Optimizing Energy-Efficient Timely Transportation for Long-Haul Heavy-Duty Trucks: Dynamic Speed Planning and Opportunistic Driving

Project: Research

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Description

AimWe will optimize timely transportation, a key module in heavy-duty truck operation. Our goal is to minimize fuel consumption by dynamic speed planning and opportunistic driving, in the presence of time-varying traffic conditions. Project Background and Project DescriptionIn the US, only 4% of total vehicle population, heavy-duty trucks consume 18% of energy in the whole transportation sector including vehicles and airplanes [1]. Meanwhile, fuel expense accounts for 26~34% of the truck operating cost, of tens of billions of US dollars [1]. These alerting observations, and that the global freight activity is predicted to increase by 2.4x by 2050 [2], make it critical to reduce fuel consumption for sustainable heavy-duty truck operation. In this project, we minimize fuel consumption by optimizing a key in-truck operation module, namely timely transportation, where a heavy-duty truck travels between two locations across the national highway system, subject to a hard deadline constraint. Different from existing studies, we consider the realistic setting of time-varying traffic conditions, and explore two new design spaces of dynamic speed planning and opportunistic driving.- (Minute-scale) dynamic speed planning: Our recent studies show that minute-scale speed planning by GPS-based navigation and adaptive cruise control can save 10% fuel for heavy-duty trucks [3]. It is thus both practical and promising to consider dynamic speed planning in fuel minimization.- Opportunistic driving: this new design space is a consequence of time-varying traffic conditions. The idea is for the truck to strategically wait (e.g., at highway rest areas) for benign traffic conditions, to traverse subsequent road segments at favorable speeds for saving fuel. Our case study based on actual US highway data shows that opportunistic driving can save an extra 11% fuel, on top of path and speed planning [4]. It is thus promising to further explore this new design space to maximize the energy saving. Meanwhile, exploring these design spaces also introduces unprecedented challenges in system modeling and solution design. We will address these challenges and develop algorithms for achieving 20-30% fuel saving for heavy-duty trucks under practical settings. First, we will develop a novel formulation of timely transportation, considering time-varying traffic conditions, dynamic speed optimization, and opportunistic driving. Second, we will then develop computationally-efficient solutions with favorable performance guarantee. We will address critical issues in extending our schemes to practical settings, including highway traffic prediction and online decisions in face of traffic uncertainty. We will also implement our solutions into an online software tool for use in practice. We have observed about 20% fuel saving by optimizing timely transportation in a case study. We will build upon the initial success to develop practical solutions to fully capitalize the benefit of dynamic speed planning and opportunistic driving in energy-efficient timely transportation. Significance of ProjectSuccessful completion of the project will generate new theoretical techniques and online softwaretools for optimizing timely transportation of heavy-duty trucks. The obtained strategies also serve as benchmarks for future solution design. 

Detail(s)

Project number9043103
Grant typeGRF
StatusActive
Effective start/end date1/11/20 → …