An ANFIS design for prediction of future state of a vehicle in lane change behavior

The lane change maneuver is one of the most common driving behaviors in highways or rural roads. Each driver usually conducts at least one lane change maneuver during his trip. Therefore, it is chosen as the object behavior in this study and novel adaptive neuro-fuzzy inference models are proposed for this behavior. These models are able to simulate and predict the future behavior of a Driver-Vehicle-Unit in the lane change maneuver for various time delays. Using the field data, the outputs of the models are validated and compared with the real traffic data. The simulation results show that these models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way.