Understanding the lateral dimension of traffic: Measuring and modeling lane discipline

Rafael Delpiano*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.

Original languageEnglish
Title of host publicationTransportation Research Record
PublisherSAGE Publications Ltd
Pages1030-1042
Number of pages13
Edition12
DOIs
StatePublished - 2021

Publication series

NameTransportation Research Record
Number12
Volume2675
ISSN (Print)0361-1981
ISSN (Electronic)2169-4052

Bibliographical note

Funding Information:
The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author acknowledges support from FONDECYT through grant Proyecto Fondecyt Iniciación No. 11201137.

Funding Information:
The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author acknowledges support from FONDECYT through grant Proyecto Fondecyt Iniciacio?n No. 11201137.

Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2021.

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