Beyene, Nahom Minassie
(2014)
THE SYNTHESIS OF NAVISECTION:
MODERNIZING DRIVER REHABILITATION PROGRAMS TO ENCOMPASS INTELLIGENT VEHICLE TECHNOLOGIES.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The synthesis of NAViSection introduced a concept for using vehicle-based sensor data to improve the practice of driver evaluation. This project to reinforce licensing recommendations acknowledges that pen and paper documentation confines the expertise of evaluators to driving programs, while advances in vehicle sensors could address driving privilege as people age, experience medical impairments, and acquire disabilities. Through a review of medical record data, client files showed internal and external limitations to current practice. Within the program, a majority of evaluations resulted in a recommendation to continue driving despite the medical conditions referenced in the physician’s referral. This finding connected to concerns of client intake waiting lists before evaluation. Additionally, driver rehabilitation programs lack insight to council clients with poor medical prognosis on when to review driving capability. The NAViSection methodology proposed a way to integrate data collection with the standard processes of a driver rehabilitation program. While collecting event data based on evaluator intervention, the broader vision sought to correlate interventions with vehicle data patterns for typical driving errors.
Through multiple tests and simulations, a design project yielded a novel data collection system based on the NAViSection methodology. The pilot study results showed that assisted-driving events (steering, braking, and verbal cue assistance) correlate best with the recommendations of a Certified Driver Rehabilitation Specialist (CDRS). The NAViSection correlation presented improved predictive values compared to clinical assessment scores and driver history as screening tools. Future work could extend the reach of the CDRS by establishing correlations to telematics products (ex. OBD2 readers) and other sensing technologies as a screening system in future vehicles. In relation to driving simulators and naturalistic driving studies, the NAViSection system is better suited to help with at-risk drivers (teen and older Americans) within the setting of driving programs. Lastly, the assisted-driving events by a CDRS present a unique source of collision-avoidance, which may provide an opportunity to validate collision avoidance technologies from automotive manufacturers through real drivers, on real roads, and in real scenarios.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
| Creators | Email | Pitt Username | ORCID  |
|---|
| Beyene, Nahom Minassie | nmb32@pitt.edu | NMB32 | |
|
| ETD Committee: |
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| Date: |
13 January 2014 |
| Date Type: |
Publication |
| Defense Date: |
2 April 2013 |
| Approval Date: |
13 January 2014 |
| Submission Date: |
4 December 2013 |
| Access Restriction: |
5 year -- Restrict access to University of Pittsburgh for a period of 5 years. |
| Number of Pages: |
243 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Health and Rehabilitation Sciences > Rehabilitation Science and Technology |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
driver rehabilitation, behind-the-wheel evaluation, intelligent vehicles, collision avoidance, driver safety, medically-impaired, disability, rehabilitation, driver licensing |
| Date Deposited: |
13 Jan 2015 06:00 |
| Last Modified: |
13 Jan 2019 06:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/20194 |
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