A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Utilizing B-Spline Curves and Neural Networks for Vehicle Trajectory Prediction in an Inverse Reinforcement Learning Framework
2022
Journal of Sensor and Actuator Networks
The ability to accurately predict vehicle trajectories is essential in infrastructure-based safety systems that aim to identify critical events such as near-crash situations and traffic violations. In a connected environment, important information about these critical events can be communicated to road users or the infrastructure to avoid or mitigate potential crashes. Intersections require special attention in this context because they are hotspots for crashes and involve numerous and complex
doi:10.3390/jsan11010014
fatcat:y73jkt7fizfwncjejv6kw5oqm4