Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving
Robotic perception requires the modeling of both 3D geometry and semantics. Existing
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
Vision-based autonomous vehicle systems based on deep learning: A systematic literature review
In the past decade, autonomous vehicle systems (AVS) have advanced at an exponential
rate, particularly due to improvements in artificial intelligence, which have had a significant …
rate, particularly due to improvements in artificial intelligence, which have had a significant …
Convolutional neural networks for 5G-enabled intelligent transportation system: A systematic review
Abstract Modern 5G-enabled Intelligent Transportation System (ITS) provides comfort and
safety to the end users by using various models and techniques most of which are based on …
safety to the end users by using various models and techniques most of which are based on …
Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges
S Khatri, H Vachhani, S Shah, J Bhatia… - Peer-to-Peer Networking …, 2021 - Springer
Low latency in communication among the vehicles and RSUs, smooth traffic flow, and road
safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc …
safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc …
Environment-attention network for vehicle trajectory prediction
Y Cai, Z Wang, H Wang, L Chen, Y Li… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In vehicle trajectory prediction, the difficulty in modeling the interaction relationship between
vehicles lies in constructing the interaction structure between the vehicles in the traffic …
vehicles lies in constructing the interaction structure between the vehicles in the traffic …
Collision avoidance/mitigation system: Motion planning of autonomous vehicle via predictive occupancy map
Despite development efforts toward autonomous vehicle technologies, the number of
collisions and driver interventions of autonomous vehicles tested in California seems to be …
collisions and driver interventions of autonomous vehicles tested in California seems to be …
SCALE-Net: Scalable vehicle trajectory prediction network under random number of interacting vehicles via edge-enhanced graph convolutional neural network
Predicting the future trajectory of surrounding vehicles in a randomly varying traffic level is
one of the most challenging problems in developing an autonomous vehicle. Since there is …
one of the most challenging problems in developing an autonomous vehicle. Since there is …
Integrating the traffic science with representation learning for city-wide network congestion prediction
Recent studies on traffic congestion prediction have paved a promising path towards the
reduction of potential economic and environmental loss. However, at the city-wide scale …
reduction of potential economic and environmental loss. However, at the city-wide scale …
Traffic-light sign recognition using Capsule network
X Liu, WQ Yan - Multimedia Tools and Applications, 2021 - Springer
Automated driving gradually emerges as a real reality, but it still has to face various
challenges, including sophisticated and volatile traffic conditions, human operating faults …
challenges, including sophisticated and volatile traffic conditions, human operating faults …
Use of social interaction and intention to improve motion prediction within automated vehicle framework: A review
Human errors contribute to 94%(±2.2%) of road crashes resulting in fatal/non-fatal
causalities, vehicle damages and a predicament in the pathway to safer road systems …
causalities, vehicle damages and a predicament in the pathway to safer road systems …