RFDrive: Tagged Human-Vehicle Interaction for All

Abstract

Human–vehicle interaction is an important factor for safe driving. The driver needs to interact with the in-vehicle steering wheel and infotainment system properly during driving. Specifically, driving guidelines require the driver to hold the steering wheel at the 3 o’clock and 9 o’clock positions. 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, whereas the front-seat passenger should be able to enjoy the full in-vehicle infotainment system). However, affordable vehicles are usually designed to achieve basic driving functions without considering safe human–vehicle interactions, which require an add-on, affordable, and ready-to-use human–vehicle interaction monitoring system. In this article, we present RFDrive, a system that can simultaneously locate the driver’s hand positions 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 are small, like a sticker, our design will enable not only safe driving but is also low cost, which can lead to sustainable solutions. To do so, we attach RFID tags on the steering wheel for the driver’s hand position location and attach RFID tags on the roof of the vehicle’s interior for in-vehicle infotainment system touch discrimination (i.e., differentiating the 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 location on the steering wheel. Thus, we propose a novel tag ID-based algorithm to locate 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 hand position location, respectively.