Browsing by Keyword "Autonomous vehicles"
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Item Security architecture for swarms of autonomous vehicles in smart farming(2021-05-11) Martínez-Rodríguez, Belén; Bilbao-Arechabala, Sonia; Jorge-Hernandez, Fernando; BIGDATA; SWTNowadays, autonomous vehicles are incorporated into farms to facilitate manual labour. Being connected vehicles, as IoT systems, they are susceptible to cyber security attacks that try to cause damage to hardware, software or even living beings. Therefore, it is important to provide sufficient security mechanisms to protect both the communications and the data, mitigating any possible risk or harm to farmers, livestock or crops. Technology providers are aware of the importance of ensuring security, and more and more secure solutions can be found on the market today. However, generally, these particular solutions are not sufficient when they are part of complex hybrid systems, since there is no single global solution proposal. In addition, as the number of technologies and protocols used increases, the number of security threats also increases. This article presents a cyber-security architecture proposal for swarms of heterogeneous vehicles in smart farming, which covers all of the aspects recommended by the ISO 7798-2 specification in terms of security. As a result of this analysis, a detailed summary of the possible solutions and available technologies for each of the communication channels of the target system as well as some recommendations are presented.Item A Vehicle Simulation Model and Automated Driving Features Validation for Low-Speed High Automation Applications(2021-12-01) Matute-Peaspan, Jose Angel; Zubizarreta-Pico, Asier; Diaz-Briceno, Sergio E.; Tecnalia Research & Innovation; CCAMThe low-speed high automation (LSHA) is foreseen as a development path for new types of mobility, improving road safety and addressing transit problems in urban infrastructures. As these automation approaches are still in the development phase, methods to improve their design and validation are required. The use of vehicle simulation models allows reducing significantly the time deployment on real test tracks, which would not consider all the scenarios or complexity related to automated driving features. However, to ensure safety and accuracy while evaluating the proper operation of LSHA features, adequate validation methodologies are mandatory. In this study a two-step validation methodology is proposed: Firstly, an open-loop test set attempts to tune the required vehicle simulation models using experimental data considering also the dynamics of the actuation devices required for vehicle automation. Secondly, a closed-loop test strives to validate the selected automated driving functionality based on test plans, also improving the vehicle dynamics response. To illustrate the methodology, a study case is proposed using an automated Renault Twizy. In the first step, the brake pedal and steering wheel actuators' behavior is modeled, as well as its longitudinal dynamics and turning capacity. Then, in a second step, an LSHA functionality for Traffic Jam Assist based on a Model Predictive Control approach is evaluated and validated. Results demonstrate that the proposed methodology is capable not only to tune vehicle simulation models for automated driving development purposes but also to validate LSHA functionalities.