activity
20192022
most citedData-Driven Multi-step Demand Prediction for Ride-hailing Services Using Convolutional Neural Network

27 citations · 57 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2022

Spatiotemporal Transformer Attention Network for 3D Voxel Level Joint Segmentation and Motion Prediction in Point Cloud

Zhensong Wei, Xuewei Qi, Zhengwei Bai +6

Environment perception including detection, classification, tracking, and motion prediction are key enablers for automated driving systems and intelligent transportation applicatio…

cs.CV20222 cited

Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR

Zhengwei Bai, Saswat Priyadarshi Nayak, Xuanpeng Zhao +6

Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as a revolutionary promoter for the next-generation transportation systems. How…

cs.CV20202 cited

End-to-End Vision-Based Adaptive Cruise Control (ACC) Using Deep Reinforcement Learning

Zhensong Wei, Yu Jiang, Xishun Liao +5

This paper presented a deep reinforcement learning method named Double Deep Q-networks to design an end-to-end vision-based adaptive cruise control (ACC) system. A simulation envir…

cs.CV20191 cited

Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network

Zhensong Wei, Chao Wang, Peng Hao +1

Accurate lane localization and lane change detection are crucial in advanced driver assistance systems and autonomous driving systems for safer and more efficient trajectory planni…

cs.CV2019

Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

Mohammad Billah, Farzana Rahman, Arash Maskooki +3

Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, sto…