TruePAL: an AI assistant for first responder safety

Thomas Lu; Kyongsik Yun; Alexander Huyen; Edward Chow

doi:10.1117/12.2619146

27 May 2022 TruePAL: an AI assistant for first responder safety

Thomas Lu, Kyongsik Yun, Alexander Huyen, Edward Chow

Proceedings Volume 12101, Pattern Recognition and Tracking XXXIII; 121010D (2022) https://doi.org/10.1117/12.2619146
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple subscenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.

Conference Presentation

Citation Download Citation

Thomas Lu, Kyongsik Yun, Alexander Huyen, and Edward Chow "TruePAL: an AI assistant for first responder safety", Proc. SPIE 12101, Pattern Recognition and Tracking XXXIII, 121010D (27 May 2022); https://doi.org/10.1117/12.2619146

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