Year: 2025
Type: article
Study design: Observational Study
Abstract: To enhance road traffic safety, this study develops a classification model to assess drivers’ tolerance of large vehicle proportions under varying road conditions. It explores how personal and socioeconomic factors influence this tolerance. Six road scenarios were designed with differences in large vehicle proportion, driving time, vehicle types and road types. Behavioural and willingness surveys collected drivers’ demographics and choices. K-means clustering segmented drivers into “low”, “medium” and “high” tolerance groups, accounting for 6.77%, 51.13% and 42.10%, respectively. Based on clustering results, an ordered logistic regression model further analysed factors influencing large vehicle tolerance. Tolerance correlated positively with household vehicle usage, annual household income, driving duration and weekly driving frequency, and negatively with urban GDP, vehicle ownership and peak congestion index, with age showing no significant effect. Additionally, linear trends were observed for urban peak congestion index, urban vehicle ownership, age and driving duration. In contrast, urban GDP, weekly driving frequency, annual household income and household vehicle usage showed curvilinear effects with gradually diminishing rates of change.
Source: PROMET - Traffic&Transportation
Authors: Hanbin WANG, Jianxiao MA, Wenyun TANG, Chenyang YANG
Institution: Nanjing Forestry University
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $970
OpenAlex ID: W4414510844
FWCI:
Cites:
Cited by:
Related to: