Multi-Agent-Based Urban Vegetation Design

Ahmed Khairadeen Ali, Hayub Song, One Jae Lee, Eun Seok Kim and Haneen Hashim Mohammed Ali
Additional contact information
Ahmed Khairadeen Ali: School of Architecture and Building Science, Chung Ang University, Seoul 06974, Korea
Hayub Song: School of Architecture and Building Science, Chung Ang University, Seoul 06974, Korea
One Jae Lee: Haenglim Architecture and Engineering Company, 201, Songpa-daero, Songpa-gu, Seoul 05854, Korea
Eun Seok Kim: School of Architecture and Building Science, Chung Ang University, Seoul 06974, Korea
Haneen Hashim Mohammed Ali: College of Agricultural Engineering, University of Duhok, Duhok 42001, Kurdistan, Iraq

IJERPH, 2020, vol. 17, issue 9, 1-21

Abstract: Urban vegetation is an essential element of the urban city pedestrian walkway. Despite city forest regulations and urban planning best practices, vegetation planning lacks clear comprehension and compatibility with other urban elements surrounding it. Urban planners and academic researchers currently devote vital attention to include most of the urban elements and their impact on the occupants and the environment in the planning stage of urban development. With the advancement in computational design, they have developed various algorithms to generate design alternatives and measure their impact on the environment that meets occupants’ needs and perceptions of their city. In particular, multi-agent-based simulations show great promise in developing rule compliance with urban vegetation design tools. This paper proposed an automatic urban vegetation city rule compliance approach for pedestrian pathway vegetation, leveraging multi-agent system and algorithmic modeling tools. This approach comprises three modules: rule compliance (T-Rule), street vegetation design tool (T-Design), and multi-agent alternative generation (T-Agent). Notably, the scope of the paper is limited to trees, shrubbery, and seating area configurations in the urban pathway context. To validate the developed design tool, a case study was tested, and the vegetation design tool generated the expected results successfully. A questionnaire was conducted to give feedback on the use of the developed tool for enhancing positive experience of the developed tool. It is anticipated that the proposed tool has the potential to aid urban planners in decision-making and develop more practical vegetation planting plans compared with the conventional Two-Dimensional (2D) plans, and give the city occupants the chance to take part in shaping their city by merely selecting from predefined parameters in a user interface to generate their neighborhood pathway vegetation plans. Moreover, this approach can be extended to be embedded in an interactive map where city occupants can shape their neighborhood greenery and give feedback to urban planners for decision-making.

Keywords: multi-agent system; visual algorithm; urban vegetation design; automatic modeling; computational design (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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