An approach for computing routes without complicated decision points in landmark-based pedestrian navigation. Issue 9 (2nd September 2019)

• Record Type: Journal Article
• Authors: Zhou, Sha; Wang, Run; Ding, Junhua; Pan, Xiaofang; Zhou, Shunping; Fang, Fang; Zhen, Wenjie
• Is Part Of: International journal of geographical information science. Volume 33:Issue 9(2019)
• Page Start: 1829
• Page End: 1846
• Publication Date: 2019-09-02
• Subjects: Landmark -- pedestrian navigation -- decision point -- route planning -- genetic algorithm; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2019.1603387
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: During navigation, a pedestrian needs to recognize a landmark at a certain decision point. If a potential landmark located at a decision point is complicated to recognize, the complexity of the decision point is significantly increased. Thus, it is important to compute routes that avoid complicated decision points (CDPs) but still achieve optimal navigation performance. In this paper, we propose an approach for computing routes that avoid CDPs while optimizing the performance of landmark-based pedestrian navigation. The approach includes (1) a model for identifying CDPs based on the structures of pedestrian networks and landmark data in real scenes, and (2) a modified genetic algorithm for computing routes that avoid the identified CDPs and find the shortest route possible. To demonstrate the advantages and effectiveness of the proposed approach, we conducted an empirical study on the pedestrian network in a real-world scenario. The experimental results show that our approach can effectively avoid CDPs while still minimizing travel distance. Furthermore, our approach can provide the routes with the shortest travel distance if the distances of the routes without CDPs exceed a certain threshold.