Level of traffic stress-based classification: A clustering approach for Bogota, Colombia.

ABSTRACT: The Level of Traffic Stress (LTS) is an indicator that quantifies the stress experienced by a cyclist on the segments of a road network. We propose an LTS-based classification with two components: a clustering component and an interpretative component. Our methodology is comprised of four steps: (i) compilation of a set of variables for road segments, (ii) generation of clusters of segments within a subset of the road network, (iii) classification of all segments of the road network into these clusters using a predictive model, and (iv) assignment of an LTS category to each cluster. At the core of the methodology, we couple a classifier (unsupervised clustering algorithm) with a predictive model (multinomial logistic regression) to make our approach scalable to massive data sets. Our metho

SUBMITTER: Huertas JA 

PROVIDER: S-EPMC7437968 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature