Effects of autonomous vehicles on pavement distress & road safety and pavement distress optimization

Rana, Md Masud (2021) Effects of autonomous vehicles on pavement distress & road safety and pavement distress optimization. Masters thesis, Memorial University of Newfoundland.

[img] [English] PDF - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (3MB)


The commercial application of automation technology in passenger and freight transport will bring positive revolutionary changes in transportation mobility. Despite having more advantages, automation in trucking technology has some detrimental effects on the performance of asphalt pavement and highway safety. This study focuses on optimization of asphalt pavement distresses and prediction of rutting induced traffic safety factors for movement of autonomous trucks. This study optimizes the asphalt concrete (AC) pavement distresses by devising traffic input in Mechanistic-Empirical Pavement Design Software, AASHTOWare. An increase in pavement distresses was observed for a small increase in the standard deviation of wheel wander, uniform distribution of truck traffic loading, and equal distribution of vehicle positioning on the road lanes. Permanent deformation of the asphalt concrete layer for roads (PEDRO) model was incorporated to predict AC pavement rutting for a typical pavement section. Hydroplaning speed and skid resistance as traffic safety factors were evaluated from widely accepted empirical equations for the induced rutting. A standard tire rather than a truck tire was considered due to its high susceptibility to traffic safety. A graphical relationship has been proposed to obtain a design threshold value for hydroplaning speed, water film depth and autonomous truck speed. An attempt was made to improve pavement performance by increasing frequency of truck load in low-temperature period of a day.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/15029
Item ID: 15029
Additional Information: Includes bibliographical references.
Keywords: Autonomous Truck, Pavement Distresses, Optimization, Traffic Safety, Low-Temperature Duration
Department(s): Engineering and Applied Science, Faculty of
Date: May 2021
Date Type: Submission
Digital Object Identifier (DOI): https://doi.org/10.48336/SCD4-2A58
Library of Congress Subject Heading: Pavements--Performance; Automated vehicles.

Actions (login required)

View Item View Item


Downloads per month over the past year

View more statistics