The variable message signs (VMS) have been widely used in guiding and managing the dynamic traffic with development of intelligent transportation technologies. It is known that cell transmission model (CTM) can well reproduce such traffic dynamics as shock waves and jams. This paper presents a new method to estimate the route travel times by using the CTM in conjunction with a logit-based route choice rule. The impacts of VMS on a two-route scenario with recurrent and non-recurrent traffic congestion are numerically investigated by analyzing the changes of route flow and travel time. Simulation results show that in networks with suitable long links, the VMS can positively influence travelers’ decision making so as to improve the system performance. For non-recurrent congestion, the value space of the route choice parameter that affects the flow distribution between two routes is narrower in the case of high traffic demand than that in the low demand case. The variable message signs (VMS) have been widely used in guiding and managing the dynamic traffic with development of intelligent transportation technologies. It is known that cell transmission model (CTM) can well reproduce such traffic dynamics as shock waves and jams. This paper presents a new method to estimate the route travel times by using the CTM in conjunction with a logit-based route choice rule. The impacts of VMS on a two-route scenario with recurrent and non-recurrent traffic congestion are numerically investigated by the changes the of of Simulation results show that in networks with suitable long links, the VMS can influence influencers’ decision making so as to improve the system performance. For non-recurrent congestion, the value space of the route choice parameter that affects the flow distribution between two routes is narrower in the case of high traffic demand than that in the low demand case.