Real-Time Freeway Traffic State Estimation Based on the Second-Order Divided Difference Kalman Filter

Reliable road traffic state identification systems should be designed to provide accurate traffic state information anywhere and anytime. In this paper we propose a road traffic classification system, based on traffic variables estimated using the second order Divided Difference Kalman Filter (DDKF2). This filter is compared with the Extended Kalman Filter (EKF) using both simulated and real-world dataset of highway traffic. Monte-Carlo simulations indicate that the DDKF2 outperforms the EKF filter in terms of parameters estimation error. The real-word evaluation of the DDKF2 filter in terms of classification rate confirms that this filter is promising for real-world traffic state identification systems

Efficient Road Traffic Video Congestion Classification Based on the Multi-Head Self-Attention Vision Transformer Model

Due to rapid population growth, traffic congestion has become one of the major issues in urban areas. The utilization of technology may help to address this issue. This paper proposes a new Multi-head Self-attention Vision Transformer (MSViT) based macroscopic approach, for road traffic congestion classification. To evaluate this approach, we use the UCSD (University of California San Diego) dataset that includes different weather conditions (clear, overcast and rainy) and different traffic scenarios (light, medium and heavy). The classification accuracy reached a high level of 99.76% with this dataset and 99.37% when night-mode frames are added to it. The proposed MSViT based method outperforms the state-of-the-art macroscopic and microscopic methods that have been evaluated using the same UCSD dataset, which makes it an efficient solution for traffic congestion prediction

Abstracts of the First International Conference on Advances in Electrical and Computer Engineering 2023

This book presents extended abstracts of the selected contributions to the First International Conference on Advances in Electrical and Computer Engineering (ICAECE'2023), held on 15-16 May 2023 by the Faculty of Science and Technology, Department of Electrical Engineering, University of Echahid Cheikh Larbi Tebessi, Tebessa-Algeria. ICAECE'2023 was delivered in-person and virtually and was open for researchers, engineers, academics, and industrial professionals from around the world interested in new trends and advances in current topics of Electrical and Computer Engineering. Conference Title: First International Conference on Advances in Electrical and Computer Engineering 2023Conference Acronym: ICAECE'2023Conference Date: 15-16 May 2023Conference Venue: University of Echahid Cheikh Larbi Tebessi, Tebessa-AlgeriaConference Organizer: Faculty of Science and Technology, Department of Electrical Engineering, University of Echahid Cheikh Larbi Tebessi, Tebessa-Algeri