Driving situation recognition with uncertainty management and rule-based systems

by: JM Nigro, S Loriette-Rougegrez, M Rombaut

Engineering Applications of Artificial Intelligence (June 2002), pp. 217-228.

View FullText article

DOI, IngentaConnect

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

fheintz

Find related articles with these CiteULike tags

event_detection, situational_awareness, uncertainty_mgt

摘要

The recognition of a temporal sequence is a complex problem, especially in the framework of driving situations. However, this recognition is essential for the development of driving assistance systems. This paper presents a rule-based system that manages the real-time measurements got from sensors of an experimental vehicle, in order to determine the current possible maneuvers worked out by the driver. The particularity of the proposed system is that it manages the inaccuracy of the data and the uncertainty of the recognition, using fuzzy subsets and beliefs on hypotheses.

@article{citeulike:2818386, abstract = {The recognition of a temporal sequence is a complex problem, especially in the framework of driving situations. However, this recognition is essential for the development of driving assistance systems. This paper presents a rule-based system that manages the real-time measurements got from sensors of an experimental vehicle, in order to determine the current possible maneuvers worked out by the driver. The particularity of the proposed system is that it manages the inaccuracy of the data and the uncertainty of the recognition, using fuzzy subsets and beliefs on hypotheses.}, author = {Nigro, J. M. and Loriette-Rougegrez, S. and Rombaut, M. }, citeulike-article-id = {2818386}, doi = {10.1016/S0952-1976(02)00070-2}, issn = {0952-1976}, journal = {Engineering Applications of Artificial Intelligence}, keywords = {event\_detection, situational\_awareness, uncertainty\_mgt}, month = {June}, pages = {217--228}, posted-at = {2008-05-21 07:50:34}, priority = {2}, publisher = {Elsevier}, title = {Driving situation recognition with uncertainty management and rule-based systems}, url = {http://dx.doi.org/10.1016/S0952-1976(02)00070-2}, year = {2002} }

RIS record

TY - JOUR ID - citeulike:2818386 L3 - citeulike-article-id:2818386 TI - Driving situation recognition with uncertainty management and rule-based systems JF - Engineering Applications of Artificial Intelligence SP - 217 EP - 228 PB - Elsevier SN - 0952-1976 N2 - The recognition of a temporal sequence is a complex problem, especially in the framework of driving situations. However, this recognition is essential for the development of driving assistance systems. This paper presents a rule-based system that manages the real-time measurements got from sensors of an experimental vehicle, in order to determine the current possible maneuvers worked out by the driver. The particularity of the proposed system is that it manages the inaccuracy of the data and the uncertainty of the recognition, using fuzzy subsets and beliefs on hypotheses. KW - event_detection KW - situational_awareness KW - uncertainty_mgt AU - Nigro, JM AU - Loriette-Rougegrez, S AU - Rombaut, M PY - 2002/06// UR - http://dx.doi.org/10.1016/S0952-1976(02)00070-2 ER -

RIS BibTeX