title: Gap Acceptance During Lane Changes by Large-Truck Drivers-An Image-Based Analysis.
abstract: This paper presents an analysis of rearward gap acceptance characteristics of drivers of large trucks in highway lane change scenarios. The range between the vehicles was inferred from camera images using the estimated lane width obtained from the lane tracking camera as the reference. Six-hundred lane change events were acquired from a large-scale naturalistic driving data set. The kinematic variables from the image-based gap analysis were filtered by the weighted linear least squares in order to extrapolate them at the lane change time. In addition, the time-to-collision and required deceleration were computed, and potential safety threshold values are provided. The resulting range and range rate distributions showed directional discrepancies, i.e., in left lane changes, large trucks are often slower than other vehicles in the target lane, whereas they are usually faster in right lane changes. Video observations have confirmed that major motivations for changing lanes are different depending on the direction of move, i.e., moving to the left (faster) lane occurs due to a slower vehicle ahead or a merging vehicle on the right-hand side, whereas right lane changes are frequently made to return to the original lane after passing.
authors.affiliation: University of Michigan Transportation Research Institute, Ann Arbor, MI 48109 USA.
authors.forename: Kazutoshi
authors.initials: K
authors.lastname: Nobukawa
authors.affiliation: University of Michigan Transportation Research Institute, Ann Arbor, MI 48109 USA.
authors.forename: Shan
authors.initials: S
authors.lastname: Bao
authors.affiliation: University of Michigan Transportation Research Institute, Ann Arbor, MI 48109 USA.
authors.forename: David J
authors.initials: DJ
authors.lastname: LeBlanc
authors.affiliation: Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109 USA.
authors.forename: Ding
authors.initials: D
authors.lastname: Zhao
authors.affiliation: Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109 USA.
authors.forename: Huei
authors.initials: H
authors.lastname: Peng
authors.affiliation: National Institute for Occupational Safety and Health, Morgantown, WV 26505 USA.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Pan
keywords: Active safety; gap analysis; lane change; large truck safety; naturalistic driving data