Modeling Discretionary Lane Changing Decisions for Connected Vehicles Based on Fuzzy Logic

Abstract

Lane changing is one of the most complex tasks during driving. Advances in vehicle technology seek to help drivers during the lane change maneuver. Researchers have conducted many attempts to address this issue. However, most of these attempts have not focused on actual driver behavior using advanced vehicle technologies. Among those advances is the vehicle-to-vehicle (V2V) communication which promises safer and more efficient driving operations. This research seeks to fill in this gap by conducting an experiment in a driving simulator environment simulating V2V communication during a lane change maneuver. The experiments allow a better understanding of driver behavior during lane changing maneuvers. First, a literature review was completed to assess studies that focused on understanding and modeling discretionary lane changes. Then a pilot study was conducted with a small sample on a driving simulator to obtain a fuzzy logic membership function. Then a large sample was tested for the study. Adjustments were made to the model and performance measures were analyzed. A t-test was conducted to evaluate any significant differences between the two conditions with and without V2V communication. The results showed that drivers were more willing to accept smaller gaps under connected environment conditions than without V2Vcommunication. Also, the implementation of V2V communication was found to help drivers make the lane changing decision faster. The overall initial speed was reduced under the connected environment.