TY - GEN
T1 - Improving the Urban Accessibility of Older Pedestrians using Multi-objective Optimization
AU - Delgado-Enales, Inigo
AU - Molina-Costa, Patricia
AU - Osaba, Eneko
AU - Urra-Uriarte, Silvia
AU - Del Ser, Javier
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Many countries around the world have witnessed the progressive ageing of their population, giving rise to a global concern to respond to the needs that this process will create. Besides the changes in the productive schemes and the evolution of the healthcare resources to new models, the accessibility of pedestrians belonging to this age range is grasping an increasing interest in urban planning processes. This work presents pre-liminary results of a framework that combines graph modeling and meta-heuristic optimization to inform decision makers in urban planning when deciding how to regenerate urban spaces taking into account pedestrian accessibility for the older people in urban areas with difficult orography. The goal of the framework is to decide where to deploy urban elements (mechanical ramps, escalators and lifts), so that an indirect measure of accessibility is improved while also accounting for the economical investment of the installation. We exploit the versatility of multi-objective evolutionary algorithms to tackle the underlying optimization problem. Experimental results of a case study located in the city of Santander (Spain) show that the proposed framework can support urban planners when making decisions regarding the accessibility of the public space.
AB - Many countries around the world have witnessed the progressive ageing of their population, giving rise to a global concern to respond to the needs that this process will create. Besides the changes in the productive schemes and the evolution of the healthcare resources to new models, the accessibility of pedestrians belonging to this age range is grasping an increasing interest in urban planning processes. This work presents pre-liminary results of a framework that combines graph modeling and meta-heuristic optimization to inform decision makers in urban planning when deciding how to regenerate urban spaces taking into account pedestrian accessibility for the older people in urban areas with difficult orography. The goal of the framework is to decide where to deploy urban elements (mechanical ramps, escalators and lifts), so that an indirect measure of accessibility is improved while also accounting for the economical investment of the installation. We exploit the versatility of multi-objective evolutionary algorithms to tackle the underlying optimization problem. Experimental results of a case study located in the city of Santander (Spain) show that the proposed framework can support urban planners when making decisions regarding the accessibility of the public space.
KW - Urban planning
KW - com-binatorial optimization
KW - multi-objective evolutionary algorithms
KW - pedestrian accessibility
UR - http://www.scopus.com/inward/record.url?scp=85138743782&partnerID=8YFLogxK
U2 - 10.1109/CEC55065.2022.9870432
DO - 10.1109/CEC55065.2022.9870432
M3 - Conference contribution
AN - SCOPUS:85138743782
T3 - 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
BT - 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Congress on Evolutionary Computation, CEC 2022
Y2 - 18 July 2022 through 23 July 2022
ER -