most citedTraffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities

254 citations · 348 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023254 cited

Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities

Maryam Shaygan, Collin Meese, Wanxin Li +2

Traffic prediction plays a crucial role in alleviating traffic congestion which represents a critical problem globally, resulting in negative consequences such as lost hours of add…

cs.CR202335 cited

Aggregated Zero-knowledge Proof and Blockchain-Empowered Authentication for Autonomous Truck Platooning

Wanxin Li, Collin Meese, Hao Guo +1

Platooning technologies enable trucks to drive cooperatively and automatically, providing benefits including less fuel consumption, greater road capacity, and safety. This paper in…

cs.DC202336 cited

BFRT: Blockchained Federated Learning for Real-time Traffic Flow Prediction

Collin Meese, Hang Chen, Syed Ali Asif +3

Accurate real-time traffic flow prediction can be leveraged to relieve traffic congestion and associated negative impacts. The existing centralized deep learning methodologies have…

cs.CR202310 cited

P-CFT: A Privacy-preserving and Crash Fault Tolerant Consensus Algorithm for Permissioned Blockchains

Wanxin Li, Collin Meese, Mark Nejad +1

Consensus algorithms play a critical role in blockchains and directly impact their performance. During consensus processing, nodes need to validate and order the pending transactio…

cs.NI202313 cited

Location-aware Verification for Autonomous Truck Platooning Based on Blockchain and Zero-knowledge Proof

Wanxin Li, Collin Meese, Zijia Zhong +2

Platooning technologies enable trucks to drive cooperatively and automatically, which bring benefits including less fuel consumption, more road capacity and safety. In order to est…