On-trip Behavior of Truck Drivers on Freeways: New mathematical models and control methods

Salil Sharma

Research output: ThesisDissertation (TU Delft)

56 Downloads (Pure)

Abstract

Congestion, a frequent problem on freeways, is often considered a major challenge for the operations of road freight transport. Trucks, the main choice for road freight, not only suffer from congestion but they also contribute to it. Consequently, billions of dollars are lost worldwide in trucking operations, which also impedes economic growth and prosperity. Understanding driving behavior and on-trip decision-making of truck drivers are critically important to design measures that mitigate the impacts of congestion on truck traffic, and vice versa, to design measures that mitigate the impacts of truck traffic on congestion. In this respect, the on-trip behavior of truck drivers can be decomposed—like driving behavior in general—into strategical, tactical, and operational behavior, depicting route choice, short-term path-planning (e.g. merging, lane changing), and the steering & accelerating of the vehicle, respectively. Whereas these on-trip behaviors have been studied in-depth for drivers of passenger cars, there are larger gaps in our knowledge when it comes to strategical, tactical and operational behavior of trucks. Furthermore, our limited insight into the driving behavior of truck drivers inhibits the design of appropriate traffic control and management measures.
To improve freight and traffic operations on freeways, this dissertation focuses on obtaining insights into the on-trip behavior of truck drivers and influencing this behavior for congestion relief. To this end, this dissertation develops new mathematical models and control methods for the strategical, tactical and operational behavior of truck drivers by analyzing emerging datasets and designing novel cooperative intelligent transportation system (C-ITS) applications.....
Original languageEnglish
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • van Lint, J.W.C., Supervisor
  • Tavasszy, L.A., Supervisor
  • Snelder, M., Supervisor
Award date31 Oct 2023
Print ISBNs978-90-5584-337-4
DOIs
Publication statusPublished - 2023

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