Waze is an example of a widely-used system that uses crowd-sourced human reporting to share knowledge about road conditions. In this video, we present a demo of LiveMap on the streets of Pittsburgh. LiveMap is a research system built at Carnegie Mellon University that is conceptually similar to Waze, but avoids the driver distraction that is inherent in human reporting from a single-occupant vehicle.
LiveMap uses edge computing to perform video analytics close to the point of data capture. Computer vision algorithms running on an in-vehicle computer (called a "vehicular cloudlet") continuously analyze video streams from one or more cameras mounted on that vehicle. Observations from these algorithms are transmitted over a 4G LTE wireless network to a central collection point (called a "zone cloudlet"), where the reports from many vehicles are synthesized and disseminated.
Kevin Christensen, Christoph Mertz, Padmanabhan Pillai, Martial Hebert, and Mahadev Satyanarayanan. 2019. Towards a Distraction-free Waze. In Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications (HotMobile '19). ACM, New York, NY, USA, 15-20. DOI: https://doi.org/10.1145/3301293.3302369