Analysis of walking speeds and success rates on mid-block crossings using virtual reality simulation

A focus is set worldwide to study pedestrian behavior in road situations associated with a high frequency of crashes. This paper presents the results from a virtual reality simulation study that recorded pedestrians performing mid-block crossings on a straight segment of an urban street. The experiment was designed with eight scenarios with combinations of one or two lanes, two vehicle speeds, and constant or variable gaps between vehicles. The experiment was conducted with 48 subjects producing 538 crossing observations. The results show that subjects, on average, watched about 5 vehicle gaps in traffic before crossing the street and accepted a gap of 4.5 s between vehicles to cross. A regression model showed that the vehicle speed, the number of lanes, and subjects in the 66-85 years old group had a significant effect on the gap value accepted to cross. An interaction term based on gender and number of lanes also had a significant effect on the accepted gap. The study found average walking speeds between 4.1 and 4.8 ft/s (1.2-1.4 m/s) for different scenarios. A regression model revealed that the gender, the number of lanes, and the gap accepted to cross influenced the walking speed. Significant effects of interactions of the age with gender, number of lanes, and vehicle speed variables were also found that explain the differences in walking speed. The results for the success rate when crossing the street showed the overall worst performance in the scenario with traffic generated with a 25-mph (40 km/h) speed and a constant 3-s gap between vehicles. A Logit model showed that the probability of a pedestrian being hit by a vehicle increased with age, with traffic at the top vehicle speed, and with the constant 3-s vehicle gap. In contrast, the probability decreased with increases in the vehicle gap accepted to cross and the walking speed.