Understanding the Lateral Dimension of Traffic: Measuring and Modeling Lane Discipline

Abstract

There is growing interest in understanding the lateral dimension of traffic. This trend has been motivated by the detection of phenomena unexplained by traditional models and the emergence of new technologies. Previous attempts to address this dimension have focused on lane-changing and non-lane-based traffic. The literature on vehicles keeping their lanes has generally been limited to simple statistics on vehicle position while models assume vehicles stay perfectly centered. Previously the author developed a two-dimensional traffic model aiming to capture such behavior qualitatively. Still pending is a deeper, more accurate comprehension and modeling of the relationships between variables in both axes. The present paper is based on the Next Generation SIMulation (NGSIM) datasets. It was found that lateral position is highly dependent on the longitudinal position, a phenomenon consistent with data capture from multiple cameras. A methodology is proposed to alleviate this problem. It was also discovered that the standard deviation of lateral velocity grows with longitudinal velocity and that the average lateral position varies with longitudinal velocity by up to 8 cm, possibly reflecting greater caution in overtaking. Random walk models were proposed and calibrated to reproduce some of the characteristics measured. It was determined that drivers’ response is much more sensitive to the lateral velocity than to position. These results provide a basis for further advances in understanding the lateral dimension. It is hoped that such comprehension will facilitate the design of autonomous vehicle algorithms that are friendlier to both passengers and the occupants of surrounding vehicles.

Statistical Models of Interactions between Vehicles during Overtaking Maneuvers

“…Furthermore, it was found that longitudinal velocity affects not only average lateral velocity and acceleration but also their dispersion. In specific terms, their dispersion parameter depends linearly on longitudinal velocity, a result that is consistent with earlier findings ( 2 ).…”

“…A possible explanation for this behavior is the better perspective and, therefore, the greater control drivers have with regard to what occurs on their left because of being seated on that side of their vehicle (in countries such as Germany where traffic drives on the right-hand side of the road). The same reasoning would also explain why the average lateral position of the vehicles is to the left of the center of the lane ( 2 , 18 ).…”

“…However, one of the main obstacles that can be overcome, at least in part, is the poor understanding of the importance and influence of the lateral dimension in vehicle traffic. This gap in the current state of knowledge has meant that lateral interactions have been a significant cause of driverless vehicle accidents, and a concern for their passengers ( 2 ).…”

“…Little has been published in the way of measurement, although two papers worthy of mention are Budhkar and Maurya ( 6 ), which establishes a relationship between vehicle velocities and the lateral distance separating them, and Jin ( 7 ), which studies the lane-change process. The present authors have contributed with an article that identifies the particular behavior of vehicles traveling side by side ( 8 ) and two others that explore lane discipline and its modeling ( 2 , 9 ). As regards modeling, the first attempt to model traffic in two dimensions and reproduce lateral friction dates back to Gunay ( 10 ), and subsequent work has pursued various angles.…”

Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration

“…Nevertheless, lateral movement has not been sufficiently investigated in simulation-based studies. Recently, Delpiano [31] recommended a study of the lateral dimension according to CAV behaviour. Aimsun developers demonstrated the feasibility of calibrating these parameters in their traffic model.…”