Multi-modal interaction-aware motion prediction at unsignalized intersections
Autonomous vehicle technologies have evolved quickly over the last few years, with safety
being one of the key requirements for their full deployment. However, ensuring their safety …
being one of the key requirements for their full deployment. However, ensuring their safety …
A safe hierarchical planning framework for complex driving scenarios based on reinforcement learning
Autonomous vehicles need to handle various traffic conditions and make safe and efficient
decisions and maneuvers. However, on the one hand, a single optimization/sampling-based …
decisions and maneuvers. However, on the one hand, a single optimization/sampling-based …
Scegene: Bio-inspired traffic scenario generation for autonomous driving testing
The core value of simulation-based autonomy tests is to create densely extreme traffic
scenarios to test the performance and robustness of the algorithms and systems. Test …
scenarios to test the performance and robustness of the algorithms and systems. Test …
A diffusion-model of joint interactive navigation
Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit
diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in …
diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in …
Analyzing the suitability of cost functions for explaining and imitating human driving behavior based on inverse reinforcement learning
Autonomous vehicles are sharing the road with human drivers. In order to facilitate
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
Analysis of driving behavior in unprotected left turns for autonomous vehicles using ensemble deep clustering
The advent of autonomous driving technology offers transformative potential in mitigating
traffic congestion and enhancing road safety. A particularly challenging aspect of traffic …
traffic congestion and enhancing road safety. A particularly challenging aspect of traffic …
A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles
Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …
maneuverings. Some essential tasks that require simultaneous management and actions …
Safety-assured speculative planning with adaptive prediction
Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
Be-sti: Spatial-temporal integrated network for class-agnostic motion prediction with bidirectional enhancement
Determining the motion behavior of inexhaustible categories of traffic participants is critical
for autonomous driving. In recent years, there has been a rising concern in performing class …
for autonomous driving. In recent years, there has been a rising concern in performing class …
Vehicle trajectory prediction on highways using bird eye view representations and deep learning
This work presents a novel method for predicting vehicle trajectories in highway scenarios
using efficient bird's eye view representations and convolutional neural networks. Vehicle …
using efficient bird's eye view representations and convolutional neural networks. Vehicle …