Dynamic evaluation of emergency lane occupation based on an improved driving risk field model

Abstract

In China, the frequent occupation of emergency lanes on highways significantly affects traffic efficiency and safety. This study collected data from six highway segments and extracted lane-changing (LC) behavior. A logistic regression model was employed to identify key factors influencing emergency lane changes (ELC). An improved driving risk field model was developed to assess risks during the LC process, integrating the heading angle of the obstacle vehicles, speeds of both the main and obstacle vehicles, as well as the filtering effect of lane lines. Compared to three existing risk field models, our model provides a more accurate assessment of collision risks during lane changes. This study revealed that the primary reasons for ELC are driven by the pursuit of speed and driving space, influenced by the speed and relative distance of surrounding vehicles, and the intention to overtake. Moreover, ELC is characterized by reduced lateral speed and acceleration, as well as a lower minimum time-to-collision (TTC), while exhibiting higher acceptable risks. Risk variation trends during lane changes from emergency to normal lanes include conservative, general, and aggressive types, while changes from normal to emergency lanes feature only conservative and general types. Additionally, ELC significantly negatively impacts following vehicles in the target lane after LC, leading to greater lateral displacement, more significant longitudinal deceleration, and heightened risk levels.