Modeling urban resident travel satisfaction during the morning and the evening peak hours: A case study in Beijing

Understanding how various factors influence travel satisfaction can assist in traffic policy-making. In the study, it is aimed to develop innovative urban resident travel satisfaction evaluation models by building a comprehensive travel satisfaction evaluation index system and considering the asymmetric traffic flow and difference in travel time urgency during the morning and evening peak hours. Both the internal factors reflecting resident-related characteristics including socio-economic attributes and travel characteristics, and the external factors reflecting road-related characteristics including traffic facilities, road traffic conditions, traffic environments, and service levels are considered. Then, for the morning and evening peak hours, a structural equation model (SEM) to capture the intrinsic interactions between latent factors, and an ordered logit model (OLM) to describe the direct influencing factors of travel satisfaction considering its ordered nature are built respectively. Finally, the proposed models are examined with the travel survey data collected in the Yizhuang district of Beijing, China. The numerical results show that both the internal and external factors have significant impacts on travel satisfaction. The SEM models capture the interactions between latent variables such as the positive relation between traffic facilities and traffic environments. The OLM results show that most external factors except the satisfaction of the road obstacles have positive influences on travel satisfaction. The research findings provide a better understanding of the intrinsic interactions between latent variables and direct influencing factors of travel satisfaction and put forward guidance on how to improve travel satisfaction.