Beyond Target-Level: ISAC-Enabled Event-Level Sensing for Behavioral Intention Prediction

TL;DR

This paper introduces an ISAC-enabled framework for behavioral intention prediction in autonomous driving, demonstrating improved accuracy in adverse weather conditions through extensive simulations.

Contribution

It presents the first ISAC-based BIP framework, showing its effectiveness and robustness in safety-critical scenarios compared to traditional sensor methods.

Findings

F1-score improved by 11.4% in adverse weather

Demonstrates ISAC's potential for event-level sensing

Validates framework through extensive simulations

Abstract

Integrated Sensing and Communication (ISAC) holds great promise for enabling event-level sensing, such as behavioral intention prediction (BIP) in autonomous driving, particularly under non-line-of-sight (NLoS) or adverse weather conditions where conventional sensors degrade. However, as a key instance of event-level sensing, ISAC-based BIP remains unexplored. To address this gap, we propose an ISAC-enabled BIP framework and validate its feasibility and effectiveness through extensive simulations. Our framework achieves robust performance in safety-critical scenarios, improving the F1-score by 11.4% over sensor-based baselines in adverse weather, thereby demonstrating ISAC's potential for intelligent event-level sensing.