Trucks

This article demonstrates the use of deep neural networks (NN) and deep reinforcement learning (deep-RL) for modeling and control of longitudinal heavy duty truck dynamics. Instead of explicit use of analytical model derived information or parameters about the truck, the deep NN model is fitted to data using a brief set of historical data collected from an arbitrary driving cycle. The deep model is used in this article to design a cruise controller for the truck using model-free deep-RL. The deep model and the control loop performances are demonstrated both using state-of-the-art...

This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter's resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration...

Building control systems for heavy duty trucks have historically been dependent on availability of the details of the mechanical configuration of each target truck. This article investigates transfer and robustness of continuous control systems learned using model free deep-RL as an alternative; a configuration agnostic strategy for control system development. For this purpose, deep-RL cruise control policies are developed and validated in simulation and field experiments using two differently configured trucks; full-size Volvo and Freightliner trucks. Their performance are validated for...

Commercial heavy vehicles, unlike passenger vehicles, display huge variation in parameters such as vehicle mass. Coupled with lower actuation authorities (engine and brake capabilities), these variations can induce actuator saturation even in moderately demanding maneuvers, presenting challenge to the task of maintaining string stability in a platoon formation of heavy trucks. A new control scheme is proposed to put on-line bounds, or artificial saturation, on command signals via parameter estimation such that all members in a platoon can follow the reference commands without saturating...