6 papers
Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling
Mohamad Mofeed Chaar, Galia Weidl
Autonomous driving (AD) systems have advanced rapidly over the past decade; however, robust perception under adverse weather conditions remains a major challenge, particularly in d…
Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation
Mohamad Mofeed Chaar, Jamal Raiyn, Galia Weidl
Depth imaging is a crucial area in Autonomous Driving Systems (ADS), as it plays a key role in detecting and measuring objects in the vehicle's surroundings. However, a significant…
Improve bounding box in Carla Simulator
Mohamad Mofeed Chaar, Jamal Raiyn, Galia Weidl
The CARLA simulator (Car Learning to Act) serves as a robust platform for testing algorithms and generating datasets in the field of Autonomous Driving (AD). It provides control ov…
Accident-Driven Congestion Prediction and Simulation: An Explainable Framework Using Advanced Clustering and Bayesian Networks
Kranthi Kumar Talluri, Galia Weidl, Vaishnavi Kasuluru
Traffic congestion due to uncertainties, such as accidents, is a significant issue in urban areas, as the ripple effect of accidents causes longer delays, increased emissions, and…
Green Wave as an Integral Part for the Optimization of Traffic Efficiency and Safety: A Survey
Kranthi Kumar Talluri, Christopher Stang, Galia Weidl
Green Wave provides practical and advanced solutions to improve traffic efficiency and safety through network coordination. Nevertheless, the complete potential of Green Wave syste…
Enhancing Safety Standards in Automated Systems Using Dynamic Bayesian Networks
Kranthi Kumar Talluri, Anders L. Madsen, Galia Weidl
Cut-in maneuvers in high-speed traffic pose critical challenges that can lead to abrupt braking and collisions, necessitating safe and efficient lane change strategies. We propose…