A systematic review of nanotechnology for electric vehicles battery
Nanotechnology has increased electric vehicle (EV) battery production, efficiency and use.
Nanotechnology is explored in this electric car battery illustration. Nanoscale materials and …
Nanotechnology is explored in this electric car battery illustration. Nanoscale materials and …
Transformer based composite network for autonomous driving trajectory prediction on multi-lane highways
In order to navigate through complex traffic scenarios safely and efficiently, the autonomous
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …
[HTML][HTML] Contrasting structures of the Southern Benue trough and the contiguous crystalline basement as observed from high-resolution aeromagnetic data
The present study investigated crustal structures and geological bodies within selected
areas of the southern Benue trough and the adjacent crystalline basement. It utilized high …
areas of the southern Benue trough and the adjacent crystalline basement. It utilized high …
[HTML][HTML] Fault Detection, Classification and Localization Along the Power Grid Line Using Optimized Machine Learning Algorithms
Distributed energy generation increases the need for smart grid monitoring, protection, and
control. Localization, classification, and fault detection are essential for addressing any …
control. Localization, classification, and fault detection are essential for addressing any …
[HTML][HTML] Modeling of traffic at a road crossing and optimization of waiting time of the vehicles
Traffic management is a critical activity, the population is increasing day by day and so the
traffic on the road is also increasing. Traffic jams and long waiting queues of vehicles at the …
traffic on the road is also increasing. Traffic jams and long waiting queues of vehicles at the …
HybridSecNet: In-Vehicle Security on Controller Area Networks Through a Hybrid Two-Step LSTM-CNN Model
A Chougule, I Kulkarni, T Alladi… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The modern Intelligent Vehicle (IV) is a complex technological marvel that heavily relies on
the Controller Area Network (CAN) bus system to enable seamless communication among …
the Controller Area Network (CAN) bus system to enable seamless communication among …
[HTML][HTML] Analysis and Prediction of Risky Driving Behaviors Using Fuzzy Analytical Hierarchy Process and Machine Learning Techniques
Driver behavior plays a pivotal role in ensuring road safety as it is a significant factor in
preventing traffic crashes. Although extensive research has been conducted on this topic in …
preventing traffic crashes. Although extensive research has been conducted on this topic in …
[HTML][HTML] An Efficient Real-Time Vehicle Classification from a Complex Image Dataset Using eXtreme Gradient Boosting and the Multi-Objective Genetic Algorithm
P Mani, P Rakkiya Goundar Komarasamy… - Processes, 2024 - mdpi.com
Recent advancements in image processing and machine-learning technologies have
significantly improved vehicle monitoring and identification in road transportation systems …
significantly improved vehicle monitoring and identification in road transportation systems …
[HTML][HTML] Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique
OI Aboulola - PLoS one, 2024 - journals.plos.org
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on
highways. Comprehending the contributing factors to these occurrences is paramount in …
highways. Comprehending the contributing factors to these occurrences is paramount in …
[HTML][HTML] Application of an ensemble CatBoost model over complex dataset for vehicle classification
P RK, K M. AboRas, A Youssef - Plos one, 2024 - journals.plos.org
The classification of vehicles presents notable challenges within the domain of image
processing. Traditional models suffer from inefficiency, prolonged training times for datasets …
processing. Traditional models suffer from inefficiency, prolonged training times for datasets …