PSI - Issue 24

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ScienceDirect

Procedia Structural Integrity 24 (2019) 423–436 Structural Integrity Procedia 00 (2019) 000–000 Structural Integrity Procedia 00 (2019) 000–000

www.elsevier.com / locate / procedia www.elsevier.com / locate / procedia

© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the AIAS2019 organizers © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) er-review line: Peer-review und r responsibility of the AIAS2019 organizers. Keywords: braking; steering; To highlight the benefits o ff ered by an adaptive ADAS compared to traditional ADASs, a special testing software has been developed: the best adaptive intervention to be applied at each instant is chosen in real-time through the criteria proposed, retrieving the required information from a pre-calculated database which collects the results of each braking and steering manoeuvre for a large variety of critical scenarios. Analyzing three ICS conditions, it is shown that the adaptive logic, di ff ering from an autonomous emergency braking, aims at creating eccentrical impacts with minimum ∆ V : the IR values associated with the ADAS adaptive intervention are consequently an order of magnitude lower than those obtained through traditional ADAS interventions. © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review line: Peer-review under responsibility of the AIAS2019 organizers. Keywords: braking; steering; AIAS 2019 International Conference on Stress Analysis Combined activation of braking and steering for automated driving systems: adaptive intervention by injury risk-based criteria Dario Vangi a , Antonio Virga a , Michelangelo-Santo Gulino a, ∗ a Universita` degli Studi di Firenze - Department of Industrial Engineering, Via di Santa Marta 3, 50139 Firenze, Italy Abstract Increase in advanced driver assistance systems (ADAS) performances is a crucial step towards autonomous driving, allowing the design of increasingly reliable automated driving systems (ADS); ADAS devices play a key role in the enhancement of vehicle safety, which primarily results from the ability to avoid possible impacts. Nevertheless, inevitable collision states (ICS) can be triggered by obstacles as buildings and stationary vehicles interposing between the opponent and the working field of ADAS sensors, compromising their functions; therefore, the performance increase of ADAS devices on the market necessarily passes from the optimal handling of an ICS, which is not currently subject to evaluations. The work introduces ADAS intervention criteria which are based on the occupants’ injury risk (IR): in a specific road scenario, the ADAS must primarily avoid the collision with maximum margin and minimize IR in the case of an ICS. Specifically, the ADAS must monitor the environment and intervene on braking and steering adapting to the scenario evolution, following an ”adaptive” logic. The most critical aspect of the approach lies in reconstructing, for the specific intervention, the eventual impact: while being a time-consuming process, reconstruction of the impact phase is necessary to compute impact-related parameters (e.g., velocity change of the vehicle ∆ V ) which directly a ff ect IR. To highlight the benefits o ff ered by an adaptive ADAS compared to traditional ADASs, a special testing software has been developed: the best adaptive intervention to be applied at each instant is chosen in real-time through the criteria proposed, retrieving the required information from a pre-calculated database which collects the results of each braking and steering manoeuvre for a large variety of critical scenarios. Analyzing three ICS conditions, it is shown that the adaptive logic, di ff ering from an autonomous emergency braking, aims at creating eccentrical impacts with minimum ∆ V : the IR values associated with the ADAS adaptive intervention are consequently an order of magnitude lower than those obtained through traditional ADAS interventions. AIAS 2019 International Conference on Stress Analysis Combined activation of braking and steering for automated driving systems: adaptive intervention by injury risk-based criteria Dario Vangi a , Antonio Virga a , Michelangelo-Santo Gulino a, ∗ a Universita` degli Studi di Firenze - Department of Industrial Engineering, Via di Santa Marta 3, 50139 Firenze, Italy Abstract Increase in advanced driver assistance systems (ADAS) performances is a crucial step towards autonomous driving, allowing the design of increasingly reliable automated driving systems (ADS); ADAS devices play a key role in the enhancement of vehicle safety, which primarily results from the ability to avoid possible impacts. Nevertheless, inevitable collision states (ICS) can be triggered by obstacles as buildings and stationary vehicles interposing between the opponent and the working field of ADAS sensors, compromising their functions; therefore, the performance increase of ADAS devices on the market necessarily passes from the optimal handling of an ICS, which is not currently subject to evaluations. The work introduces ADAS intervention criteria which are based on the occupants’ injury risk (IR): in a specific road scenario, the ADAS must primarily avoid the collision with maximum margin and minimize IR in the case of an ICS. Specifically, the ADAS must monitor the environment and intervene on braking and steering adapting to the scenario evolution, following an ”adaptive” logic. The most critical aspect of the approach lies in reconstructing, for the specific intervention, the eventual impact: while being a time-consuming process, reconstruction of the impact phase is necessary to compute impact-related parameters (e.g., velocity change of the vehicle ∆ V ) which directly a ff ect IR.

∗ Corresponding author. Tel.: + 39 055 / 2758711. E-mail address: michelangelo.gulino@unifi.it ∗ Corresponding author. Tel.: + 39 055 / 2758711. E-mail address: michelangelo.gulino@unifi.it

2452-3216 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the AIAS2019 organizers 10.1016/j.prostr.2020.02.039 2210-7843 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review li e: Peer-review under responsibility of the AIAS2019 organizers. 2210-7843 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review line: Peer-review under responsibility of the AIAS2019 organizers.