Methodology and Results for the Investigation of Interactions Between Pedestrians and Vehicles in Real and Controlled Traffic Conditions

Effects of simulated mild vision loss on gaze, driving and interaction behaviors in pedestrian crossing situations

“…In particular, the situations with the preprogrammed bot pedestrians resulted in TTC less than 1.5 s. These situations also resulted in higher DSTs, above 3 m/s 2 (Figure 11), which are experienced as uncomfortable by drivers (Schroeder, 2008). The simulated vision impairment intensified the criticality in the crossings but compared to Kotte and Pütz (2017) who reported an average PET of 3 s, the crossings in this study were safer (average PET 4.76 s with simulated vision impairment). We found only 1 out of 95 situations where the driver did not yield to a pedestrian at a zebra crossing (a situation with the human-controlled ped and a driver without the goggles).…”

“…The bot was controlled by a preprogrammed script which triggered it to start moving when the participant's vehicle was 46 meters from the predefined crossing point (see Appendix A). After being triggered, the bot ran across the street ahead of the driver without changing speed at 1.6 m/s, slightly faster than the average crossing speed of 1.5 m/s reported for marked and unmarked pedestrian crossings in a real world study (Kotte & Pütz, 2017). Thus the bot simulated a pedestrian totally unaware of the approaching car, similar to the groupone, high-risk-taker pedestrians identified in the questionnaire study by Papadimitriou et al (2017).…”

“…The DST was computed for each event based on a safety margin of 3 s (representing the PET (Kotte & Pütz, 2017)) where the DST was the deceleration that the driver needed to apply to ensure that safety time. There were highly significant main effects of both pedestrian (β = 0.450; SE = 0.041; t= 11.171; p < 0.001) and crossing (β = − 0.223; SE = 0.041; t = −5.427; p < 0.001) on the DST.…”