Impact of Access Management on Driver Behaviors

This project started with a broad question: What can new, rich naturalistic driver data such as in the Second Strategic Highway Research Program\u2019s Naturalistic Driving Study (SHRP2-NDS), tell us about how drivers react to roadway designs and access management techniques? To address this question, the project team reviewed and analyzed 6,209 trips that drivers in the NDS took through 40 circular intersections across five States. Coders flagged several types of driver behavior and captured a broad range of contextual variables. The analysis team used traditional statistics and machine learning methods to understand (1) when driver hesitation or uncertainty is most likely, and (2) general patterns and trends in driver hesitation or uncertainty. The team found that driver age is the most important predictor of hesitation or uncertainty with drivers\u2019 engagement in secondary tasks being a strong second. The findings presented here suggest further development and dissemination of educational or informational materials could mitigate drivers\u2019 hesitation or uncertainty in circular intersections and thereby improve traffic safety

Interactive PowerPoint Training to Improve Safety Driver Awareness while Operating a Transit Vehicle Equipped with Driving Automation Features

As new technologies, such as advanced driver assistance systems (ADAS) and automated driving systems (ADS) are introduced into transit operations, the tasks required of the operator will change. This research effort sought to understand if a low-cost training tool could be developed to maintain/improve safety as transit agencies pilot test these technologies. The program that was developed used an error training approach to improve hazard anticipation, hazard mitigation, and attention maintenance. This preliminary pilot study was conducted with federal employees and showed significant improvements across all three of the training areas

Locomotive Horn Detectability at Closely-Spaced Highway-Rail Grade Crossings

DTFR5317X00026Researchers assessed the feasibility of altering the locomotive horn sounding pattern of repetition at each crossing in a series of closely-spaced grade crossings by exploring the specific geometries and warning requirements for motorists in advance of such crossings. Acoustic modeling on five example scenarios showed that the locomotive horn would meet the auditory detection criteria out to a minimum of 1200 ft downstream of the primary crossing in those scenarios. The results from this analysis confirm that further exploration is needed on this topic, including assessing the feasibility and effectiveness for both detectability and driver response, to only sounding the locomotive horn prior to arriving at the first in a series of closely-spaced grade crossings

Human Factors Considerations for Integrating Traffic Information on Airport Moving Maps

The purpose of this research effort was to identify human factors considerations in the integration of traffic information and surface indications and alerts for runway status on airport moving maps for flight deck displays. The information is primarily intended to support the development of Federal Aviation Administration (FAA) policy and guidance for surface conflict detection and alerting (e.g., runway incursion alerting). The Volpe Center gathered information in two ways: (1) from observations made during FAA-sponsored demonstrations of Automated Dependent Surveillance – Broadcast (ADS-B) surface conflict detection algorithms, and (2) collecting pilot feedback on the use of ADS-B in the general aviation environment. Four human factors issues pertaining to the integration of traffic information and alerting are addressed in this paper: use of color, the presentation of indications and alerts, the design of traffic symbols, and position accuracy