A DRL-Based Lane-Changing Decision Model for Connected and Automated Trucks to Reduce Congestion in Freeway Merging Areas
Trucks, which primarily travel in the rightmost lane on freeways, are in direct conflict with on-ramp vehicles and constitute a key factor contributing to congestion in merging areas. To address this challenge, this study proposes an adaptive information-fusion and stability-driven deep reinforcement learning (ASR) mod...