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A Bayesian Approach for Analyzing Results of Vehicle Collision Tests
Author(s) -
Carnahan James V.,
Krishnan K. S.
Publication year - 1989
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1989.tb01417.x
Subject(s) - collision , computer science , bayesian probability , set (abstract data type) , motor vehicle crash , test (biology) , standard model (mathematical formulation) , limit (mathematics) , spillage , simulation , engineering , mathematics , poison control , computer security , artificial intelligence , gauge (firearms) , medicine , history , paleontology , mathematical analysis , environmental health , archaeology , injury prevention , biology , programming language , waste management
Certain motor vehicle safety standards stipulate a collision test speed and a set of performance criteria that vehicles must satisfy during or after the collision test. For example, Federal Motor Vehicle Safety Standard 301 requires a 30 mile per hour (mph) barrier collision and specifies a certain maximum allowable limit on the total spillage of fuel. Vehicle designs are required to meet this standard; however, when collision tests are conducted at speeds higher than the standard, vehicles do not always satisfy the performance criteria. This paper develops a mathematical model for estimating the probability of meeting the standard by using a Bayesian framework to incorporate engineering judgment with collision test results. The model is based on the idea that there are random features to a vehicle's ability to meet performance standards in a collision, especially at such elevated speeds. Example calculations are included to illustrate the estimation of the probability of meeting the standard and to compare it with a maximum likelihood approach.