Artificial Proprioceptive Reflex Warning Using EMG in Advanced Driving Assistance System

Abstract

A frequent cause of auto accidents is disregarding the proximal traffic of an ego-vehicle during lane changing. Presumably, in a split-second-decision situation we may prevent an accident by predicting the intention of a driver before her action onset using the neural signals data, meanwhile building the perception of surroundings of a vehicle using optical sensors. The prediction of an intended action fused with the perception can generate an instantaneous signal that may replenish the driver's ignorance about the surroundings. This study examines electromyography (EMG) signals to predict intention of a driver along perception building stack of an autonomous driving system (ADS) in building an advanced driving assistant system (ADAS). EMG are classified into left-turn and right-turn intended actions and lanes and object detection with camera and Lidar are used to detect vehicles approaching from behind. A warning issued before the action onset, can alert a driver and may save her from a fatal accident. The use of neural signals for intended action prediction is a novel addition to camera, radar and Lidar based ADAS systems. Furthermore, the study demonstrates efficacy of the proposed idea with experiments designed to classify online and offline EMG data in real-world settings with computation time and the latency of communicated warnings.

Emerging Trends in Realistic Robotic Simulations: A Comprehensive Systematic Literature Review

“…For known environments where the terrain and • Advanced driving assistant system (ADAS) + neuroscience for enhanced vehicle control [59] • Path planning application in unknown and complex environments [2] • Autonomous driving applications [21], [33], [37], [60]- [66] • Intelligent Transportation Systems (ITS) [67] • Gesture recognition for human-vehicle interaction [68] • All-terrain vehicle (ATV) with autonomous navigation and teleoperation [69] • Robust localisation of Autonomous Cars [70] • Socially aware robot navigation [34], [71], [72]…”

“…They ensure that while a robot remains agile in its movements, it doesn't endanger its integrity or that of its environment. [116], ICP 3 + SVM 4 [132], 2D multi-SLAM [77], GMapping [87], [88], [105], FNN 5 [27], Visual-SLAM + RTAB-Map 6 [126], RTAB-Map [94], Cartographer [65], Monocular SLAM + RL [36], KimeraMulti [133] 2 -Object Detection YOLOv4 7 [62], [103], YOLOv3 [31], [59], [62], YOLOv2 [134], PointNet [135], CNN 8 [21], [23], [136], SVM [137], MobileNet [138], YOLOv2 + JPDA 9 + IMM 10 [139] 3 -Object Tracking…”

Persona-PhysioSync AV: Personalized Interaction through Personality and Physiology Monitoring in Autonomous Vehicles

“…Studies such as that by Katsis et al (2008) show that driver distraction is marked by reduced EMG signal amplitude and frequency, making it a useful tool for assessing alertness levels [79]. The work by Hussain et al (2023) expresses the use of EMG for intended action prediction as an addition to the use of cameras and radar-and lidar-based advanced driver assistance systems in AVs [92]. Additionally, the research showcases the effectiveness of the suggested concept through experiments aimed at categorizing online and offline EMG data in real-world environments [92].…”

“…The work by Hussain et al (2023) expresses the use of EMG for intended action prediction as an addition to the use of cameras and radar-and lidar-based advanced driver assistance systems in AVs [92]. Additionally, the research showcases the effectiveness of the suggested concept through experiments aimed at categorizing online and offline EMG data in real-world environments [92]. Demonstrating the assessment of a driver's capability to respond to TORs using EMG measurements adequately was exemplified by [93].…”