Pre-Lane-change Signal in Transitional Autonomous Vehicles: Results from Controlled Experiments

Abstract

This paper investigates how a production transitional autonomous vehicle (tAV) develops and executes mandatory lane-change decisions. Using 150 controlled mandatory lane changes from the NC-tALC experiments, the study examines whether the eventual target gap is observable before lateral movement begins and how the tAV progresses longitudinally from that pre-lane-change state to lane-change start. Signal time (SigT) is defined as an operational pre-lane-change-start reference point. A Firth logistic regression predicts whether the tAV eventually merges in front of or behind its nearest target-lane vehicle using relative position and relative speed at SigT. Longitudinal progression from SigT to lane-change start is then examined separately for in-position and repositioning cases. The traffic state at SigT contains substantial information about eventual target-gap choice and provides meaningful lead time before lateral movement begins. The proposed formulation predicts whether the tAV remains with its current gap or repositions to a neighboring gap by moving forward or dropping back, including cases with longitudinal overlap and ambiguous current-gap geometry. The model achieves an average five-fold cross-validated accuracy of 0.89. Results also provide preliminary evidence that in-position and repositioning cases follow different longitudinal pathways from SigT to lane-change start. These findings support a two-stage conjecture of the observable lane-change process: longitudinal preparation from SigT to lane-change start, followed by lateral maneuver execution. The formulation applies to in-position, repositioning, and longitudinally overlapping cases, and can support lane-change models that distinguish target-gap choice from lateral-onset timing while representing longitudinal preparation before lateral movement begins.