… To the best of our knowledge, no other studies analyze multi-class object detection in
autonomous vehicles with camera data by evaluating different factors such as accuracy, speed, …

… the technical aspect of automated driving. Studies regarding present challenges, high-level …
on our own platform in a real-world driving setting. The paper concludes with an overview of …

… , critical for improving self-driving perception algorithms. In this paper, we introduce PandaSet,
the first dataset produced by a complete, high-precision autonomous vehicle sensor kit …

… the user’s privacy. In this paper, we present a new approach to learn autonomous driving …
We design a new Federated Autonomous Driving network (FADNet) that can improve the …

… Our total unique roadway distance is calculated by hashing our autonomous vehicle
poses as UTM coordinates into 25 meter voxels and counting the number of non-zero voxels. …

… Specifically, we consider physical-world attack vectors for high attack practicality, and
target an attack goal with the most direct safety consequence for autonomous driving: cause a …

… Currently, some automated driving … automated driving (L2) or conditional automated driving
(L3) technologies to improve the future sales and profits. Along with the increment of vehicle …

… Due to the time-varying nature of our autonomous vehicular network settings, ie the number
of vehicles, miners and wireless channel conditions vary dynamically in our network scenario…

… the member vehicles of the groups may be part of the car pooling service or are barring
specific requests due to previous experience or user ratings. Personal user preferences are also …

… Using NEAT intermediate representations, we train several autonomous driving models
for the CARLA driving simulator [20]. We consider a more challenging evaluation setting than …