Roaming Nairobi Roads: Instrumenting Roads under Resource Constraints

Abstract

Many intelligent transportation systems (ITS) in cities with developed economies are making use of mobile technology as data sources (e.g., many crowd-sourced traffic-related applications) to improve the quality and efficiency of transportation networks. Often, these data sources are used to supplement existing traffic monitoring equipment (e.g., ground-loop detectors, traffic cameras), to provide greater insights into roadway infrastructure and traffic dynamics. For cities with emerging economies where traditional traffic monitoring equipment is cost prohibitive, the rise in mobile technology presents a unique opportunity to leverage smartphone sensors as an alternative data source for ITS. There are, however, challenges to using these sensors particularly with the cost of mobile data, network consistency, and on-device resources. In this paper, we present a mobile system that instruments roads under resource constraint while a vehicle is in motion. It determines when and what data to collect and/or upload using a number of on-device valuation and optimisation functions, by prioritising data collection over uploading or vis-versa. We deployed our mobile system on a fleet of heavy-duty waste-collection trucks in Nairobi, Kenya to collect a large volume of real-word road infrastructure and mobility data. Results show that a 42 % reduction in wireless transmissions costs can be achieved with minimal impact to the time in which important data are collected, uploaded and harmonized into a frequently updated map of road infrastructure and traffic.