estado actual também e transmitido. As estações fixas estão equipadas com vários sensores e sao usadas para fornecer dados ambientais. O condutor pode aceder a todos os dados recolhidos através de informações visuais, num ecrã que contém um mapa da sua redondeza junto com a informação disponível dos nos vizinhos. O sistema proposto e avaliado através de testes reais em dois cenários distintos: urbano e auto-estrada. Os resultados mostram que o atraso da comunicação e maior no cenário da auto-estrada, principalmente devido as maiores distancias entre os veículos e as velocidades mais elevadas. No entanto, resultados promissores em relação ao atraso máximo e ao numero médio de retransmissões prevêem contribuições importantes para serviços futuros de condução assistida em geral, e assistência de ultrapassagem de veículos, em particular

An Empirical Study on V2X Enhanced Low-Cost GNSS Cooperative Positioning in Urban Environments

High-precision and lane selective position estimation is of fundamental importance for prospective advanced driver assistance systems (ADAS) and automated driving functions, as well as for traffic information and management processes in intelligent transportation systems (ITS). User and vehicle positioning is usually based on Global Navigation Satellite System (GNSS), which, as stand-alone positioning, does not meet the necessary requirements in terms of accuracy. Furthermore, the rise of connected driving offers various possibilities to enhance GNSS positioning by applying cooperative positioning (CP) methods. Utilizing only low-cost sensors, especially in urban environments, GNSS CP faces several demanding challenges. Therefore, this contribution presents an empirical study on how Vehicle-to-Everything (V2X) technologies can aid GNSS position estimation in urban environments, with the focus being solely on positioning performance instead of multi-sensor data fusion. The performance of CP utilizing common positioning approaches as well as CP integration in state-of-the-art Vehicular Ad-hoc Networks (VANET) is displayed and discussed. Additionally, a measurement campaign, providing a representational foundation for validating multiple CP methods using only consumer level and low-cost GNSS receivers, as well as commercially available IEEE 802.11p V2X communication modules in a typical urban environment is presented. Evaluating the algorithm&rsquo s performance, it is shown that CP approaches are less accurate compared to single positioning in the given environment. In order to investigate error influences, a skyview modelling seeking to identify non-line-of-sight (NLoS) effects using a 3D building model was performed. We found the position estimates to be less accurate in areas which are affected by NLoS effects such as multipath reception. Due to covariance propagation, the accuracy of CP approaches is decreased, calling for strategies for multipath detection and mitigation. In summary, this contribution will provide insights on integration, implementation strategies and accuracy performances, as well as drawbacks for local area, low-cost GNSS CP in urban environments. Document type: Articl

Wake-up radio systems for cooperative-intelligent transport systems architecture

© 2019 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.Cooperative-Intelligent Transport systems are new applications developed on top of communications between vehicles and between vehicles and fixed infrastructure. Their architecture envisages devices deployed along the routes and streets, transmitting and receiving different kind of messages belonging to different services. Quite often, these devices will be located in isolated places with very low number of vehicles passing nearby. Being in isolated places, these devices will require to be feed with rechargeable batteries and alternative power sources, the usage of which need to be very efficient. The fact of continuously transmitting messages whenever there is no vehicle to receive them demands a solution. In this paper, we propose to use a well-known saving power strategy already used in Internet of Things, the Wake-up Radio systems. As vehicular communications are based on IEEE 802.11 standard, we propose to use a Wake-up Radio system based on this standard as well, being thus no additional hardware needed for the wake-up transmitter. The paper analyses the feasibility of using this solution on several vehicular applications.Peer ReviewedPostprint (author's final draft

Vehicular communication management framework : a flexible hybrid connectivity platform for CCAM services

In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a lack of real flexible and modular platforms that can support the need for hybrid communication. In this paper, we propose a novel vehicular communication management framework (CAMINO), which incorporates flexible support for both short-range direct and long-range cellular technologies and offers built-in Cooperative Intelligent Transport Systems' (C-ITS) services for experimental validation in real-life settings. Moreover, integration with vehicle and infrastructure sensors/actuators and external services is enabled using a Distributed Uniform Streaming (DUST) framework. The framework is implemented and evaluated in the Smart Highway test site for two targeted use cases, proofing the functional operation in realistic environments. The flexibility and the modular architecture of the hybrid CAMINO framework offers valuable research potential in the field of vehicular communications and CCAM services and can enable cross-technology vehicular connectivity