Development of advanced public transportation system with limited infrastructure support

Abstract

An effective public transportation system is vital for socioeconomic development. This paper presents the software for scalable implementation of arrival time prediction, automatic bus-stop detection, and bus crowdedness detection to increase the efficiency of the public transportation system. It utilizes the bus trajectories and crowdsourced commuters’ data. The software can be executed in developing countries where the deployment of Intelligent Transportation System (ITS) infrastructures is limited. The software users can run the code on their data records, modify the code to create their own APTS algorithms and use the provided dataset to validate them.

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