TITLE:
Making Data-Driven Transportation Decisions for Freight Operations
AUTHORS:
Kwabena Abedi, Julius Codjoe, Raju Thapa, Vijaya Gopu
KEYWORDS:
Freight, Performance Measures, TTTR Index, Crash Rate, Data-Driven, User Delay Cost
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.13 No.3,
July
17,
2023
ABSTRACT: Using Louisiana’s Interstate system, this paper aims to demonstrate how
data can be used to evaluate freight movement reliability, economy, and safety
of truck freight operations to improve decision-making. Data mainly from the
National Performance Management Research Data Set (NPMRDS) and the Louisiana Crash Database were used
to analyze Truck Travel Time Reliability Index, commercial vehicle User Delay
Costs, and commercial vehicle safety. The results indicate that while
Louisiana’s Interstate system remained reliable over the years, some segments were found to be
unreliable, which were annually less than 12% of the state’s Interstate system
mileage. The User Delay Costs by commercial vehicles on these unreliable
segments were, on average, 65.45% of the User Delay Cost by all vehicles on the
Interstate highway system between 2016 and 2019, 53.10% between 2020 and 2021,
and 70.36% in 2022, which are considerably high. These disproportionate ratios
indicate the economic impact of the unreliability of the Interstate system on
commercial vehicle operations. Additionally, though the annual crash frequencies remained relatively constant, an increasing
proportion of commercial vehicles are involved in crashes, with segments
(mileposts) that have high crash frequencies seeming to correspond with
locations with recurring congestion on the Interstate highway system. The study
highlights the potential of using data to identify areas that need improvement
in transportation systems to support better decision-making.