Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles [PDF]
Driven by the ever-increasing requirements of autonomous vehicles, such as traffic monitoring and driving assistant, deep learning-based object detection (DL-OD) has been increasingly attractive in intelligent transportation systems.
Siyuan Liang +7 more
semanticscholar +1 more source
Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing [PDF]
The rising popularity of self-driving cars has led to the emergence of a new research field in recent years: Autonomous racing. Researchers are developing software and hardware for high-performance race vehicles which aim to operate autonomously on the ...
Johannes Betz +7 more
semanticscholar +1 more source
Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys [PDF]
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in
Long Chen +15 more
semanticscholar +1 more source
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles [PDF]
The future of autonomous vehicles lies in the convergence of human-centric design and advanced AI capabilities. Autonomous vehicles of the future will not only transport passengers but also interact and adapt to their desires, making the journey ...
Can Cui +4 more
semanticscholar +1 more source
Receive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles [PDF]
The fusion of human-centric design and artificial intelligence capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond traditional transportation.
Can Cui +4 more
semanticscholar +1 more source
nuScenes: A Multimodal Dataset for Autonomous Driving [PDF]
Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image based benchmark datasets have driven development in computer vision tasks such as object detection, tracking and segmentation of agents in the ...
Holger Caesar +9 more
semanticscholar +1 more source
Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review
With the significant advancement of sensor and communication technology and the reliable application of obstacle detection techniques and algorithms, automated driving is becoming a pivotal technology that can revolutionize the future of transportation ...
De Jong Yeong +3 more
semanticscholar +1 more source
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles [PDF]
Trajectory prediction is a critical component for autonomous vehicles (AVs) to perform safe planning and navigation. However, few studies have analyzed the adversarial robustness of trajectory prediction or investigated whether the worst-case prediction ...
Qingzhao Zhang +4 more
semanticscholar +1 more source
A Review on Autonomous Vehicles: Progress, Methods and Challenges
Vehicular technology has recently gained increasing popularity, and autonomous driving is a hot topic. To achieve safe and reliable intelligent transportation systems, accurate positioning technologies need to be built to factor in the different types of
Darshit J. Parekh +6 more
semanticscholar +1 more source
Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages
The use of neural networks and reinforcement learning has become increasingly popular in autonomous vehicle control. However, the opaqueness of the resulting control policies presents a significant barrier to deploying neural network-based control in ...
Sampo Kuutti +2 more
doaj +1 more source

