Pregled bibliografske jedinice broj: 1104326
Development of Models for Children—Pedestrian Crossing Speed at Signalized Crosswalks
Development of Models for Children—Pedestrian Crossing Speed at Signalized Crosswalks // Sustainability, 13 (2021), 2; 1057995, 18 doi:10.3390/su13020777 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1104326 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Development of Models for Children—Pedestrian
Crossing Speed at Signalized Crosswalks
Autori
Ištoka Otković, Irena ; Deluka-Tibljaš, Aleksandra ; Šurdonja, Sanja ; Campisi, Tiziana
Izvornik
Sustainability (2071-1050) 13
(2021), 2;
1057995, 18
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
pedestrian children ; pedestrian crossing speed ; field measurements ; prediction models ; neural network
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo
POVEZANOST RADA
Ustanove:
Građevinski fakultet, Rijeka,
Građevinski i arhitektonski fakultet Osijek
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus