RFDrive: Tagged Human-Vehicle Interaction for All

Abstract

Human-vehicle interaction is important for safe driving. The driver needs to interact with the in-vehicle steering wheel and infotainment system properly during driving. Specifically, the driving guidelines require the driver to hold the steering wheel from 3-9 o’clock. Moreover, the in-vehicle infotainment system should be more adaptive for the driver and front-seat passenger during driving (i.e., the in-vehicle infotainment system should be part and even fully disabled for the driver, while the front-seat passenger should enjoy the full in-vehicle infotainment system). However, affordable vehicles are usually designed to achieve basic driving functions without considering the safe human-vehicle interactions, which require an add-on, affordable, and ready-to-use human-vehicle interaction monitoring system. In this paper, we present RFDrive, a system that can simultaneously localize the driver’s hand position on the steering wheel and automate in-vehicle infotainment system touch discrimination for safe driving, using commodity passive RFID tags. Since these commodity passive RFID tags are low-cost (i.e., around 5 cents per tag), battery-free, and small form factor like a sticker, our design will enable not only safe driving but also a sustainable society for all drivers, especially drivers with affordable vehicles. To do so, we attach RFID tags on the steering wheel for driver’s hand position localization and attach RFID tags on the roof of the vehicle’s interior for in-vehicle infotainment system touch discrimination (i.e., differentiating driver’s infotainment system touch and front-seat passenger’s infotainment system touch). However, the wheel steering will distort the wireless channel-based driver’s hand position localization on the steering wheel. So, we propose a novel tag ID-based algorithm to localize the driver’s hand position on the steering wheel by harnessing the human body as part of the RFID tag’s antenna. Since the in-vehicle infotainment system touch from the driver or front-seat passenger will affect different RFID tags attached to the roof of the vehicle’s interior, we propose to use the differential amplitude of backscattered signals from all the tags to discriminate in-vehicle infotainment system touch sources. Our experiments show that RFDrive can achieve the average accuracy of 0.98 and 0.98 for in-vehicle touch source discrimination and driver’s hands’ position localization respectively.