Routing in VANETs: A Fuzzy Constraint Q-Learning Approach
Vehicular Ad hoc NETworks (VANETs) can be used for the purpose of driving assistance, environment monitoring and entertainment. However, due to the vehicle movement, limited wireless resources and lossy feature of wireless channel, providing a reliable multi-hop communication in VANETs is particularly challenging. In this paper, the authors propose a VANET routing protocol which learns the optimal route by employing a fuzzy constraint Q-Learning algorithm. The protocol uses a fuzzy logic to evaluate a wireless link is whether good or not by considering multiple metrics of signal strength, available bandwidth and relative vehicle movement.