Roadside LiDAR Assisted Cooperative Localization for Connected Autonomous Vehicles

Advancements in LiDAR technology have led to more cost-effective production while simultaneously improving precision and resolution. As a result, LiDAR has become integral to vehicle localization, achieving centimeter-level accuracy through techniques like Normal Distributions Transform (NDT) and other advanced 3D registration algorithms. Nonetheless, these approaches are reliant on high-definition 3D point cloud maps, the creation of which involves significant expenditure. When such maps are unavailable or lack sufficient features for 3D registration algorithms, localization accuracy diminishes, posing a risk to road safety. To address this, we proposed to use LiDAR-equipped roadside unit and Vehicle-to-Infrastructure (V2I) communication to accurately estimate the connected autonomous vehicle's position and help the vehicle when its self-localization is not accurate enough. Our simulation results indicate that this method outperforms traditional NDT scan matching-based approaches in terms of localization accuracy.Comment: Accepted by 2023 International Conference on Intelligent Computing and its Emerging Application

A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks

The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has begun and many research challenges still need to be addressed. Location privacy continues to be in the top of these challenges. Indeed, both of academia and industry agreed to apply the pseudonym changing approach as a solution to protect the location privacy of VANETs'users. However, due to the pseudonyms linking attack, a simple changing of pseudonym shown to be inefficient to provide the required protection. For this reason, many pseudonym changing strategies have been suggested to provide an effective pseudonym changing. Unfortunately, the development of an effective pseudonym changing strategy for VANETs is still an open issue. In this paper, we present a comprehensive survey and classification of pseudonym changing strategies. We then discuss and compare them with respect to some relevant criteria. Finally, we highlight some current researches, and open issues and give some future directions

Optimization of vehicular networks in smart cities: from agile optimization to learnheuristics and simheuristics

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.Peer ReviewedPostprint (published version

Routing Unmanned Vehicles in GPS-Denied Environments

Most of the routing algorithms for unmanned vehicles, that arise in data gathering and monitoring applications in the literature, rely on the Global Positioning System (GPS) information for localization. However, disruption of GPS signals either intentionally or unintentionally could potentially render these algorithms not applicable. In this article, we present a novel method to address this difficulty by combining methods from cooperative localization and routing. In particular, the article formulates a fundamental combinatorial optimization problem to plan routes for an unmanned vehicle in a GPS-restricted environment while enabling localization for the vehicle. We also develop algorithms to compute optimal paths for the vehicle using the proposed formulation. Extensive simulation results are also presented to corroborate the effectiveness and performance of the proposed formulation and algorithms.Comment: Publised in International Conference on Umanned Aerial System

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

Natural computing for vehicular networks

La presente tesis aborda el diseño inteligente de soluciones para el despliegue de redes vehiculares ad-hoc (vehicular ad hoc networks, VANETs). Estas son redes de comunicación inalámbrica formada principalmente por vehículos y elementos de infraestructura vial. Las VANETs ofrecen la oportunidad para desarrollar aplicaciones revolucionarias en el ámbito de la seguridad y eficiencia vial. Al ser un dominio tan novedoso, existe una serie de cuestiones abiertas, como el diseño de la infraestructura de estaciones base necesaria y el encaminamiento (routing) y difusión (broadcasting) de paquetes de datos, que todavía no han podido resolverse empleando estrategias clásicas. Es por tanto necesario crear y estudiar nuevas técnicas que permitan de forma eficiente, eficaz, robusta y flexible resolver dichos problemas. Este trabajo de tesis doctoral propone el uso de computación inspirada en la naturaleza o Computación Natural (CN) para tratar algunos de los problemas más importantes en el ámbito de las VANETs, porque representan una serie de algoritmos versátiles, flexibles y eficientes para resolver problemas complejos. Además de resolver los problemas VANET en los que nos enfocamos, se han realizado avances en el uso de estas técnicas para que traten estos problemas de forma más eficiente y eficaz. Por último, se han llevado a cabo pruebas reales de concepto empleando vehículos y dispositivos de comunicación reales en la ciudad de Málaga (España). La tesis se ha estructurado en cuatro grandes fases. En la primera fase, se han estudiado los principales fundamentos en los que se basa esta tesis. Para ello se hizo un estudio exhaustivo sobre las tecnologías que emplean las redes vehiculares, para así, identificar sus principales debilidades. A su vez, se ha profundizado en el análisis de la CN como herramienta eficiente para resolver problemas de optimización complejos, y de cómo utilizarla en la resolución de los problemas en VANETs. En la segunda fase, se han abordado cuatro problemas de optimización en redes vehiculares: la transferencia de archivos, el encaminamiento (routing) de paquetes, la difusión (broadcasting) de mensajes y el diseño de la infraestructura de estaciones base necesaria para desplegar redes vehiculares. Para la resolución de dichos problemas se han propuesto diferentes algoritmos CN que se clasifican en algoritmos evolutivos (evolutionary algorithms, EAs), métodos de inteligencia de enjambre (swarm intelligence, SI) y enfriamiento simulado (simulated annealing, SA). Los resultados obtenidos han proporcionado protocolos de han mejorado de forma significativa las comunicaciones en VANETs. En la tercera y última fase, se han realizado experimentos empleando vehículos reales circulando por las carreteras de Málaga y que se comunicaban entre sí. El principal objetivo de estas pruebas ha sido el validar las mejoras que presentan los protocolos que se han optimizado empleando CN. Los resultados obtenidos de las fases segunda y tercera confirman la hipótesis de trabajo, que la CN es una herramienta eficiente para tratar el diseño inteligente en redes vehiculares

Reliable Message Dissemination in Mobile Vehicular Networks

Les réseaux véhiculaires accueillent une multitude d’applications d’info-divertissement et de sécurité. Les applications de sécurité visent à améliorer la sécurité sur les routes (éviter les accidents), tandis que les applications d’info-divertissement visent à améliorer l'expérience des passagers. Les applications de sécurité ont des exigences rigides en termes de délais et de fiabilité ; en effet, la diffusion des messages d’urgence (envoyés par un véhicule/émetteur) devrait être fiable et rapide. Notons que, pour diffuser des informations sur une zone de taille plus grande que celle couverte par la portée de transmission d’un émetteur, il est nécessaire d’utiliser un mécanisme de transmission multi-sauts. De nombreuses approches ont été proposées pour assurer la fiabilité et le délai des dites applications. Toutefois, ces méthodes présentent plusieurs lacunes. Cette thèse, nous proposons trois contributions. La première contribution aborde la question de la diffusion fiable des messages d’urgence. A cet égard, un nouveau schéma, appelé REMD, a été proposé. Ce schéma utilise la répétition de message pour offrir une fiabilité garantie, à chaque saut, tout en assurant un court délai. REMD calcule un nombre optimal de répétitions en se basant sur l’estimation de la qualité de réception de lien dans plusieurs locations (appelées cellules) à l’intérieur de la zone couverte par la portée de transmission de l’émetteur. REMD suppose que les qualités de réception de lien des cellules adjacentes sont indépendantes. Il sélectionne, également, un nombre de véhicules, appelés relais, qui coopèrent dans le contexte de la répétition du message d’urgence pour assurer la fiabilité en multi-sauts. La deuxième contribution, appelée BCRB, vise à améliorer REMD ; elle suppose que les qualités de réception de lien des cellules adjacentes sont dépendantes ce qui est, généralement, plus réaliste. BCRB utilise les réseaux Bayésiens pour modéliser les dépendances en vue d’estimer la qualité du lien de réception avec une meilleure précision. La troisième contribution, appelée RICS, offre un accès fiable à Internet. RICS propose un modèle d’optimisation, avec une résolution exacte optimale à l'aide d’une technique de réduction de la dimension spatiale, pour le déploiement des passerelles. Chaque passerelle utilise BCRB pour établir une communication fiable avec les véhicules.Vehicular networks aim to enable a plethora of safety and infotainment applications. Safety applications aim to preserve people's lives (e.g., by helping in avoiding crashes) while infotainment applications focus on enhancing the passengers’ experience. These applications, especially safety applications, have stringent requirements in terms of reliability and delay; indeed, dissemination of an emergency message (e.g., by a vehicle/sender involved in a crash) should be reliable while satisfying short delay requirements. Note, that multi-hop dissemination is needed to reach all vehicles, in the target area, that may be outside the transmission range of the sender. Several schemes have been proposed to provide reliability and short delay for vehicular applications. However, these schemes have several limitations. Thus, the design of new solutions, to meet the requirement of vehicular applications in terms of reliability while keeping low end-to-end delay, is required. In this thesis, we propose three schemes. The first scheme is a multi-hop reliable emergency message dissemination scheme, called REMD, which guarantees a predefined reliability , using message repetitions/retransmissions, while satisfying short delay requirements. It computes an optimal number of repetitions based on the estimation of link reception quality at different locations (called cells) in the transmission range of the sender; REMD assumes that link reception qualities of adjacent cells are independent. It also adequately selects a number of vehicles, called forwarders, that cooperate in repeating the emergency message with the objective to satisfy multi-hop reliability requirements. The second scheme, called BCRB, overcomes the shortcoming of REMD by assuming that link reception qualities of adjacent cells are dependent which is more realistic in real-life scenarios. BCRB makes use of Bayesian networks to model these dependencies; this allows for more accurate estimation of link reception qualities leading to better performance of BCRB. The third scheme, called RICS, provides internet access to vehicles by establishing multi-hop reliable paths to gateways. In RICS, the gateway placement is modeled as a k-center optimisation problem. A space dimension reduction technique is used to solve the problem in exact time. Each gateway makes use of BCRB to establish reliable communication paths to vehicles

Information collection algorithm for vehicular ad-hoc networks (application domain: Urban Traffic Wireless Vehicular Ad-Hoc Networks (VANETs))

Vehicle to vehicle communication (V2VC) is one of the modern approaches for exchanging and generating traffic information with (yet to be realized) potential to improve road safety, driving comfort and traffic control. In this research, we present a novel algorithm which is based on V2V communication, uses in-vehicle sensor information and in collaboration with the other vehicles' sensor information can detect road conditions and determine the geographical area where this road condition exists – e.g. geographical area where there is traffic density, unusual traffic behaviour, a range of weather conditions (raining), etc. The algorithms' built-in automatic geographical restriction of the data collection, aggregation and dissemination mechanisms allows warning messages to be received by any car, not necessarily sharing the identified road condition, which may then be used to identify the optimum route taken by the vehicle e.g. avoid bottlenecks or dangerous areas including accidents or congestions on their current routes. This research covers the middle ground between MANET [1] and collaborative data generation based on knowledge granularity (aggregation). It investigates the possibility of designing, implementing and modelling of the functionality of an algorithm (as part of the design of an intelligent node in an Intelligent Transportation System - ITS) that ensures active participation in the formation, routing and general network support of MANETs and also helps in-car traffic information and real-time control generation and distribution. The work is natural extension of the efforts of several large EU projects like DRIVE [2], GST [3] and SAFESPOT [4]