Traffic jam driving with NMV avoidance


Autoria(s): Milanés Montero, Vicente; Alonso, Luciano; Villagra Serrano, Jorge; Godoy, Jorge; Pedro Lucio, María Teresa de; Oria, Juan P.
Data(s)

01/08/2012

Resumo

n recent years, the development of advanced driver assistance systems (ADAS) – mainly based on lidar and cameras – has considerably improved the safety of driving in urban environments. These systems provide warning signals for the driver in the case that any unexpected traffic circumstance is detected. The next step is to develop systems capable not only of warning the driver but also of taking over control of the car to avoid a potential collision. In the present communication, a system capable of autonomously avoiding collisions in traffic jam situations is presented. First, a perception system was developed for urban situations—in which not only vehicles have to be considered, but also pedestrians and other non-motor-vehicles (NMV). It comprises a differential global positioning system (DGPS) and wireless communication for vehicle detection, and an ultrasound sensor for NMV detection. Then, the vehicle's actuators – brake and throttle pedals – were modified to permit autonomous control. Finally, a fuzzy logic controller was implemented capable of analyzing the information provided by the perception system and of sending control commands to the vehicle's actuators so as to avoid accidents. The feasibility of the integrated system was tested by mounting it in a commercial vehicle, with the results being encouraging.

Formato

application/pdf

Identificador

http://oa.upm.es/21303/

Idioma(s)

eng

Relação

http://oa.upm.es/21303/1/INVE_MEM_2012_141647.pdf

http://www.sciencedirect.com/science/article/pii/S0888327012001355

info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ymssp.2012.04.008

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

Mechanical Systems And Signal Processing, ISSN 0888-3270, 2012-08, Vol. 31

Palavras-Chave #Robótica e Informática Industrial
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed