MAVEN Deliverable 6.4: Integration Final Report

This document presents the work that has been performed in WP6 after D6.3, and therefore focussing on the integration sprints 3-6. It describes which parts of the system are implemented and how they are put together. To do so, it builds upon the deliverables created so far, esp. D6.3 and all other deliverables of the underlying work packages 3, 4 and 5. Another important aspect for understanding the content of this deliverable is D2.1 [4] for the scenario definition of the whole MAVEN project, and the deliverables D6.1 [5] and D6.2 [6], which give an overview on the existing infrastructure and vehicles used in MAVEN

Connected Vehicle Technology: User and System Performance Characteristics

The emerging connected vehicle (CV) technology plays a promising role in providing more operable and safer transportation environments. Yet, many questions remain unanswered as to how various user and system characteristics of CV-enabled networks can shape the successful implementation of the technology to maximize the return on investment. This research attempts to capture the effect of multiple factors such as traffic density, market penetration, and transmission range on the communication stability and overall network performance by developing a new CONnectivity ROBustness (CONROB) model. The model was tested with data collected from microscopic simulation of a 195 sq-mile traffic network and showed a potential to capture the effect of such factors on the communication stability in CV environments. The information exchanged among CVs can also be used to estimate traffic conditions in real time by invoking the probe vehicle feature of CV technology. Since factors affecting the connectivity robustness also have an impact on the performance of traffic condition estimation models, a direct relationship between connectivity robustness and traffic condition estimation performance was established. Simulation results show that the CONROB model can be used as a tool to predict the accuracy of the estimated traffic conditions (e.g. travel times), as well as the reliability of such estimates, given specific system characteristics. The optimal deployment of road-side units (RSUs) is another important factor that affects the communication stability and the traffic conditions estimates and reliability. Thus, an optimization approach was developed to identify the optimal RSUs locations with the objective function of maximizing the connectivity robustness. Simulation results for the developed approach show that CONROB model can help identify the optimal RSUs locations. This shows the importance of CONROB model as a planning tool for CV environments. For the individual user performance characteristics, a preliminary driving simulator test bed for CV technology was developed and tested on thirty licensed drivers. Forward collision warning messages were delivered to drivers when predefined time-to-collision values take place. The findings show improved reaction times of drivers when receiving the warning messages which lend credence to the safety benefits of the CV technology

Autonomous vehicles: From vehicular control to traffic control

International audienc

Quality of service aware data dissemination in vehicular Ad Hoc networks

Des systèmes de transport intelligents (STI) seront éventuellement fournis dans un proche avenir pour la sécurité et le confort des personnes lors de leurs déplacements sur les routes. Les réseaux ad-hoc véhiculaires (VANETs) représentent l'élément clé des STI. Les VANETs sont formés par des véhicules qui communiquent entre eux et avec l'infrastructure. En effet, les véhicules pourront échanger des messages qui comprennent, par exemple, des informations sur la circulation routière, les situations d'urgence et les divertissements. En particulier, les messages d'urgence sont diffusés par des véhicules en cas d'urgence (p.ex. un accident de voiture); afin de permettre aux conducteurs de réagir à temps (p.ex., ralentir), les messages d'urgence doivent être diffusés de manière fiable dans un délai très court. Dans les VANETs, il existe plusieurs facteurs, tels que le canal à pertes, les terminaux cachés, les interférences et la bande passante limitée, qui compliquent énormément la satisfaction des exigences de fiabilité et de délai des messages d'urgence. Dans cette thèse, en guise de première contribution, nous proposons un schéma de diffusion efficace à plusieurs sauts, appelé Dynamic Partitioning Scheme (DPS), pour diffuser les messages d'urgence. DPS calcule les tailles de partitions dynamiques et le calendrier de transmission pour chaque partition; à l'intérieur de la zone arrière de l'expéditeur, les partitions sont calculées de sorte qu'en moyenne chaque partition contient au moins un seul véhicule; l'objectif est de s'assurer que seul un véhicule dans la partition la plus éloignée (de l'expéditeur) est utilisé pour diffuser le message, jusqu'au saut suivant; ceci donne lieu à un délai d'un saut plus court. DPS assure une diffusion rapide des messages d'urgence. En outre, un nouveau mécanisme d'établissement de liaison, qui utilise des tonalités occupées, est proposé pour résoudre le problème du problème de terminal caché. Dans les VANETs, la Multidiffusion, c'est-à-dire la transmission d'un message d'une source à un nombre limité de véhicules connus en tant que destinations, est très importante. Par rapport à la diffusion unique, avec Multidiffusion, la source peut simultanément prendre en charge plusieurs destinations, via une arborescence de multidiffusion, ce qui permet d'économiser de la bande passante et de réduire la congestion du réseau. Cependant, puisque les VANETs ont une topologie dynamique, le maintien de la connectivité de l'arbre de multidiffusion est un problème majeur. Comme deuxième contribution, nous proposons deux approches pour modéliser l'utilisation totale de bande passante d'une arborescence de multidiffusion: (i) la première approche considère le nombre de segments de route impliqués dans l'arbre de multidiffusion et (ii) la seconde approche considère le nombre d'intersections relais dans l'arbre de multidiffusion. Une heuristique est proposée pour chaque approche. Pour assurer la qualité de service de l'arbre de multidiffusion, des procédures efficaces sont proposées pour le suivi des destinations et la surveillance de la qualité de service des segments de route. Comme troisième contribution, nous étudions le problème de la congestion causée par le routage du trafic de données dans les VANETs. Nous proposons (1) une approche de routage basée sur l’infonuagique qui, contrairement aux approches existantes, prend en compte les chemins de routage existants qui relaient déjà les données dans les VANETs. Les nouvelles demandes de routage sont traitées de sorte qu'aucun segment de route ne soit surchargé par plusieurs chemins de routage croisés. Au lieu d'acheminer les données en utilisant des chemins de routage sur un nombre limité de segments de route, notre approche équilibre la charge des données en utilisant des chemins de routage sur l'ensemble des tronçons routiers urbains, dans le but d'empêcher, dans la mesure du possible, les congestions locales dans les VANETs; et (2) une approche basée sur le réseau défini par logiciel (SDN) pour surveiller la connectivité VANET en temps réel et les délais de transmission sur chaque segment de route. Les données de surveillance sont utilisées en entrée de l'approche de routage.Intelligent Transportation Systems (ITS) will be eventually provided in the near future for both safety and comfort of people during their travel on the roads. Vehicular ad-hoc Networks (VANETs), represent the key component of ITS. VANETs consist of vehicles that communicate with each other and with the infrastructure. Indeed, vehicles will be able to exchange messages that include, for example, information about road traffic, emergency situations, and entertainment. Particularly, emergency messages are broadcasted by vehicles in case of an emergency (e.g., car accident); in order to allow drivers to react in time (e.g., slow down), emergency messages must be reliably disseminated with very short delay. In VANETs, there are several factors, such as lossy channel, hidden terminals, interferences and scarce bandwidth, which make satisfying reliability and delay requirements of emergency messages very challenging. In this thesis, as the first contribution, we propose a reliable time-efficient and multi-hop broadcasting scheme, called Dynamic Partitioning Scheme (DPS), to disseminate emergency messages. DPS computes dynamic partition sizes and the transmission schedule for each partition; inside the back area of the sender, the partitions are computed such that in average each partition contains at least a single vehicle; the objective is to ensure that only a vehicle in the farthest partition (from the sender) is used to disseminate the message, to next hop, resulting in shorter one hop delay. DPS ensures fast dissemination of emergency messages. Moreover, a new handshaking mechanism, that uses busy tones, is proposed to solve the problem of hidden terminal problem. In VANETs, Multicasting, i.e. delivering a message from a source to a limited known number of vehicles as destinations, is very important. Compared to Unicasting, with Multicasting, the source can simultaneously support multiple destinations, via a multicast tree, saving bandwidth and reducing overall communication congestion. However, since VANETs have a dynamic topology, maintaining the connectivity of the multicast tree is a major issue. As the second contribution, we propose two approaches to model total bandwidth usage of a multicast tree: (i) the first approach considers the number of road segments involved in the multicast tree and (ii) the second approach considers the number of relaying intersections involved in the multicast tree. A heuristic is proposed for each approach. To ensure QoS of the multicasting tree, efficient procedures are proposed for tracking destinations and monitoring QoS of road segments. As the third contribution, we study the problem of network congestion in routing data traffic in VANETs. We propose (1) a Cloud-based routing approach that, in opposition to existing approaches, takes into account existing routing paths which are already relaying data in VANETs. New routing requests are processed such that no road segment gets overloaded by multiple crossing routing paths. Instead of routing over a limited set of road segments, our approach balances the load of communication paths over the whole urban road segments, with the objective to prevent, whenever possible, local congestions in VANETs; and (2) a Software Defined Networking (SDN) based approach to monitor real-time VANETs connectivity and transmission delays on each road segment. The monitoring data is used as input to the routing approach

The potential of naturalistic driving studies with simple data acquisition systems (DAS) for monitoring driver behaviour

This report addresses the important question regarding the potential of simple and low-cost technologies to address research questions such as the ones dealt with in UDrive. The resources and efforts associated with big naturalistic studies, such as the American SHRP II and the European UDrive, are tremendous and can not be repeated and supported frequently, or even more than once in a decade (or a life time..). Naturally, the wealth and richness of the integrated data, gathered by such substantial studies and elaborated DAS, cannot be compared to data collected via simpler, nomadic data collection technologies. The question that needs to be asked is how many Research Questions (RQs) can be addressed, at least to some extent, by other low-cost and simple technologies? This discussion is important, not only in order to replace the honourable place (and cost!) of naturalistic studies, but also to complement and enable their continuity after their completion. Technology is rapidly evolving and almost any attempt to provide a comprehensive and complete state of the art of existing technologies (as well as their features and cost) is doomed to fail. Hence, in chapter 1 of this report, we have created a framework for presentation, on which the various important parameters associated with the question at hand, are illustrated, positioned and discussed. This framework is denoted by “Framework for Naturalistic Studies” (FNS) and serves as the back bone of this report. The framework is a conceptual framework and hence, is flexible in the sense that its dimensions, categories and presentation mode are not rigid and can be adjusted to new features and new technologies as they become available. The framework is gradually built using two main dimensions: data collection technology type and sample size. The categories and features of the main dimensions are not rigidly fixed, and their values can be ordinal, quantitative or qualitative. When referring to parameters that are not numerical –even the order relation among categories is not always clear. In this way –the FNS can be, at times, viewed as a matrix rather than a figure with order relation among categories presented along its axes. On the two main dimensions of the FNS –data collection technology type and sample size –other dimensions are incorporated. These dimensions include: cost, data access, specific technologies and research questions that can be addressed by the various technologies. These other dimensions are mapped and positioned in the plot area of the FNS. Other presentations, in which the axes and the plot area are interchanged, or 3 -dimensional presentations are performed, can be incorporated to highlight specific angles of the involved dimensions. The various technologies for data collection were mapped on the FNS. The technology groups include: mobile phone location services, mobile phone applications, telematics devices, built -in data loggers, dash cameras and enhanced dash cameras, wearable technologies, compound systems, eye trackers and Mobileyetype technologies. After this detailed illustrations of analyses that can be conducted using simple low-cost technologies are described. It is demonstrated how temporal and spatial analysis can reveal important aspects on the behavioural patterns of risky drivers. Also one stand alone smartphone app can be used to monitor and evaluate smartphone us age while driving. Most of the simple systems relate to specific behaviour that is monitored (i.e. speeding , lane keeping etc.). Additionally, certain thresholds or triggers are used to single out risky situations, which are related to that behaviour. However, once those instances are detected, no information on the circumstances leading or accompanying this behaviour are available. Typically, visual information (discrete or preferably continuous) is needed in order to fully understand the circumstances. Hence, upgrading simple (single-task oriented) technologies by other technologies (most typically by cameras), can significantly improve researchers' ability to obtain information on the circumstances, which accompany the detected risky behaviour. One of the most conceptually straightforward integrated systems is a system, for which the basic technology detects the desired behaviour (e.g. harsh braking) and triggers a simple continuous dashboard camera to save the relevant information, which occurs together with that behaviour. Many RQs can be addressed using this type of combined systems

A Survey of Deep Learning Applications to Autonomous Vehicle Control

Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex environment and inability to test the system in the wide variety of scenarios which it may encounter after deployment. However, deep learning methods have shown great promise in not only providing excellent performance for complex and non-linear control problems, but also in generalising previously learned rules to new scenarios. For these reasons, the use of deep learning for vehicle control is becoming increasingly popular. Although important advancements have been achieved in this field, these works have not been fully summarised. This paper surveys a wide range of research works reported in the literature which aim to control a vehicle through deep learning methods. Although there exists overlap between control and perception, the focus of this paper is on vehicle control, rather than the wider perception problem which includes tasks such as semantic segmentation and object detection. The paper identifies the strengths and limitations of available deep learning methods through comparative analysis and discusses the research challenges in terms of computation, architecture selection, goal specification, generalisation, verification and validation, as well as safety. Overall, this survey brings timely and topical information to a rapidly evolving field relevant to intelligent transportation systems.Comment: 23 pages, 3 figures, Accepted in IEEE Transactions on Intelligent Transportation System

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Advisory Safety System for Autonomous Vehicles under Sun-glare

Autonomous Vehicles (AVs) are expected to provide a large number of benefits such as improving comfort, vehicle safety and traffic flow. AVs use various sensors and control systems to empower driver’s decision-making under uncertainties as well as, assist the driving task under adverse conditions such as vision impairment. Excessive sunlight has been recognized as the primary source of the reduction in vision performance during daytime. Sun glare oftentimes leads to an impaired visibility for drivers and has been studied from different aspects on roadways. However, there is a lack of knowledge regarding the potential detrimental effects of natural light brightness differential, particularly sun glare on driving behavior and its possible risks. This dissertation addresses this issue by developing an integrated vehicle safety methodology as an advisory system for safe driving under sun glare. The main contribution of this research is to establish a real-time detection of the vision impairment area on roadways. This study also proposes a Collision Avoidance System Under Sun-glare (CASUS) in which upcoming possible vision impairment is detected, a warning message is sent, and the speed of vehicle is adjusted accordingly. In this context, real-world data is used to calibrate a psychophysical car-following model within VISSIM, a traffic microscopic simulation tool. Traffic safety impacts are explored through the number of conflicts extracted from the microsimulation tool and assessed by the time-to-collision indicator. Conventional/human-driven vehicles and different type of AVs are modeled for a straight segment of the TransCanada highway under various AVs penetration rates. The findings revealed a significant reduction in potential collisions due to adjustment of travel speed of AVs under the sun glare. The results also indicated that applying CASUS to the AVs with a failing sensory system improves traffic safety by providing optimal-safe speeds. Furthermore, the CASUS algorithm has the potential to be integrated into driving simulators or real vehicles to further evaluate and examine its benefits under different vision impairment scenarios