Study on Perception and Communication Systems for Safety of Vulnerable Road Users

International audience—The existing R&D efforts for protecting vulnerable road users (VRU) are mainly based on perception techniques, which aim to detect VRUs utilizing vehicle embedded sensors. The efficiency of such a technique is largely affected by the sensor's visibility condition. Vehicle-to-Pedestrian (V2P) communication can also contribute to the VRU safety by allowing vehicles and pedestrians to exchange information. This solution is, however, largely affected by the reliability of the exchanged information, which most generally is the GPS data. Since perception and communication have complementary features, we can expect that a combination of such approaches can be a solution to the VRU safety. This is the motivation of the current work. We develop theoretical models to present the characteristics of perception and communications systems. Experimental studies are conducted to compare the performances of these techniques in real-world environments. Our results show that the perception system reliably detects pedestrians and other objects within 50 m of range in the line-of-sight (LOS) condition. In contrast, the V2P communication coverage is approximately 340 and 200 meters in LOS and non-LOS (NLOS) conditions, respectively. However, the communication-based system fails to correctly position the VRU w.r.t the vehicle, preventing the system from meeting the safety requirement. Finally, we propose a cooperative system that combines the outputs of the communication and perception systems

Fusion of Perception and V2P Communication Systems for Safety of Vulnerable Road Users

International audienceWith cooperative intelligent transportation systems (C-ITS), vulnerable road users (VRU) safety can be enhanced by multiple means.On one hand, perception systems are based on embedded sensors to protect VRUs. However, such systems may fail due to the sensors' visibility conditions and imprecision. On the other hand, Vehicle-to-Pedestrian (V2P) communication can contribute to the VRU safety by allowing vehicles and pedestrians to exchange information. This solution is, however, largely affected by the reliability of the exchanged information, which most generally is the GPS data. Since perception and communication have complementary features, we can expect that a fusion between these two approaches can be a solution to the VRU safety. In this work, we propose a cooperative system that combines the outputs of communication and perception. After introducing theoretical models of both individual approaches, we develop a probabilistic association between perception and V2P communication information by means of multi-hypothesis tracking (MHT). Experimental studies are conducted to demonstrate the applicability of this approach in real-world environments. Our results show that the cooperative VRU protection system can benefit of the redundancy coming from the perception and communication technologies both in line-of-sight (LOS) and non-LOS (NLOS) conditions. We establish that the performances of this system are influenced by the classification performances of the perception system and by the accuracy of the GPS positioning transmitted by the communication system

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

DECOMOBIL Roadmap for research on Human Centred Design of ICT for clean and safe mobility. Deliverable 2.2

The scientific seminar on 'Roadmap of Information & Communication Technology design for clean and efficient multimodal mobility' organized by Ifsttar in the framework of the European project DECOMOBIL, has been held the 28th of May 2013 in Munich, Germany. The aims of the event were to overview perspectives of research in the domain of ICT and green transport, with presentation of the main key issues, the on-going major projects, some outstanding results and the scientific and technical lacks of knowledge to overcome, in order to debate about future steps to follow to reach identified and consensual objectives in this domain. Speakers have been identified as key experts in the ecomobility research areas, with diversified points of view and approaches, in order to give to the audience a holistic vision of this issue. During this seminar, an overview of European projects on ecomobility such as eCoMove, compass4D, Adasis, Amitran, has been provided. Experience gained from the iMobility WG on ICT for clean and efficient mobility, which aims providing a vision on eco-friendly mobility, has been presented. Priorities for road safety research in Europe have been defined through the presentation of the PROS project, and transport cross-modal considerations on safety and human factors have been discussed through the presentation of the EXCROSS project. Perspectives on Powered-Two-Wheels contribution to ecomobility in addition to sustainable driving/riding training for a safe and cost efficient behavior have been drawn. Finally, main issues related to design, integration and safety of mobile service for ecomobility and concept of cooperative services have been presented and discussed.A round table allowed the audience to interact in a fruitful way with all the speakers of the day.After summarizing the context linked to ecomobility at a European level, this report gathers a summary of each presentation in addition to the full set of slides displayed at the seminar.Furthermore, all the presentations (slides and video recordings of the speakers) are available for downloading on the DECOMOBIL website http://decomobil.humanist-vce.eu/Downloads.html Document type: Repor

Système coopératif de perception et de communication pour la protection des usagers vulnérables

Cooperative intelligent transportation systems (C-ITS) have the opportunity to enhance road safety, especially the safety of vulnerable road users (VRU), e.g., pedestrians and cyclists. Road accidents are mainly due to vehicles' and VRUs' inability to detect the danger before a collision cannot be avoided.We introduce a perception system based on laser and camera sensors to estimate the state of VRUs located around the vehicle. A multi-class classification of road obstacles based on laser data has been developed using statistical machine learning and Bayesian estimation.We propose an architecture for vehicles-to-pedestrians (V2P) communication which considers the weak energy resources of the devices carried by pedestrians such as smartphones. Our solution is relying on the standards defined by ETSI ITS architecture for vehicular communication and proposes geographical dissemination for V2P communication.A cooperative perception/communication system can deal with scenarios which are becoming more and more complex by combining the ability of perception to estimate the dynamic state of detected obstacles and the ability of communication to exchange a rich content between distant users. We introduce a multi-hypotheses fusion between perception and communication information and a smartphone application dedicated to protect VRUs from road danger.The solutions proposed during this thesis are evaluated on real data. We carried out real experiments on INRIA campus demonstrating the assets of a cooperative system for the protection of vulnerable road users.Les systèmes de transports intelligents coopératifs (C-ITS) offrent des opportunités pour améliorer la sécurité routière et particulièrement la sécurité des usagers vulnérables (VRU), e.g., piétons et cyclistes. La principale source d'accidents provient de l'incapacité des usagers, véhicules et VRUs, à détecter le danger avant qu'une collision soit inévitable. Nous introduisons un système de perception qui s'appuie sur les données des capteurs laser et caméra pour estimer l'état des VRUs entourant le véhicule. Une technique de classification multi-classes des obstacles routiers à partir de données laser a été développée en utilisant une méthode d'apprentissage statistique et une estimation bayésienne. Nous proposons une architecture de communication véhicules-piétons (V2P) qui prend en compte les faibles ressources énergétiques des smartphones transportés par les piétons. Notre solution s'appuie sur les standards définis dans l'architecture de communication véhiculaire ETSI ITS et propose une dissémination géographique pour la communication V2P. Un système coopératif perception/communication a le potentiel de gérer des scénarios de plus en plus complexes en combinant la capacité de la perception à estimer l'état dynamique des obstacles détectés et la capacité de la communication à échanger un contenu riche entre des usagers éloignés. Nous introduisons une fusion multi-hypothèses entre les informations de perception et de communication et une application pour smartphone destinée à protéger les VRUs des dangers de la route. Les solutions proposées au cours de la thèse sont évaluées sur des données réelles. Nous avons mené des expérimentations sur le campus d'INRIA démontrant les atouts d'un système coopératif de protection des usagers vulnérables

Product Development within Artificial Intelligence, Ethics and Legal Risk

This open-access-book synthesizes a supportive developer checklist considering sustainable Team and agile Project Management in the challenge of Artificial Intelligence and limits of image recognition. The study bases on technical, ethical, and legal requirements with examples concerning autonomous vehicles. As the first of its kind, it analyzes all reported car accidents state wide (1.28 million) over a 10-year period. Integrating of highly sensitive international court rulings and growing consumer expectations make this book a helpful guide for product and team development from initial concept until market launch

Product Development within Artificial Intelligence, Ethics and Legal Risk

This open-access-book synthesizes a supportive developer checklist considering sustainable Team and agile Project Management in the challenge of Artificial Intelligence and limits of image recognition. The study bases on technical, ethical, and legal requirements with examples concerning autonomous vehicles. As the first of its kind, it analyzes all reported car accidents state wide (1.28 million) over a 10-year period. Integrating of highly sensitive international court rulings and growing consumer expectations make this book a helpful guide for product and team development from initial concept until market launch