Guide them through: an automatic crowd control framework using multi-objective genetic programming
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 920
- Type
- D - Journal article
- DOI
-
10.1016/j.asoc.2018.01.037
- Title of journal
- Applied Soft Computing
- Article number
- -
- First page
- 90
- Volume
- 66
- Issue
- -
- ISSN
- 1568-4946
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
http://eprints.mdx.ac.uk/23685/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- An automatic crowd control framework based on multi-objective optimisation of strategy space using genetic programming is proposed. Previous work focuses on investigating how a crowd will respond to and evolve into the given environment configuration and crowd composition, but there is little effort on how to automatically generate crowd control strategies. This paper is significant because the proposed framework is capable of generating control strategies that guide the individuals on when and where to slow down for optimal overall crowd flow in realtime, quantitatively measured by multiple objectives such as shorter travel time and less congestion along the path.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -