Identification of Potential Warning Signals for a Smartphone-based Bicyclist Assistant System

Abstract

Bicycle-vehicle crashes are common and often result in severe outcomes for bicyclists. Assistive technologies may help mitigate bicycle-vehicle crashes; however, these technologies applied to bicycles are understudied. This paper summarizes a preliminary study to identify effective warning signals for a smartphone-based application. This application alerts bicyclists to an imminent collision with a vehicle using a warning signal and gives them additional time to avoid the collision. The signal, however, must be designed to be informative and not otherwise distracting. This work analyzes discussions from experts and stakeholders on the modality and design of warning signals, as well as the efficacy of the mobile application. The experts were presented with visual, audible, and haptic signal options. Text analysis of the focus group transcript shows that flashing visual signals, high pitch auditory tones, and speech messages were most favored by participants.