Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

ORCID

https://orcid.org/0000-0003-2157-3572

Access Type

Open Access Thesis

Document Type

thesis

Degree Program

Industrial Engineering & Operations Research

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2019

Month Degree Awarded

September

Abstract

Driving safety among young novice driver is one of the largest concern in the transportation domain. Many Paper-based or PC- based training program have been developed over the years to train the young novice driver to improve their driving skills (Hazard Anticipation). This training programs does help young novice driver to improve their situational awareness and so the hazard anticipation skills. But, there is one common problem with most of the currently available training programs. They are not very immersive, because such training program mostly provide plain view of the training scenario’s along with some description about the scenario and the subject trained in such training method needs to translate the provided knowledge in the plain view into the real-world driving.

An Advanced training program on risk awareness and perception was developed and evaluated in Oculus rift platform. The primary objective is to train the young novice driver in the Virtual reality headset based risk awareness and perception training program and evaluate the trained driver in the driving simulator against the placebo trained young novice driver. The Virtual reality headset based risk awareness and perception training program (V-RAPT) is based on 3M Error-based Training approach where the driver will have 80 horizontal degrees’ and 90 vertical degrees’ field of view.

Thirty-six drivers will receive training in the respective training methods- V-RAPT (Virtual reality headset based risk awareness and perception training), RAPT (PC- based risk awareness and perception training) and placebo training. Twelve young novice driver trained in the V-RAPT group will served as experimental group. Twenty-four other young novice will receive training in the RAPT and Placebo training respective will serve as control group. After training all three-group trained driver will be evaluated in the advanced driving simulator and the eye movement of the all thirty-six participants are recorded and measured. Vehicle measures such as acceleration, velocity and brake position is also recorded. The drivers’ score will based on whether or not their eye-fixations indicated recognition of potential risks in different high risk driving situations. The evaluation driver included six scenarios used in the V-RAPT training (near transfer scenarios) and four scenarios that were not used in the V-RAPT training (far transfer scenarios).

Drivers who received the V-RAPT training are expected to drive more safely than the drivers who received either training. The V-RAPT trained drivers are expected to glance on regions (Hazard anticipation) where potential risks might appear than the drivers’ trained in the RAPT and Placebo training method. Further, The V-RAPT trained drivers are expected have slower average velocity and better brake position (Hazard mitigation) are compared to the driver trained in the other two training method.

DOI

https://doi.org/10.7275/13641210

First Advisor

Siby Samuel

Second Advisor

Donald L. Fisher

Third Advisor

Michael Knodler Jr.

Share

COinS