dc.creator | Corcoba Magaña, Victor | es |
dc.creator | Muñoz Organero, Mario | es |
dc.creator | Álvarez García, Juan Antonio | es |
dc.creator | Fernández Rodríguez, Jorge Yago | es |
dc.date.accessioned | 2021-09-14T10:55:23Z | |
dc.date.available | 2021-09-14T10:55:23Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Corcoba Magaña, V., Muñoz Organero, M., Álvarez García, J.A. y Fernández Rodríguez, J.Y. (2017). Design of a Speed Assistant to Minimize the Driver Stress. ADCAIJ: Advances in Distributed Computing and Articial Intelligence Journal, 6 (3), 45-56. | |
dc.identifier.issn | 2255-2863 | es |
dc.identifier.uri | https://hdl.handle.net/11441/125737 | |
dc.description.abstract | Stress is one of the most important factors in traffic accidents. When the driver is in
this mental state, their skills and abilities are reduced. In this paper, we propose an
algorithm to estimate the optimal speed to minimize stress levels on upcoming road
segments when driving. The prediction model is based on deep learning. The stress
level estimation considers the previous driver’s driving behavior before reaching the
road section to be assessed, the road state (weather and traffic), and the previous
drives made by the driver. We use this algorithm to build a speed assistant. The solution
provides an optimum average speed for each road segment that minimizes the
stress. A validation experiment has been conducted in a real setting using two different
types of vehicles. The proposal is able to predict the stress levels given the average
speed by 84.20% on average. On the other hand, the speed assistant reduces the stress
levels (estimated from the driver’s heart rate signal) and the aggressiveness of driving
regardless of the vehicle type. The proposed solution is implemented on Android mobile
devices and uses a heart rate chest strap. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TIN2013-46801-C4-2-R /1-R | es |
dc.description.sponsorship | Ministerio de Educación, Cultura y Deporte PRX15/00036 | es |
dc.format | application/pdf | es |
dc.format.extent | 9 | es |
dc.language.iso | eng | es |
dc.publisher | Ediciones Universidad de Salamanca | es |
dc.relation.ispartof | ADCAIJ: Advances in Distributed Computing and Articial Intelligence Journal, 6 (3), 45-56. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Intelligent | es |
dc.subject | Transport System | es |
dc.subject | Driver Stress | es |
dc.subject | Driving Assistant | es |
dc.subject | Deep Learning | es |
dc.subject | Particle Swarm | es |
dc.subject | Optimization | es |
dc.subject | Android | es |
dc.subject | Mobile Computing | es |
dc.title | Design of a Speed Assistant to Minimize the Driver Stress | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIN2013-46801-C4-2-R /1-R | es |
dc.relation.projectID | PRX15/00036 | es |
dc.relation.publisherversion | https://gredos.usal.es/bitstream/handle/10366/135892/Design_of_a_Speed_Assistant_to_Minimize_.pdf?sequence=1 | es |
dc.identifier.doi | 10.14201/ADCAIJ2017634556 | es |
dc.contributor.group | Universidad de Sevilla. TIC134: Sistemas Informáticos | es |
dc.journaltitle | ADCAIJ: Advances in Distributed Computing and Articial Intelligence Journal | es |
dc.publication.volumen | 6 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 45 | es |
dc.publication.endPage | 56 | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | es |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte (MECD). España | es |