With the development of autonomous vehicles, a mixed traffic flow scenario of Connected Autonomous Vehicles (CAV) and Human-Driven Vehicles (HVs) would be popular in the near future. The traditional traffic light control systems (TLCSs) for HVs do not make full use of traffic information collected via VANET; meanwhile emerging traffic light systems for CAV assume complicated and quick reactions, which human drivers may not be able to handle. Therefore, they are not suitable for the mixed scenario. This paper proposed a novel TLCS, named PALM, for tackling the challenge for handling mixed traffic scenarios. PALM considers the traffic flow at each intersection and adjacent ones and adjusts the traffic lights schedule for the next few phases accordingly. It also optimizes the signal timing and phases to better serve the platoons formed by CAV. The simulation results show that our approach achieves up to 75.34% and 33.02% drop in the average waiting time compared to the static and actuated TLCS, respectively.