首页|Findings from Queensland University of Technology Update Knowledge of Artificial Intelligence (A Non-stationary Bivariate Extreme Value Model To Estimate Real-t ime Pedestrian Crash Risk By Severity At Signalized Intersections Using Artifici al …)
Findings from Queensland University of Technology Update Knowledge of Artificial Intelligence (A Non-stationary Bivariate Extreme Value Model To Estimate Real-t ime Pedestrian Crash Risk By Severity At Signalized Intersections Using Artifici al …)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ar tificial Intelligence. According to news reportingfrom Brisbane, Australia, by NewsRx journalists, research stated, “Vehicle-pedestrian crashes are generallys evere due to the vulnerability of pedestrians compared to the occupants of vehic les. However, theestimation of pedestrian crash risk by severity has not been g iven adequate attention in the field ofproactive safety assessments applying tr affic conflict techniques.”
BrisbaneAustraliaAustralia and New Z ealandArtificial IntelligenceEmerging TechnologiesMachine LearningQueens land University of Technology
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