A review on following behavioral models: Regular to connected autonomous vehicle heterogeneity

Abstract

Following behavior, an integral part of driving, is vital in describing the longitudinal interaction among vehicles. The traffic composition of the stream influences the following behavior. Several studies have concentrated on developing the following behavioral models; however, very few have addressed the sophistication needed to cater to the pragmatic needs of the present day, inducing the real, naturalistic sense of traffic movement. This study endeavors to review the previous following behavior studies in a different aspect and to find the research gaps accordingly. The study disintegrates the following behavioral models based on three levels of heterogeneous traffic conditions: (1) Homogenous Regular Vehicle (Hom-RV); (2) Heterogenous Regular Vehicle (Het-RV); (3) Heterogenous Connected Automated Vehicles (Het-CAV) (4) Heterogenous Regular Vehicle with Connected Autonomous Vehicles (Het-RV-CAV). The categories mentioned above have been explored in terms of the generalized following behavioral model structure having uniform notations to study input-output variables and their inter-relations, data collected and performance measures of the parameters for different traffic conditions. The in-depth review reveals that incorporating human psychological variables, and intelligent vision-based sensors, thereby upgrading the existing dataset and adding more studies considering Het-RV-CAV, can fill the potential gaps in the current knowledge domain.

Keywords

• Car following models
• Following behavior
• Homogenous traffic
• Heterogenous traffic
• Connected autonomous vehicle