An efficient method for calculating place-based space-time accessibility measures based on the preprocessing of transport networks

Abstract

This paper proposes an efficient method for calculating place-based space-time accessibility measures based on the preprocessing of transport networks and illustrates a case study of using the proposed method. First, we argue from a literature review that the calculation of place-based space-time accessibility measures can be computationally intensive and therefore efficient computational methods for the calculation should be developed. Second, we develop a method that calculates time distances between pairs of nodes in a transport network and thereby reduces the computational time of calculating space-time accessibility measures. Third, we implement the proposed method using the opensource programming language Python and demonstrates a case study that calculates different types of space-time accessibility measures. Last, we argue from the case study that the method can be implemented without great difficulty, runs very fast and works as expected.