Date of Graduation

5-2019

Document Type

Thesis

Degree Name

Bachelor of Science in Industrial Engineering

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

Nurre, Sarah

Committee Member/Reader

Hernandez, Sarah

Committee Member/Second Reader

Sullivan, Kelly M.

Abstract

The Truck Parking Problem occurs when drivers have met the daily driving limit and encounter a decision between driving over time or parking in unauthorized locations. This research applies data analytics to gain further knowledge to characterize the truck parking shortage in Arkansas. Truck parking shortages are a serious problem that truck drivers face daily and is complex due to Hours of Service (HOS) regulations restrictions on legal parking areas and design. Existing research includes a one-day annual survey which compiles where public rest stops, businesses, and private rest stops are utilized by truck drivers. This research expands on the survey to capture broader time-of-day and daily patterns. This was done by calculating the following metrics for truck parking: how many drivers occupy a specific rest area at arrival, by time of day, and how long each driver stays at a rest location. To accomplish this research task, we combined multiple real data sources representing truck parking locations and truck travel characteristics represented by GPS “pings” over a one-year period. We used data analytics to describe and characterize the truck parking problem over time and geographic location. We then used the defined metrics to compare and contrast many locations across Arkansas. This research presents the findings using a user-friendly heat map which demonstrates the knowledge gained from this research. As a result, this heat map can serve as the visual foundation for new policies on truck parking expansion and show how HOS regulatory requirements are impacting truck drivers throughout the state.

Keywords

Truck; Parking; ArDot; Arkansas; Capacity

Download

Share

COinS