Traffic System Disorder Evaluation Method for Highways Considering Lane Distribution Characteristics

Abstract Traditional traffic state evaluation systems for multilane highways predominantly focus on one-dimensional longitudinal kinematics, thereby systematically neglecting the impact of lateral spatial distribution and lane utilization imbalance. To address this limitation, this study proposes a multidimensional traffic system disorder evaluation method that integrates macroscopic flow regimes, microscopic driving behaviors, and lane distribution characteristics through a hybrid criteria importance through intercriteria correlation (CRITIC)–Entropy–technique for order of preference by similarity to ideal solution (TOPSIS) model. Utilizing empirical high-precision radar-video trajectory data, convergent validity analysis quantitatively demonstrates that the proposed index maintains a moderate but highly significant correlation ranging from 0.57 to 0.65 at p < 0.001 across temporal, longitudinal, lateral, and kinetic dimensions with four mainstream surrogate safety measures including time exposed time-to-collision, proportion of stopping distance, lateral conflict frequency, and crash potential index. Furthermore, unsupervised clustering identified a four-stage evolutionary pattern characterizing the flow transition from stable states to turbulent regimes. Our findings reveal that while high-density synchronized flow maintains temporary stability through driver adaptation, frequent lane-changing maneuvers trigger systemic oscillations. Severe disorder eventually degrades into a physical deadlock where extreme saturation structurally restricts lateral maneuverability, inducing asynchronous interlane stop-and-go oscillations and a complete loss of system self-organization. The developed evaluation approach provides a theoretical foundation for proactive risk monitoring and dynamic management strategies in highway traffic operations.