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.

Risks to pedestrians in traffic systems with unfamiliar driving rules: a virtual reality approach

In this study, a virtual-reality (VR) pedestrian simulation method was used to evaluate the risks to pedestrians crossing streets in a traffic system with driving rules that were unfamiliar to them. Pedestrians from mainland China (which has a right-side driving (RD) system) and Hong Kong (which has a left-side driving (LD) system) were studied. Significant differences were observed between pedestrians from the different locations in terms of the direction in which the pedestrians habitually first looked before crossing. When exposed to an unfamiliar driving rule (i.e., traffic coming from an inconsistent direction in terms of participants' habitual driving system), the odds of participants from mainland China making an error in their looking behavior were 2.93 times those when exposed to a familiar driving rule. Road markings and traffic sound did not improve these participants' looking behavior. The results also show a negative correlation between inattentive looking behavior and time to collision (significant at the 1% level), as these errors lead to a shorter time to collision and increased the risk to pedestrians. The results of this study confirmed the risks for pedestrians traveling to places with unfamiliar driving rules and confirmed the existence of habitual looking behavior, and therefore provide evidence of the need for future studies to improve this problem. These may help decision makers take the risks of pedestrians from different driving rules into consideration in future traffic policymaking or traffic-facility improvements. The use of a VR simulation-based approach in this study provided a safe and controllable way to trial interventions and potential improvements without risking injury to participants, and thus may also be used for similar future studies.