Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Gheorghe-Daniel Voinea, Cristian Cezar Postelnicu, Mihai Duguleana, Gheorghe-Leonte Mogan and Radu Socianu
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Gheorghe-Daniel Voinea: Department of Automotive and Transport Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Cristian Cezar Postelnicu: Department of Automotive and Transport Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Mihai Duguleana: Department of Automotive and Transport Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Gheorghe-Leonte Mogan: Department of Automotive and Transport Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Radu Socianu: General Magic Technology, 500090 Brasov, Romania

IJERPH, 2020, vol. 17, issue 19, 1-20

Abstract: Technological advances are changing every aspect of our lives, from the way we work, to how we learn and communicate. Advanced driver assistance systems (ADAS) have seen an increased interest due to the potential of ensuring a safer environment for all road users. This study investigates the use of a smartphone-based ADAS in terms of driving performance and driver acceptance, with the aim of improving road safety. The mobile application uses both cameras of a smartphone to monitor the traffic scene and the driver’s head orientation, and offers an intuitive user interface that can display information in a standard mode or in augmented reality (AR). A real traffic experiment consisting of two driving conditions (a baseline scenario and an ADAS scenario), was conducted in Brasov, Romania. Objective and subjective data were recorded from twenty-four participants with a valid driver’s license. Results showed that the use of the ADAS influences the driving performance, as most of them adopted an increased time headway and lower mean speeds. The technology acceptance model (TAM) questionnaire was used to assess the users’ acceptance of the proposed driver assistance system. The results showed significant interrelations between acceptance factors, while the hierarchical regression analysis indicates that the variance of behavioral intention (BI) can be predicted by attitude toward behavior.

Keywords: smartphone-based ADAS; user acceptance study; driver behavior; road safety; driving performance (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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