journal article·2021-07-28Open access

Physarum-Inspired Bicycle Lane Network Design in a Congested Megacity

M. A. H. Akhand, Md. Ahsan Habib, Md Abdus Samad Kamal, Nazmul Siddique

Applied Sciences· Volume 11· Issue 15

Abstract

Improvement of mobility, especially environment-friendly green mobility, is challenging in existing megacities due to road network complexity and space constraints. Endorsing the bicycle lane network (BLN) in congested megacities is a promising option to foster green mobility. This research presents a novel bioinspired network design method that considers various constraints and preferences related to the megacity for designing an optimal BLN. The proposed method is inspired by natural Physarum polycephalum, a brainless, multi-headed single-celled organism, which is capable of developing a reticulated network of complex foraging behaviors in pursuit of food. The mathematical model of Physarum foraging behavior is adapted to maneuver various BLN constraints in megacity contexts in designing the optimal BLN. The Physarum-inspired BLN method is applied to two case studies on the megacity Dhaka for designing BLNs: the first one covers congested central city area, and the second one covers a broader area that includes major locations of the city. The obtained BLNs were evaluated comparing their available routes between different locations with the existing vehicle routes of the city in terms of distance and required travel times in different time periods, and the BLN routes were found to be suitable alternatives for avoiding congested main roads. The expected travel time using BLNs is shorter than other transport (e.g., car and public bus); additionally, at glance, the average travel speed on BLNs is almost double that of public buses in peak hours. Finally, the designed BLNs are promising for environment-friendly and healthy mobility.
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Research context

OpenAlex topics: Slime Mold and Myxomycetes Research · Biocrusts and Microbial Ecology · Plant and Biological Electrophysiology Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh

Graduate School of Science and Technology, Gunma University, Kiryu 376-8515, Japan

School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry BT48 7JL, UK

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