Debiased machine learning for estimating the causal effect of urban traffic on pedestrian crossing behaviour
利用去偏机器学习估计城市交通对行人过街行为的因果效应
Before the transition of AVs to urban roads and subsequently unprecedented changes in traffic conditions, evaluation of transportation policies and futuristic road design related to pedestrian crossing behavior is of vital importance. Recent studies analyzed the non-causal impact of various variables on pedestrian waiting time in the presence of AVs. However, we mainly investigate the causal effect of traffic density on pedestrian waiting time. We develop a Double/Debiased…