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

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.

Simulator Study of Driver Responses to Pedestrian Treatments at Multilane Roundabouts.

Previous studies have shown that roundabouts - especially multilane roundabouts - pose accessibility challenges to pedestrians with vision impairments, in part due to a lack of yielding by drivers, especially on multilane roundabout exit legs. In this study, three different treatments are assessed in terms of their propensity for increasing driver yielding rate using a driving simulator. These are stop bar and crosswalk relocation away from the beginning of exit leg, and two types of beacons, namely a Pedestrian Hybrid Beacon (PHB) and a Rectangular Rapid Flashing Beacon (RRFB). The study shows that installation of any kind of beacon (PHB or RRFB) with or without crosswalk relocation increases driver yielding rates significantly. Relocating the crosswalk does not provide a significant increase in driver yielding rate for the base case, but appeared to further enhance the effectiveness of the PHB and RRFB treatments. The results of using an eye tracker on drivers to track their gaze pattern while exiting the roundabout shows that having a beacon installed with crosswalk relocation increases drivers' attention both on the beacon and the pedestrian along the road. However, a portion of participants failed to see and react to the pedestrian treatments, causing concern about the visibility of these treatments at the roundabout exit leg.

Development and Implementation of a Conflict-based Assessment of Pedestrian Safety (CAPS) to Evaluate Accessibility of Complex Intersections.

This paper develops and implements the Conflict-based Assessment of Pedestrian Safety (CAPS) methodology for evaluating pedestrian accessibility at complex intersections. In past years, a significant research has been done on pedestrian access to modern roundabouts and other complex intersection forms, including a significant focus on the accessibility for pedestrians who are blind. A majority of these studies have relied on actual street crossings by study participants under supervision of trained Orientation and Mobility (O&M) Specialist. These crossing studies were used to evaluate risk from a measurement of intervention events, where the O&M specialist had to physically stop the participant from crossing. While providing arguably the most accurate data for the crossing risk at a particular intersection, actual street crossings can be dangerous to the study participants, and are further very time consuming and expensive to conduct. The CAPS method presented in this paper emphasizes the use of conflict-based safety factors to quantify risk. The CAPS method relates pedestrian crossing decisions to advanced measurements of vehicle dynamics to estimate lane-by-lane conflicts. CAPS identifies the grade of conflict based on a score generated on a five-criterion rating scale. Each of these criteria or factors has different severity levels, and when combined, provides an overall risk rating of the crossing decision. The CAPS framework was applied to a study of blind pedestrian crossings at a multi-lane roundabout. The resulting risk scores were calibrated from actual O&M interventions observed during the study to give confidence in the CAPS performance. The calibrated CAPS framework correctly matched all (high risk) O&M intervention events, and further identifies other (lower risk) pedestrian-vehicle conflicts. The resulting method has the potential to allow for a faster and most importantly safer evaluation of complex intersections for pedestrian access. Since all factors are measured prior to the pedestrian stepping into the roadway, this approach is compatible with crossing indicator studies, where the participants merely indicate when they would cross, rather than actually stepping into the roadway. The CAPS framework therefore allows for a more objective and consistent safety assessment of pedestrian crossings in a research context without having pedestrians physically step into the roadway.

Event-Based Modeling of Driver Yielding Behavior at Unsignalized Crosswalks.

This research explores factors associated with driver yielding behavior at unsignalized pedestrian crossings and develops predictive models for yielding using logistic regression. It considers the effect of variables describing driver attributes, pedestrian characteristics and concurrent conditions at the crosswalk on the yield response. Special consideration is given to 'vehicle dynamics constraints' that form a threshold for the potential to yield. Similarities are identified to driver reaction in response to the 'amber' indication at a signalized intersection. The logit models were developed from data collected at two unsignalized mid-block crosswalks in North Carolina. The data include 'before' and 'after' observations of two pedestrian safety treatments, an in-street pedestrian crossing sign and pedestrian-actuated in-roadway warning lights.The analysis suggests that drivers are more likely to yield to assertive pedestrians who walk briskly in their approach to the crosswalk. In turn, the yield probability is reduced with higher speeds, deceleration rates and if vehicles are traveling in platoons. The treatment effects proved to be significant and increased the propensity of drivers to yield, but their effectiveness may be dependent on whether the pedestrian activates the treatment.The results of this research provide new insights on the complex interaction of pedestrians and vehicles at unsignalized intersections and have implications for future work towards predictive models for driver yielding behavior. The developed logit models can provide the basis for representing driver yielding behavior in a microsimulation modeling environment.

Empirical Behavioral Models to Support Alternative Tools for the Analysis of Mixed-Priority Pedestrian-Vehicle Interaction in a Highway Capacity Context.

This paper presents behavioral-based models for describing pedestrian gap acceptance at unsignalized crosswalks in a mixed-priority environment, where some drivers yield and some pedestrians cross in gaps. Logistic regression models are developed to predict the probability of pedestrian crossings as a function of vehicle dynamics, pedestrian assertiveness, and other factors. In combination with prior work on probabilistic yielding models, the results can be incorporated in a simulation environment, where they can more fully describe the interaction of these two modes. The approach is intended to supplement HCM analytical procedure for locations where significant interaction occurs between drivers and pedestrians, including modern roundabouts.

Working Concept of Accessibility: Performance Measures for Usability of Crosswalks by Pedestrians with Vision Impairments.

This research presents an analysis framework and associated performance measures for quantifying the accessibility of pedestrian crossings at modern roundabouts for pedestrians who are blind. The measures, developed under two ongoing national research projects, NCHRP Project 3-78A and a bioengineering research grant from the National Institutes of Health-National Eye Institute, attempt to isolate the components of the crossing task for a blind pedestrian into computable and replicable quantities that allow the comparison of accessibility across individuals or sites. The framework differentiates between crossing opportunities in the form of yields and crossable gaps and the utilization of these opportunities by the pedestrian. It further accounts for the amount of delay and risk involved in the crossing. The analysis framework and measures are demonstrated for two single-lane roundabouts in North Carolina evaluated under the aforementioned research projects. The application shows that the accessibility of a pedestrian crossing to a blind pedestrian is characterized by a combination of different measures and further depends on crossing geometry, traffic volume, driver behavior, and the travel skills and risk-taking behavior of the individual. With successful demonstration at roundabout crosswalks, the analysis framework is hypothesized to have broader application to unsignalized pedestrian crossings, including midblock locations.

Mixed-Priority Pedestrian Delay Models at Single-Lane Roundabouts.

This paper presents an approach for developing mixed-priority pedestrian delay models at single-lane roundabouts using behavioral crossing data. Mixed-priority refers to crosswalk operations where drivers sometimes yield to create crossing opportunities, but where pedestrians sometimes have to rely on their judgment of gaps in traffic to cross the street. The models use probabilistic behavioral parameters measured in controlled pedestrian crossings by blind pedestrians as part of NCHRP project 3-78a. While blind pedestrians clearly represent a special population of pedestrians, the developed delay model is structured to be applicable to any pedestrian population. Delay is predicted as a function of the probability of encountering a crossing opportunity in the form of a yield or crossable gap, and the probability of utilizing that opportunity, which are combined to produce an overall probability of crossing. The paper presents the theoretical approach to estimating the probability parameters and uses a multi-linear log-transformed regression approach to predict the average pedestrian delay. The final delay model explains 64% of the variability in the observed data and therefore represents a reasonable model for predicting pedestrian delay at single-lane roundabouts. The paper concludes with a discussion of how agencies can estimate the underlying probability parameters for existing or proposed roundabouts using empirical and theoretical approaches, and how pedestrian crossing treatments can be used in the context of the model to reduce average pedestrian delay. The research is important in light of the ongoing debate of the accessibility of modern roundabouts to pedestrians who are blind.