How Far are Autonomous Vehicles from Driving in Real Traffic? The Adaptability Analysis of Autonomous Vehicles to Cut-in Scenarios in China

Abstract

At present, autonomous vehicle technologies (AVTs) have been extensively researched and developed, but there is less research focused on the adaptability of current AVTs to the real traffic. Whether AVTs can be competent in the real driving environment is still an issue. To fill the gap, this paper first collected a great amount of driving data from more than 60 Chinese drivers and established a big natural driving database covering millions of kilometers, all-weather and all working conditions. Then, using the dataset, 3044 cut-in scenarios related to automatic driving were extracted and their characteristics were analyzed based on the cluster method. According to the distribution of cut-in behavior, the related technical requirements of autonomous vehicles were clearly detailed, analyzed, and evaluated from the perspectives of perception, intelligent networking, and motion planning. Finally, from the comparative analysis, we draw the adaptation conclusions of the current AVTs to the real traffic and point out the unsolved challenges. Our conclusions could be very useful for motor corporations and researchers to draw their attention to the complexity of the Chinese traffic environment, and for policy-makers to think about making new AVTs policies in anticipation of the advent of future autonomous vehicles.