查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning have be en published. According to news originating from Bhopal, India, by NewsRx corres pondents, research stated, "The primary safety hazard at unsignalized intersecti ons, particularly in urban areas, is pedestrian-vehicle collisions. Due to its c omplexity and inattention, pedestrian crossing behaviour has a significant impac t on their safety." Our news journalists obtained a quote from the research from the Maulana Azad Na tional Institute of Technology, "This study introduces a novel framework to enha nce pedestrian safety at unsignalized intersections by developing a predictive m odel of pedestrian crossing behaviour using machine learning algorithms. While a ccounting for crossing behaviour as the dependent variable and other independent variables, the analysis prioritises accuracy and internal validity. Important f eature scores for the different algorithms were assessed. The model results reve aled that the arrival first of a pedestrian or vehicle, pedestrian delay, vehicl e speed, pedestrian speed, age, gender, traffic hour, and vehicle category are h ighly influencing variables for analysing pedestrian behaviour while crossing at unsignalized intersections. This study found that the prediction of pedestrian behaviour based on random forest, extreme gradient boosting and binary logit mod el achieved 81.72%, 77.19% and 74.95%, r espectively. Algorithms, including k-nearest neighbours, artificial neural netwo rks, and support vector machines, have varying classification performance at eve ry step."
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