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Title:

Driver Reactions to Uphill Grades: Inference from a Stochastic Car-Following Model

Accession Number:

01751488

Record Type:

Component

Availability:

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Order URL: http://worldcat.org/issn/03611981

Abstract:

This paper analyzes the impact of uphill grades on the acceleration drivers choose to impose on their vehicles. Statistical inference is made based on the maximum likelihood estimation of a two-regime stochastic car-following model using Next Generation SIMulation (NGSIM) data. Previous models assume that the loss in acceleration on uphill grades is given by the effects of gravity. We find evidence that this is not the case for car drivers, who tend to overcome half of the gravitational effects by using more engine power. Truck drivers only compensate for 5% of the loss, possibly because of limited engine power. This indicates not only that current models are severely overestimating the operational impacts that uphill grades have on regular vehicles, but also underestimating their environmental impacts. We also find that car-following model parameters are significantly different among shoulder, median and middle lanes but more data is needed to understand clearly why this happens.

Supplemental Notes:

© National Academy of Sciences: Transportation Research Board 2020.

Language:

English

Authors:

Xu, Tu
Laval, Jorge

Pagination:

pp 343-351

Publication Date:

2020-11

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Volume: 2674
Issue Number: 11
Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Web

Features:

References (19)

Subject Areas:

Highways; Safety and Human Factors

Files:

TRIS, TRB, ATRI

Created Date:

Sep 1 2020 3:04PM