Virtual Reality Driving Simulator: Investigating the Effectiveness of Image–Arrow Aids in Improving the Performance of Trainees

Virtual reality driving simulators have been increasingly used for training purposes, but they are still lacking effective driver assistance features, and poor use of user interface (UI) and guidance systems leads to users’ performance being affected. In this paper, we investigate image–arrow aids in a virtual reality driving simulator (VRDS) that enables trainees (new drivers) to interpret instructions according to the correct course of action while performing their driving task. Image–arrow aids consist of arrows, texts, and images that are separately rendered during driving in the VRDS. A total of 45 participants were divided into three groups: G1 (image–arrow aids), G2 (audio and textual aids), and G3 (arrows and textual aids). The results showed that G1 (image–arrow guidance) achieved the best performance, with a mean error rate of 8.1 (SD = 1.23) and a mean completion time of 3.26 min (SD = 0.56). In comparison, G2 (audio and textual aids) had a mean error rate of 10.8 (SD = 1.31) and completion time of 4.49 min (SD = 0.67), while G3 (arrows and textual aids) had the highest error rate (18.4, SD = 1.43) and longest completion time (6.51 min, SD = 0.68). An evaluation revealed that the performance of G1 is significantly better than that of G2 and G3 in terms of performance measures (errors + time) and subjective analysis such as usability, easiness, understanding, and assistance.

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Publication Details

Journal
Future Transportation
Published
2025-10-01
DOI
https://doi.org/10.3390/futuretransp5040130
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44
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article

Virtual Reality Driving Simulator: Investigating the Effectiveness of Image–Arrow Aids in Improving the Performance of Trainees

Dawar Khan, M. A. Ansari, Sehat Ullah, Numan Ali et al.
1 citations
Future Transportation
Human-Automation Interaction and Safety
2.44
article

Virtual Reality Driving Simulator: Investigating the Effectiveness of Image–Arrow Aids in Improving the Performance of Trainees

Dawar Khan, M. A. Ansari, Sehat Ullah, Numan Ali, Hameedur Rahman
article en
1 citations

Abstract

Virtual reality driving simulators have been increasingly used for training purposes, but they are still lacking effective driver assistance features, and poor use of user interface (UI) and guidance systems leads to users’ performance being affected. In this paper, we investigate image–arrow aids in a virtual reality driving simulator (VRDS) that enables trainees (new drivers) to interpret instructions according to the correct course of action while performing their driving task. Image–arrow aids consist of arrows, texts, and images that are separately rendered during driving in the VRDS. A total of 45 participants were divided into three groups: G1 (image–arrow aids), G2 (audio and textual aids), and G3 (arrows and textual aids). The results showed that G1 (image–arrow guidance) achieved the best performance, with a mean error rate of 8.1 (SD = 1.23) and a mean completion time of 3.26 min (SD = 0.56). In comparison, G2 (audio and textual aids) had a mean error rate of 10.8 (SD = 1.31) and completion time of 4.49 min (SD = 0.67), while G3 (arrows and textual aids) had the highest error rate (18.4, SD = 1.43) and longest completion time (6.51 min, SD = 0.68). An evaluation revealed that the performance of G1 is significantly better than that of G2 and G3 in terms of performance measures (errors + time) and subjective analysis such as usability, easiness, understanding, and assistance.

Future TransportationVol. 5(4)
University of Malakand (PK), King Abdullah University of Science and Technology (SA), Air University (PK)
Openalex Percentile: Top 10%
Human-Automation Interaction and Safety
2.44
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Virtual Reality Driving Simulator: Investigating the Effectiveness of Image–Arrow Aids in Improving the Performance of Trainees — Dawar Khan, M. A. Ansari, et al. · Future Transportation (2025) | TGRS Research Map | TGRS