Title: An intelligent road perception system for advanced driver assistance: combining object detection and distance estimation

Authors: Ouafae Abarkan; Walid Jebrane; Nabil El Akchioui

Addresses: Applied and Theoretical Sciences, Intelligent Systems and Renewable Energies, FSTH, Abdelmalek Essaadi University, Tetouan, Morocco ' Applied and Theoretical Sciences, Intelligent Systems and Renewable Energies, FSTH, Abdelmalek Essaadi University, Tetouan, Morocco ' Applied and Theoretical Sciences, Intelligent Systems and Renewable Energies, FSTH, Abdelmalek Essaadi University, Tetouan, Morocco

Abstract: Artificial intelligence (AI) techniques, such as deep learning and computer vision, have seen increasing adoption in the automotive industry, driving a rapid transformation of the sector in recent years. Intelligent, autonomous, and efficient decision-making in vehicles has become feasible thanks to these technologies. In this paper, we present an advanced application for the detection of road traffic-related objects, developed using the single shot multibox detector SSD300 algorithm. In addition to object recognition, our system integrates a distance estimation module that calculates the proximity between the vehicle and the identified objects. This dual functionality enhances road safety by supporting proactive collision avoidance and maintaining safe following distances in dynamic driving environments.

Keywords: artificial intelligence; road objects; SSD300; distance estimation.

DOI: 10.1504/IJVP.2026.155226

International Journal of Vehicle Performance, 2026 Vol.12 No.3, pp.279 - 298

Received: 04 Jul 2025
Accepted: 22 Oct 2025
Published online: 29 Jul 2026 *

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