206 research outputs found

    MethOds and tools for comprehensive impact Assessment of the CCAM solutions for passengers and goods. D1.1: CCAM solutions review and gaps

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    Review of the state-of-the-art on Cooperative, Connected and Automated mobility use cases, scenarios, business models, Key Performance Indicators, impact evaluation methods, technologies, and user needs (for organisations & citizens)

    An analysis of possible socio-economic effects of a Cooperative, Connected and Automated Mobility (CCAM) in Europe

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    A Cooperative, Connected and Automated Mobility (CCAM) is likely to have significant impacts on our economy and society. It is expected that CCAM unveils new and unprecedented mobility opportunities that hold the potential to unlock a range of safety, environmental and efficiency benefits. At the same time, it is anticipated that it will bring deep changes in the labour market, progressively making some occupations and skills less relevant, while at the same time opening up new opportunities for different businesses and requiring new and more advanced skills. With Europe accounting for 23% of global motor vehicle production (Acea Statistics, 2016) and almost 72% of inland freight transported by road in Europe (European Commission, 2017a), the full deployment of Connected and Automated Vehicle (CAV) technologies is expected to have a substantial impact on the European economy. The economic impacts of CAVs will go far beyond the automotive industry, into sectors like insurance, maintenance and repair or health, among others. While it is clear that CAVs could offer unique opportunities for value creation, it is also essential to acknowledge that they might imply a substantial transformation of our industries and our social and living systems. The study is aimed at analysing the value at stake for both industry and society as a result of a transition towards a CCAM mobility in Europe. It aims at identifying the economic sectors that are most likely to be affected by CCAM as well as the influencing factors driving future changes in each sector. The ultimate goal is to estimate ranges of potential effects for the main affected sectors, with the support of a set of scenarios. The study also aims at analysing the potential effects of CCAM on the workforce and pursues the identification of skills that need to be addressed in the mobility transition. The focus of the study is exclusively paid on road transport and covers both passenger and freight transport.JRC.C.4-Sustainable Transpor

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

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    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

    A transparent distributed ledger-based certificate revocation scheme for VANETs

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    The widespread adoption of Cooperative, Connected, and Automated Mobility (CCAM) applications requires the implementation of stringent security mechanisms to minimize the surface of cyber attacks. Authentication is an effective process for validating user identity in vehicular networks. However, authentication alone is not enough to prevent dangerous attack situations. Existing security mechanisms are not able to promptly revoke the credentials of misbehaving vehicles, thus tolerate malicious actors to remain trusted in the system for a long time. The resulting vulnerability window allows the implementation of complex attacks, thus posing a substantial impairment to the security of the vehicular ecosystem. In this paper we propose a Distributed Ledger-based Vehicular Revocation Scheme that improves the state of the art by providing a vulnerability window lower than 1 s, reducing well-behaved vehicles exposure to sophisticated and potentially dangerous attacks. The proposed scheme harnesses the advantages of the underlying Distributed Ledger Technology (DLT) to implement a privacy-aware revocation process while being fully transparent to all participating entities. Furthermore, it meets the critical message processing times defined by EU and US standards, thus closing a critical gap in the current international standards. Theoretical analysis and experimental validation demonstrate the effectiveness and efficiency of the proposed scheme, where DLT streamlines the revocation operation overhead and delivers an economically viable yet scalable solution against cyber attacks on vehicular systems

    Beam management for vehicle-to-vehicle (V2V) communications in millimeter wave 5G

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    Cooperative, Connected and Automated Mobility (CCAM) is expected to leverage the full potential of wireless communications. With the growing adoption of 5G and its support for Vehicle-to-Everything (V2X) communications, beamformed vehicular communications at millimeter-wave (mmWave) bands are expected to enable the most demanding connected driving applications. Beamformed V2X links present the challenge of beam management in such a fast-changing scenario. This paper goes through the practical limitations of the 5G V2X stack to support successful beamforming procedures. Two beam management strategies are proposed. Both strategies are evaluated in terms of power performance, beam recovery time and channel usage. The results suggest that significant differences apply when the beam is more frequently updated, whereas little improvement is seen by increasing the size of the beamset. Also, the selection of a proper strategy is shown to be important to alleviate the channel from overheads, and substantial differences in required signaling can be seen depending on the beam-tracking approach.This work was partly funded by the Spanish ComisiĂłn Interministerial de Ciencia y TecnologĂ­a under projects TEC2013-47360- C3-1-P, TEC2016-78028-C3-1-P and MDM2016-0600, and Catalan Research Group 2017 SGR 219. The Spanish Ministry of Education (FPU17/05561) and Generalitat de Catalunya DI programme (2018- DI-084) also contribute with predoctoral grants for the authors.Peer ReviewedPostprint (published version

    Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles

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    The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles. CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions

    Minimum Race-Time Planning-Strategy for an Autonomous Electric Racecar

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    Increasing attention to autonomous passenger vehicles has also attracted interest in an autonomous racing series. Because of this, platforms such as Roborace and the Indy Autonomous Challenge are currently evolving. Electric racecars face the challenge of a limited amount of stored energy within their batteries. Furthermore, the thermodynamical influence of an all-electric powertrain on the race performance is crucial. Severe damage can occur to the powertrain components when thermally overstressed. In this work we present a race-time minimal control strategy deduced from an Optimal Control Problem (OCP) that is transcribed into a Nonlinear Problem (NLP). Its optimization variables stem from the driving dynamics as well as from a thermodynamical description of the electric powertrain. We deduce the necessary first-order Ordinary Differential Equations (ODE)s and form simplified loss models for the implementation within the numerical optimization. The significant influence of the powertrain behavior on the race strategy is shown.Comment: Accepted at The 23rd IEEE International Conference on Intelligent Transportation Systems, September 20 - 23, 202

    Roundabouts: Traffic Simulations of Connected and Automated Vehicles—A State of the Art

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    The paper deals with traffic simulation within roundabouts when both “connected and automated vehicles” (CAVs) and human-driven cars are present. The aim is to present the past, current and future research on CAVs running into roundabouts within the Cooperative, Connected and Automated Mobility (CCAM) framework. Both microscopic traffic simulations and virtual reality simulations by dynamic driving simulators will be considered. The paper is divided into five parts. At first, the literature is analysed using the Systematic Literature Review (SLR) methodology based on Scopus database. Secondly, the influence of CAVs on roundabout-specific design features and configuration is analysed. Gap-acceptance models used to define the capacity of the roundabout, one of its most important key performance indicators, are also presented. Third, the most common simulation software are described and analysed in terms of traffic demand implementation. Then the communication approaches and path management algorithms are studied. An example is proposed on the integration of microscopic traffic simulations and dynamic driving simulators virtual reality simulations. Finally, car following models suitable for roundabout traffic are discussed. There is still a gap between simulations and actual experience. There are reasonable doubts on how modelling and optimizing CAVs’ behaviour into roundabouts in view of CCAM. It seems that Cooperative, Connected and Automated Vehicles (CCAVs), more than simply Connected and Automated Vehicles (CAVs), could optimise traffic flow, safety and driving comfort within the roundabout. A very promising technology for traffic simulation within the roundabout seems the one based on dynamic driving simulators
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