Transportation Research Part F-Traffic Psychology and Behaviour

Papers
(The H4-Index of Transportation Research Part F-Traffic Psychology and Behaviour is 34. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries109
Public perception of autonomous vehicles: A qualitative study based on interviews after riding an autonomous shuttle94
Attitudes towards privately-owned and shared autonomous vehicles92
Mobility as a service and sustainable travel behaviour: A thematic analysis study89
Revealing psychological inertia in mode shift behavior and its quantitative influences on commuting trips79
Examining human attitudes toward shared mobility options and autonomous vehicles76
Exploring expert perceptions about the cyber security and privacy of Connected and Autonomous Vehicles: A thematic analysis approach74
Modelling the acceptance of fully autonomous vehicles: A media-based perception and adoption model70
How gender differences and perceptions of safety shape urban mobility in Southeast Asia68
Effects of explanation types and perceived risk on trust in autonomous vehicles65
A structural equation modeling approach for the acceptance of driverless automated shuttles based on constructs from the Unified Theory of Acceptance and Use of Technology and the Diffusion of Innovat63
How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors50
Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists46
Perceived risk of using shared mobility services during the COVID-19 pandemic46
Exploratory factor analysis in transportation research: Current practices and recommendations46
The motivations for using bike sharing during the COVID-19 pandemic: Insights from Lisbon46
Driver behaviour and traffic accident involvement among professional urban bus drivers in China45
Modelling the influence of time pressure on reaction time of drivers45
Overall performance impairment and crash risk due to distracted driving: A comprehensive analysis using structural equation modelling44
Modeling dispositional and initial learned trust in automated vehicles with predictability and explainability44
Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks43
The Long-Term effects of COVID-19 on travel behavior in the United States: A panel study on work from home, mode choice, online shopping, and air travel43
Factors of acceptability, acceptance and usage for non-rail autonomous public transport vehicles: A systematic literature review43
This is not me! Technology-identity concerns in consumers’ acceptance of autonomous vehicle technology43
Modeling the interaction between vehicle yielding and pedestrian crossing behavior at unsignalized midblock crosswalks42
Buying an electric car: A rational choice or a norm-directed behavior?40
An international survey on the incidence and modulating factors of carsickness38
Autonomous buses: Intentions to use, passenger experiences, and suggestions for improvement38
A perception-based cognitive map of the pedestrian perceived quality of service on urban sidewalks38
An observational study on the risk behaviors of electric bicycle riders performing meal delivery at urban intersections in China37
Trust and intention to use autonomous vehicles: Manufacturer focus and passenger control37
Differences in parental perceptions of walking and cycling to high school according to distance35
Influence of values, attitudes towards transport modes and companions on travel behavior35
Intention of Chinese college students to use carsharing: An application of the theory of planned behavior34
Car-following behavioural adaptation when driving next to automated vehicles on a dedicated lane on motorways: A driving simulator study in the Netherlands34
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