This work explores the design of a central collaborative driving strategy between connected cars with the objective of improving road safety in case of highway on-ramp merging scenario. Based on a suitable method for predicting vehicle motion and behavior for a central collaborative strategy, a dynamic Bayesian network method that predicts the intention of drivers in highway on-ramp is proposed. The method was validated using real data of detailed vehicle trajectories on a segment of interstate 80 in Emeryville, California
Autonomous driving is expected to become more common in the future. Autonomous vehicles operate toda...
Unsuccessful overtaking maneuvers on two-lane rural roads are one of the major causes of road accide...
This article reviews the applications of Bayesian Networks to Intelligent Autonomous Vehicles (IAV) ...
In the context of autonomous driving and road situation awareness, this manuscript introduces a Baye...
Connected Automated Vehicles (CAVs) have the potential to improve traffic operations when they coope...
The highway on-ramp merging area is one of the major sections that form traffic bottlenecks. In a co...
One of the designs for future highways with mixed flow of connected automated vehicles (CAVs) and ma...
Merging is a challenging task for automated vehicles. This paper proposes a strategy for connected a...
In recent years, autonomous driving has become an increasingly practical technology. With state-of-t...
Transport researchers and practitioners have long been seeking capable solutions to deal with the tr...
High-speed highway on-ramp merging is one of the most difficult and critical tasks for any autonomou...
Abstract—In this study, we present novel work focused on assisting the driver during merge maneuvers...
Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehi...
© 2000-2011 IEEE. Transport researchers and practitioners have long been seeking capable solutions t...
Work zone areas are frequent congested sections considered as the freeway bottleneck. Connected and ...
Autonomous driving is expected to become more common in the future. Autonomous vehicles operate toda...
Unsuccessful overtaking maneuvers on two-lane rural roads are one of the major causes of road accide...
This article reviews the applications of Bayesian Networks to Intelligent Autonomous Vehicles (IAV) ...
In the context of autonomous driving and road situation awareness, this manuscript introduces a Baye...
Connected Automated Vehicles (CAVs) have the potential to improve traffic operations when they coope...
The highway on-ramp merging area is one of the major sections that form traffic bottlenecks. In a co...
One of the designs for future highways with mixed flow of connected automated vehicles (CAVs) and ma...
Merging is a challenging task for automated vehicles. This paper proposes a strategy for connected a...
In recent years, autonomous driving has become an increasingly practical technology. With state-of-t...
Transport researchers and practitioners have long been seeking capable solutions to deal with the tr...
High-speed highway on-ramp merging is one of the most difficult and critical tasks for any autonomou...
Abstract—In this study, we present novel work focused on assisting the driver during merge maneuvers...
Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehi...
© 2000-2011 IEEE. Transport researchers and practitioners have long been seeking capable solutions t...
Work zone areas are frequent congested sections considered as the freeway bottleneck. Connected and ...
Autonomous driving is expected to become more common in the future. Autonomous vehicles operate toda...
Unsuccessful overtaking maneuvers on two-lane rural roads are one of the major causes of road accide...
This article reviews the applications of Bayesian Networks to Intelligent Autonomous Vehicles (IAV) ...