This project intends to make an existing Autonomous Truck Mounted Attenuator (ATMA) system fully operational for harsh Canadian weather conditions and develop an augmented perception framework to enhance motion planning of the control system. The primarily focus of an ATMA is ensuring the safety of highway workers and transportation infrastructure in work zones. Upon successfully gaining an understanding of the existing control system, the perception module will be augmented by Visual-LiDAR fusion and semantics integration into the ATMA system, through which reliable decision will make it possible to design a robust control system to address low visibility and perceptually degraded conditions (by Camera or LiDAR) in harsh weather scenarios. By utilizing a wide range of proprioceptive and exteroceptive sensory information, this project will enhanced safe navigation will be enhanced for motion planning and (vehicle) stabilization for the ATMA system.

To achieve the main objective of the project, two main tasks have been identified for this research project: facilitating enhanced perception and full control system integration for ATMA’s autonomous driving (including developing an enhanced detection system for perceptually degraded conditions using multimodal Visual-LiDAR fusion); and comprehensive testing in adverse Canadian weather conditions, with robustness enhancement of the ATMA’s longitudinal controls.

Ehsan Hashemi

MITACS

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