Development of Models for Children—Pedestrian Crossing Speed at Signalized Crosswalks

Irena Ištoka Otković, Aleksandra Deluka-Tibljaš, Sanja Šurdonja and Tiziana Campisi
Additional contact information
Irena Ištoka Otković: Faculty of Civil Engineering and Architecture Osijek, Josip Juraj Strossmayer University of Osijek, 31 000 Osijek, Croatia
Aleksandra Deluka-Tibljaš: Faculty of Civil Engineering, University of Rijeka, 51 000 Rijeka, Croatia
Sanja Šurdonja: Faculty of Civil Engineering, University of Rijeka, 51 000 Rijeka, Croatia
Tiziana Campisi: Faculty of Engineering and Architecture, University of Enna KORE, 94100 Enna, Italy

Sustainability, 2021, vol. 13, issue 2, 1-18

Abstract: Modeling the behavior of pedestrians is an important tool in the analysis of their behavior and consequently ensuring the safety of pedestrian traffic. Children pedestrians show specific traffic behavior which is related to cognitive development, and the parameters that affect their traffic behavior are very different. The aim of this paper is to develop a model of the children-pedestrian’s speed at a signalized pedestrian crosswalk. For the same set of data collected in the city of Osijek—Croatia, two models were developed based on neural network and multiple linear regression. In both cases the models are based on 300 data of measured children speed at signalized pedestrian crosswalks on primary city roads located near a primary school. As parameters, both models include the selected traffic infrastructure features and children’s characteristics and their movements. The models are validated on data collected on the same type of pedestrian crosswalks, using the same methodology in two other urban environments—the city of Rijeka, Croatia and Enna in Italy. It was shown that the neural network model, developed for Osijek, can be applied with sufficient reliability to the other two cities, while the multiple linear regression model is applicable with relatively satisfactory reliability only in Rijeka. A comparative analysis of the statistical indicators of reliability of these two models showed that better results are achieved by the neural network model.

Keywords: pedestrian children; pedestrian crossing speed; field measurements; prediction models; neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/2/777/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/2/777/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:2:p:777-:d:480593

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().