Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations

TL;DR

This paper develops a distributed approximate dynamic programming method for truck platoon coordination considering realistic Hours-of-Service regulations, demonstrating significant platooning benefits in large-scale simulations.

Contribution

It introduces a novel distributed decision-making scheme that accounts for HoS constraints, enabling effective platoon formation in complex, regulated transportation networks.

Findings

Trucks can drive in platoons for 37% of routes with a 5% delay allowance.

Without delays, platooning occurs for 12% of routes.

Simulation on the Swedish network with 1000 trucks validates the approach.

Abstract

Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints. We propose a distributed decision-making scheme where each truck controls its waiting times at hubs based on the predicted schedules of others. The decoupling of trucks' decision-makings contributes to an approximate dynamic programming approach for platoon coordination under HoS regulations. Finally, we perform a simulation over the Swedish road network with one thousand trucks to evaluate the achieved platooning benefits under the HoS regulations in the European Union (EU). The simulation results show that, on average, trucks drive in platoons for 37% of their routes if each truck is allowed to be delayed for 5% of its total travel time. If trucks are not allowed to be delayed, they drive in platoons for 12% of their routes.