An Intelligent Self-Driving Truck System for Highway Transportation

Abstract

Recently, there have been many advances in autonomous driving society, attracting a lot of attention from academia and industry. However, existing studies mainly focus on cars, extra development is still required for self-driving truck algorithms and models. In this article, we introduce an intelligent self-driving truck system. Our presented system consists of three main components, 1) a realistic traffic simulation module for generating realistic traffic flow in testing scenarios, 2) a high-fidelity truck model which is designed and evaluated for mimicking real truck response in real world deployment, and 3) an intelligent planning module with learning-based decision making algorithm and multi-mode trajectory planner, taking into account the truck's constraints, road slope changes, and the surrounding traffic flow. We provide quantitative evaluations for each component individually to demonstrate the fidelity and performance of each part. We also deploy our proposed system on a real truck and conduct real world experiments which show our system's capacity of mitigating sim-to-real gap. Our code is available at https://github.com/InceptioResearch/IITS.

Stability Analysis of a Vehicle–Cargo Securing System for Autonomous Trucks Based on 6-SPS-Type Parallel Mechanisms

“…However, there are still several challenges that need to be resolved in self-driving truck systems, such as precise control with complex truck system dynamics and corresponding truck-aware decision making, etc. [2]. Due to the lack of human intervention, cargo loosening, shifting, off-centered positions, and so on during transportation would negatively impact vehicle dynamics and stability and bring huge economic losses, which suggests the need for higher requirements for the stability of the securing system of autonomous trucks [3].…”