Modeling Large-Scale Walking and Cycling Networks: A Machine Learning Approach Using Mobile Phone and Crowdsourced Data

arXiv:2404.00162v1 Announce Type: new
Abstract: Walking and cycling are known to bring substantial health, environmental, and economic advantages. However, the development of evidence-based active transportation planning and policies has been impeded by significant data limitations, such as biases in crowdsourced data and representativeness issues of mobile phone data. In this study, we develop and apply a machine learning based modeling approach for estimating daily walking and cycling volumes across a large-scale regional network in New South Wales, Australia that includes …

abstract advantages arxiv biases cs.lg cs.na cycling data development economic environmental evidence health however limitations machine machine learning math.na mobile modeling networks phone planning policies scale transportation type walking