Baseline vulnerable road user injury risk in multiple U.S. dense urban driving environments.

Objective: Understanding and modeling baseline driving safety risk in dense urban areas represents a crucial starting point for automated driving system (ADS) safety impact analysis. The purpose of this study was to leverage naturalistic vulnerable road user (VRU) collision data to quantify collision rates, crash severity, and injury risk distributions in the absence of objective injury outcome data.

Methods: From over 500 million vehicle miles traveled, a total of 335 collision events involving VRUs were video verified and reconstructed (126 pedestrians, 144 cyclists, and 65 motorcyclists).

A perceptual paradigm and psychophysical evidence for hierarchy in scene gist processing.

What is the order of processing in scene gist recognition? Following the seminal studies by Rosch (1978) and Tversky and Hemmenway (1983) it has been assumed that basic-level categorization is privileged over the superordinate level because the former maximizes both within-category similarity and between-category variance. However, recent research has begun to challenge this view (Oliva & Torralba, 2001; Joubert, Rousselet, Fize, & Fabre-Thorpe, 2007; Loschky & Larson, 2010). Here we study these directions more fundamentally by investigating the perceptual relations between scene categories in a way that allows us to identify the order of processing of scene categories across taxonomic levels.