Abstract

The Space-time prism (STP) is a key concept in time geography for analyzing human activity-travel behavior under various Space-time constraints. Most existing time-geographic studies use a straightforward algorithm to construct STPs in road networks by using two one-to-all shortest path searches. However, this straightforward algorithm can introduce considerable computational overhead, given the fact that accessible links in a STP are generally a small portion of the whole network. To address this issue, an efficient geo-computational algorithm, called NTP-A*, is proposed. The proposed NTP-A* algorithm employs the A* and branch-and-bound techniques to discard inaccessible links during two shortest path searches, and thereby improves the STP construction performance. Comprehensive computational experiments are carried out to demonstrate the computational advantage of the proposed algorithm. Several implementation techniques, including the label-correcting technique and the hybrid link-node labeling technique, are discussed and analyzed. Experimental results show that the proposed NTP-A* algorithm can significantly improve STP construction performance in large-scale road networks by a factor of 100, compared with existing algorithms.

Highlights

  • Time geography is powerful for analyzing human movements and activities through space and time [1]

  • This study investigates models and geo-computational algorithms for efficiently constructing network–time prisms (NTPs) in real road networks

  • Few efficient geo-computational algorithms have been developed in the literature for constructing network–time prisms (NTPs) in realistic road networks

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Summary

Introduction

Time geography is powerful for analyzing human movements and activities through space and time [1]. These spatiotemporal big data provide an unprecedented opportunity for time-geographic studies to uncover people’s mobility patterns and their interactions with the urban environment [23,24,25,26,27,28,29,30] To support such time-geographic studies in the era of spatiotemporal big data, efficient geo-computational algorithms for constructing NTPs in large-scale road networks are sorely needed. The accessible nodes (and links) can be determined by checking whether their earliest arrival time is larger than the latest departure time Such a NTP-Dij algorithm is easy to implement by directly using the classical shortest path algorithm (i.e., Dijkstra’s algorithm). This study contributes to time-geography literature in the following aspects: Firstly, an improved NTP model is proposed by considering the complexities of road networks, including turn restrictions and divided/undivided roads.

The Classical Space-Time Prism Model in the Planar Space
Constructing Space-Time Prisms in Road Networks
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