Cooperative look-ahead control for fuel-efficient and safe heavy-duty vehicle platooning (1505.00447v1)

Abstract: The operation of groups of heavy-duty vehicles (HDVs) at a small inter-vehicular distance (known as platoon) allows to lower the overall aerodynamic drag and, therefore, to reduce fuel consumption and greenhouse gas emissions. However, due to the large mass and limited engine power of HDVs, slopes have a significant impact on the feasible and optimal speed profiles that each vehicle can and should follow. Therefore maintaining a short inter-vehicular distance as required by platooning without coordination between vehicles can often result in inefficient or even unfeasible trajectories. In this paper we propose a two-layer control architecture for HDV platooning aimed to safely and fuel-efficiently coordinate the vehicles in the platoon. Here, the layers are responsible for the inclusion of preview information on road topography and the real-time control of the vehicles, respectively. Within this architecture, dynamic programming is used to compute the fuel-optimal speed profile for the entire platoon and a distributed model predictive control framework is developed for the real-time control of the vehicles. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios that suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of standard platoon controllers.

• The paper proposes a two-layer control framework combining dynamic programming and distributed model predictive control to optimize speed profiles for fuel-efficient and safe HDV platooning.
• This framework utilizes a platoon coordinator with dynamic programming for global speed optimization and a vehicle controller with distributed model predictive control for real-time tracking and safety.
• Simulations demonstrate that this cooperative look-ahead control yields significant fuel savings, outperforming traditional methods and showing superior results with a time gap policy.

Overview of Cooperative Look-Ahead Control for HDV Platooning

The paper "Cooperative Look-Ahead Control for Fuel-Efficient and Safe Heavy-Duty Vehicle Platooning" by Valerio Turri, Bart Besselink, and Karl H. Johansson explores a two-layer control framework aimed at enhancing the fuel efficiency and safety of heavy-duty vehicle (HDV) platooning. As the transportation sector is under pressure to reduce greenhouse gas emissions significantly, platooning emerges as a viable solution to decrease aerodynamic drag and fuel consumption, with demonstrable savings up to 12% for follower vehicles when compared to traditional platooning methods.

Control Architecture and Optimization

The authors propose a control framework that consists of two distinct layers: the platoon coordinator and the vehicle controller layer. The central concept revolves around exploiting preview information regarding road topography to compute an optimal speed profile that the entire platoon can follow safely and efficiently.

1. Platoon Coordinator Layer: This layer employs a dynamic programming (DP) approach to determine a speed trajectory based on the road ahead, considering both slope variations and vehicle constraints. The coordinator produces a unified speed profile for all vehicles, ensuring consistency and potential fuel savings. The DP-based formulation captures the non-linear models of HDVs, thus providing a robust method for optimizing the speed profile over significant spatial horizons.
2. Vehicle Controller Layer: Utilizing a distributed model predictive control (DMPC) strategy, this layer focuses on real-time tracking of the speed profile and maintaining a specified inter-vehicular spacing. It ensures safety with robust handling of potential collisions and the ability to manage heterogeneous platoons with varied vehicle characteristics.

Simulation and Performance Analysis

Simulations targeted several real-world and hypothetical configurations. When compared to traditional cruise control (CC) and standalone look-ahead control (LAC) methods, the cooperative look-ahead control (CLAC) yielded notable fuel savings. For example, simulations on a 45 km highway revealed that adopting CLAC can deliver up to 3.6% additional energy savings for the platoon over LAC strategies.

Analysis further differentiated between gap policies including space gap (SG), headway gap (HG), and time gap (TG), revealing how each affects braking actions and fuel efficiency. The TG policy, allowing vehicles to follow the same speed profile spatially, resulted in superior fuel savings when implemented with CLAC.

Implications and Future Prospects

The proposed framework for coordinating HDVs in a platoon introduces significant practical improvements in terms of fuel economy without sacrificing safety. Its ability to integrate topographical information and synchronize vehicle dynamics across the platoon positions it as a robust solution that can adapt to varying road conditions.

However, practical considerations such as the limitation imposed by mechanical gear-shift systems and real-time traffic disturbances have been noted as areas for future enhancement. More sophisticated models accounting for discrete gear ratios and their impact on fuel efficiency could be developed. Further, the integration of reactive strategies to handle unexpected traffic behaviors autonomously will be pivotal in advancing autonomous platoon operations.

In summary, the paper provides a comprehensive method for optimizing HDV platoon operations, potentially contributing to more sustainable freight transport systems. As automation in vehicular technology progresses, such cooperative strategies promise to play a critical role in the continued evolution toward greener transportation networks.