# Scanning and Detection at Intersections

> **NIH NIH R01** · SCHEPENS EYE RESEARCH INSTITUTE · 2024 · $690,566

## Abstract

Project Summary
Hemianopia (the loss of half the field of vision on the same side in both eyes) is a severe visual consequence
of stroke and traumatic brain injury. Resuming driving after the onset of hemianopia is an important goal to
maintain independence and quality of life. People with hemianopia are permitted to drive in about 18 states.
However, in a retrospective analysis of crash records, drivers with hemianopia were found to have a higher risk
for crashes than drivers with a full field of vision. Intersections are especially challenging for drivers with
hemianopia as a wide field (up to 180°) has to be checked for potential hazards, requiring head as well as eye
movements. If drivers with hemianopia do not scan (look) toward the side of the hemianopia, or do not scan far
enough, then a hazard that appears within a field loss area might never be seen or might be seen too late to
make a safe driving response. Although there is strong evidence of inadequate scanning by people with
hemianopia in simulated driving, little is known about their scanning behaviors and the extent to which
inadequate scanning contributes to collision risk in real-world driving. The overall goals of this research are to
(1) Investigate inadequate scanning and factors contributing to near-collision incidents (a proxy for actual
collisions) in naturalistic driving; (2) Evaluate the efficacy of a novel approach to scanning training to address
intersection scanning deficits; and (3) Evaluate whether scanning training in the simulator transfers to real-
world driving. To address the first goal, in Aim 1, drivers with hemianopia and drivers with normal vision will
complete an extended period of driving with a video-recording system in their own vehicle. This will provide
important data to better understand factors contributing to inadequate scanning in naturalistic driving and the
role of inadequate scanning as compared to other at-risk behaviors in near-collision incidents. To address the
second and third goals, randomized controlled clinical trials will be conducted to evaluate the efficacy of the
scanning training for former drivers with hemianopia (Aim 2) and current drivers with hemianopia (Aim 3).
Scanning training will be given in a simulator. In Aim 2 the effects of the training on intersection scanning and
responses to hazards will be evaluated in the driving simulator. In Aim 3, the effects of the training will be
evaluated through recordings of scanning behaviors in naturalistic driving before and after training, which will
enable an evaluation of whether training in the simulator generalizes to improvements in scanning in real-world
driving. The program of research will also examine whether scanning in the virtual environment of a driving
simulator is representative of scanning in real-world driving as a first step toward validating the driving
simulator as a tool for both training and evaluation of scanning of at-risk drivers. The proposed research has
the p...

## Key facts

- **NIH application ID:** 10909089
- **Project number:** 5R01EY025677-09
- **Recipient organization:** SCHEPENS EYE RESEARCH INSTITUTE
- **Principal Investigator:** Alexandra Rae Bowers
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $690,566
- **Award type:** 5
- **Project period:** 2015-09-30 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909089

## Citation

> US National Institutes of Health, RePORTER application 10909089, Scanning and Detection at Intersections (5R01EY025677-09). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10909089. Licensed CC0.

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