Event-Based Modeling of Driver Yielding Behavior to Pedestrians at Two-Lane Roundabout Approaches

Abstract

Unlike other types of controlled intersections, drivers do not always comply with the “yield to pedestrian” sign at the roundabouts. This paper aims to identify the contributing factors affecting the likelihood of driver yielding to pedestrians at two-lane roundabouts. It further models the likelihood of driver yielding based on these factors using logistic regression. The models have been applied to 1150 controlled pedestrian crossings at entry and exit legs of two-lane approaches of six roundabouts across the country. The logistic regression models developed support prior research that the likelihood of driver yielding at the entry leg of roundabouts is higher than at the exit. Drivers tend to yield to pedestrians carrying a white cane more often than to sighted pedestrians. Drivers traveling in the far lane, relative to pedestrian location, have a lower probability of yielding to a pedestrian. As the speed increases the probability of driver yielding decreases. At the exit leg of the roundabout, drivers turning right from the adjacent lane have a lower propensity of yielding than drivers coming from other directions. The findings of this paper further suggest that although there has been much debate on pedestrian right-of-way laws and distinction between pedestrian waiting positions (in the street versus at the curb), this factor does not have a significant impact on driver yielding rate. The logistic regression models also quantify the effect of each of these factors on propensity of driver yielding. The models include variables which are specific to each study location and explain the impact size of each study location on probability of yielding. The models generated in this research will be useful to transportation professionals and researchers interested in understanding the factors that impact driver yielding at modern roundabouts. The results of the research can be used to isolate factors that may increase yielding (such as lower roundabout approach speeds), and can feasibly be incorporated into microsimulation algorithms to model driver yielding at roundabouts.

Agreeing to cross: How drivers and pedestrians communicate

“…Numerous psychological studies examined the behaviors of drivers and pedestrians before crossing events. Usually, the following aspects are considered: the likelihood of the driver yielding ( [9], [10], [11]), driver awareness of the pedestrian [12], [13] and pedestrian's decision making [14], [15]. Multiple factors affecting these behaviors have been identified: vehicle speed and time to collision (TTC) ( [16], [17]), size of the gap between the vehicles [18], geometry and other features of the road (signs and delineation) [14], weather conditions [15], crossing conditions (whether pedestrian is crossing from a standstill or walking), number of pedestrians crossing [18], gender and age of the drivers and pedestrians [14], eye contact between the pedestrian and the driver ( [11], [19]), etc.…”

People as Sensors: Imputing Maps from Human Actions

“…These influences can also be learned by estimating the cost function of the driver, which can determine what actions the driver might take given some feature representations [13]. Driver models specifically considering pedestrian interactions have also been developed [14]- [16].…”

Pedestrian–Vehicle Interaction at Unsignalized Crosswalks: A Systematic Review

“…In addition, it is worth noting that the investigation has had as one of the most relevant premises that yielding to a pedestrian is a critical component of the accessibility and safety of pedestrians. Therefore, a better understanding of the behavior of the driver at the moment of yielding to a pedestrian can be of great value for conducting a more optimal PVI analysis [14]. In fact, the PVI is separated into two main processes, the pedestrian walking behavior and the driver yielding behavior.…”

“…On the other hand, driver behavior has been analyzed focusing on the identification of the factors that have a greater influence in yielding to pedestrians. Indeed, the action of yielding to a pedestrian is influenced by various factors, such as dynamics of the vehicle, characteristics of the driver, traffic volume, attributes of pedestrians, and concurrent events in the pedestrian crossing [14,[17][18][19]. The analysis of the driver yielding behavior assumes more relevance to ensure road safety since the driver tends to assume the risk because he/she feels protected inside the vehicle in contrast to the pedestrian who will accept time gaps that not compromise her/his physical integrity at least in normal conditions (i.e., visibility, weather, cognitive functions, etc.…”

“…The authors state this intuitive approach to analyse the yield response variable based on a binary logistic regression, allowing an easy interpretation and, more importantly, the implementation of the results in a micro-simulation environment. Meanwhile, Salamati et al [14] aimed to analyse the factors that influenced the yielding of the driver to pedestrians in the approach to two-lane roundabouts. The driver's behavior observations were controlled by the authors, and the data collection methodology (a ground-level video camera was pointed at the crosswalk and approach to capture the pedestrian and oncoming vehicles) was designed to include different waiting positions for the pedestrian to follow the four conditions defined by the study: a blind pedestrian standing at the curb, a blind pedestrian standing with one foot in the crosswalk, a sighted pedestrian standing at the curb, sighted pedestrian standing with one foot in the crosswalk.…”