We proposes the traffic congestion reducer agents and performed simulation to determine how well they mitigate congestion on multiple-lane highways. Traffic congestion has been a major problem in many countries for years, but as yet there is no effective method/control to mitigate the congestion due to the complex behaviors of cars on multiple-lane roads. We previously proposed traffic congestion reducer (TCR) agents, which are intelligent autonomous agents, to pursue the minimum extra functions required to mitigate or avoid congestion on a highway. Then, we found that, when more than two agents are arranged in succession, they can mitigate the initial (so, light) congestion on a single-lane highway. However, we did not analyze their effectiveness on multi-lane highways, which is more difficult because the dynamics of lane changes. Thus, we built an agent-based simulation for a multiple-lane highway to examine the effects of TCR agents and behaviors of nearby car agents. We also modified the definition of the TCR agents for behavior on a multi-lane highway. The simulation results revealed that while TCR agents can mitigate light congestion, its mitigation mechanism is quite different from that on a single-lane highway.