Jittering: A Computationally Efficient Method for Generating Realistic Route Networks from Origin-Destination Data

Abstract

Origin-destination (OD) datasets are often represented as ‘desire lines’ between zone centroids. This paper presents a ‘jittering’ approach to pre-processing and conversion of OD data into geographic desire lines that (1) samples unique origin and destination locations for each OD pair, and (2) splits ‘large’ OD pairs into ‘sub-OD’ pairs. Reproducible findings, based on the open source _odjitter_ Rust crate, show that route networks generated from jittered desire lines are more geographically diffuse than route networks generated by ‘unjittered’ data. We conclude that the approach is a computationally efficient and flexible way to simulate transport patterns, particularly relevant for modelling active modes. Further work is needed to validate the approach and to find optimal settings for sampling and disaggregation.