Valerio Turri

Heavy-Duty Vehicle Platooning for Sustainable Freight Transportation: A Cooperative Method to Enhance Safety and Efficiency

The current system of global trade is largely based on transportation and communication technology from the 20th century. Advances in technology have led to an increasingly interconnected global market and reduced the costs of moving goods, people, and technology around the world. Transportation is crucial to society, and the demand for transportation is strongly linked to economic development. Specifically, road transportation is essential since about 60% of all surface freight transportation (which includes road and rail transport) is done on roads [2]. Despite the important role of road freight transportation in the economy, it is facing serious challenges, such as those posed by increasing fuel prices and the need to reduce greenhouse gas emissions. On the other hand, the integration of information and communication technologies to transportation systems-leading to intelligent transportation systems-enables the development of cooperative methods to enhance the safety and energy efficiency of transportation networks. This article focuses on one such cooperative approach, which is known as platooning. The formation of a group of heavy-duty vehicles (HDVs) at close intervehicular distances, known as a platoon (see Figure 1) increases the fuel efficiency of the group by reducing the overall air drag. The safe operation of such platoons requires the automatic control of the velocity of the platoon vehicles as well as their intervehicular distance.

Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads

This paper presents a control architecture based on a linear MPC formulation that addresses the lane keeping and obstacle avoidance problems for a passenger car driving on low curvature roads. The proposed control design decouples the longitudinal and lateral dynamics in two successive stages. First, plausible braking or throttle profiles are defined over the prediction horizon. Then, based on these profiles, linear time-varying models of the vehicle lateral dynamics are derived and used to formulate the associated linear MPC problems. The solutions of the optimization problems are used to determine for every time step, the optimal braking or throttle command and the corresponding steering angle command. Simulations show the ability of the controller to overcome multiple obstacles and keep the lane. Experimental results on an autonomous passenger vehicle driving on slippery roads show the effectiveness of the approach.

Cooperative Look-Ahead Control for Fuel-Efficient and Safe Heavy-Duty Vehicle Platooning

The operation of groups of heavy-duty vehicles at a short inter-vehicular distance, known as platoon, allows one 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 trucks, slopes have a significant impact on the feasible and optimal speed profiles that each vehicle can and should follow. 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 heavy-duty vehicle 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 follower vehicles compared with the use of standard platoon controllers.

Cyber–Physical Control of Road Freight Transport

Freight transportation is of outmost importance in our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of the total energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber–physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network.

Fuel-efficient heavy-duty vehicle platooning by look-ahead control

The operation of groups of heavy-duty vehicles at close intervehicular distances (known as platoons) has been shown to be an effective way of reducing fuel consumption. For single vehicles, it is also known that the availability of preview information on the road topography can be exploited to obtain fuel savings. The current paper aims at the inclusion of preview information in platooning by introducing a two-layer control system architecture for so-called look-ahead platooning. Here, the layers are responsible for the inclusion of preview information and real-time vehicle control for platooning, respectively. Within this framework, a control strategy is presented, where dynamic programming is used for the calculation of fuel-optimal speed profiles, while a model predictive control approach is exploited for the real-time vehicle control. The feasibility of this approach is illustrated by means of the simulation of relevant scenarios.

A model predictive controller for non-cooperative eco-platooning

This paper proposes an energy-saving adaptive cruise control (ACC) which exploits the future trajectory of the preceding vehicle to minimize unnecessary braking. By suitable design of the model predictive control terminal set, the proposed eco-ACC avoids unnecessary braking and improves fuel economy, while guaranteeing safety and limited online computational burden. Simulations and experiments show the efficacy of the approach and confirm fuel saving, when the eco-ACC is compared to baseline ACC formulations.

Gear management for fuel-efficient heavy-duty vehicle platooning

Vehicle platooning has great potential for the reduction of greenhouse gas emissions and fuel consumption of heavy-duty vehicles. However, previous works on fuel-efficient platoon control largely ignore the effect of gear changes, even though experimental studies have shown that gear shifts have a large impact on the behavior and fuel consumption of vehicle platoons. In particular, the interruption in traction force during a gear shift can cause large deviations in the tracking of the reference speed and inter-vehicle distance and can result in the braking of the vehicles. In this paper, we discuss a control architecture that includes the management of gear shifts and we propose a method to select the gears that takes fuel-efficiency into account, but also targets the good behavior of the platoon. In detail, the proposed method is based on a dynamic programming formulation that computes the optimal sequence of gear shifts necessary for the fuel-efficient and smooth tracking of a given reference speed profile. The performance of the proposed approach is finally analyzed by means of simulations by comparing it with the performance of alternative solutions.

Control-Oriented Modeling of Motorcycle Dynamics

Recent technology advances in the field of ride-by-wire technology for motorcycle (namely active braking and full electronic throttle) open the way to the design of innovative control strategies to improve two-wheeled vehicles stability. As such, it is of growing importance to devise control oriented models of the bike dynamics to be employed for control design purposes. This paper proposes an analytical model of a two-wheeled vehicle tuned to capture the coupling between longitudinal variables (i.e. traction and braking torque) and out-of-plane modes. The model is derived from first principles. The model parameters are identified from a complete multi-body simulator. The proposed model offers a good tradeoff between complexity and accuracy.