TY - GEN
T1 - Bayesian networks and traffic accident reconstruction
AU - Davis, Gary A.
AU - Pei, Jianping
PY - 2003
Y1 - 2003
N2 - The attempt to draw rational conclusions about a road accident can be viewed as a problem in uncertain reasoning about a particular event, to which developments in the modeling of uncertain reasoning for artificial intelligence can be applied. Physical principles can be used to develop a structural model for the accident, and this model can then be combined with an expert assessment of prior uncertainty concerning the model's variables. Posterior probabilities, given evidence collected at the accident scene, can then be computed using Bayes theorem. Truth conditions for counterfactual claims about the accident can then be defined using a "possible worlds" semantics, and used to rigorously implement a "but for" test of whether or not a speed limit violation could be considered a cause of the accident.
AB - The attempt to draw rational conclusions about a road accident can be viewed as a problem in uncertain reasoning about a particular event, to which developments in the modeling of uncertain reasoning for artificial intelligence can be applied. Physical principles can be used to develop a structural model for the accident, and this model can then be combined with an expert assessment of prior uncertainty concerning the model's variables. Posterior probabilities, given evidence collected at the accident scene, can then be computed using Bayes theorem. Truth conditions for counterfactual claims about the accident can then be defined using a "possible worlds" semantics, and used to rigorously implement a "but for" test of whether or not a speed limit violation could be considered a cause of the accident.
KW - Bayesian networks
KW - Monte Carlo simulation
KW - accident reconstruction
KW - counterfactuals
UR - http://www.scopus.com/inward/record.url?scp=54849408734&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=54849408734&partnerID=8YFLogxK
U2 - 10.1145/1047788.1047829
DO - 10.1145/1047788.1047829
M3 - Conference contribution
AN - SCOPUS:54849408734
SN - 1581137478
SN - 9781581137477
T3 - Proceedings of the International Conference on Artificial Intelligence and Law
SP - 171
EP - 176
BT - Proceedings of the 9th International Conference on Artificial Intelligence and Law
T2 - 9th International Conference on Artificial Intelligence and Law, ICAIL '03
Y2 - 24 June 2003 through 28 June 2003
ER -