OOIR: Observatory of International Research

Papers

(The H4-Index of Transportation Research Part F-Traffic Psychology and Behaviour is 32. 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 2020-10-01 to 2024-10-01.)

Article	Citations
Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries	128
Exploring expert perceptions about the cyber security and privacy of Connected and Autonomous Vehicles: A thematic analysis approach	95
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 Innovat	75
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 travel	62
Factors of acceptability, acceptance and usage for non-rail autonomous public transport vehicles: A systematic literature review	58
Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists	57
Exploratory factor analysis in transportation research: Current practices and recommendations	56
The motivations for using bike sharing during the COVID-19 pandemic: Insights from Lisbon	56
Driver behaviour and traffic accident involvement among professional urban bus drivers in China	53
Autonomous buses: Intentions to use, passenger experiences, and suggestions for improvement	53
Perceived risk of using shared mobility services during the COVID-19 pandemic	52
Modeling dispositional and initial learned trust in automated vehicles with predictability and explainability	49
Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks	48
This is not me! Technology-identity concerns in consumers’ acceptance of autonomous vehicle technology	48
Overall performance impairment and crash risk due to distracted driving: A comprehensive analysis using structural equation modelling	47
Trust and intention to use autonomous vehicles: Manufacturer focus and passenger control	44
An observational study on the risk behaviors of electric bicycle riders performing meal delivery at urban intersections in China	44
Intention of Chinese college students to use carsharing: An application of the theory of planned behavior	43
Antecedents of consumer loyalty in ride-hailing	43
Risky riding behaviours among motorcyclists in Malaysia: A roadside survey	42
Car-following behavioural adaptation when driving next to automated vehicles on a dedicated lane on motorways: A driving simulator study in the Netherlands	39
Modeling the influence of mobile phone use distraction on pedestrian reaction times to green signals: A multilevel mixed-effects parametric survival model	38
Eliciting attitudinal factors affecting the continuance use of E-scooters: An empirical study in Chicago	38
The impact of a dedicated lane for connected and automated vehicles on the behaviour of drivers of manual vehicles	37
Developing human-machine trust: Impacts of prior instruction and automation failure on driver trust in partially automated vehicles	37

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers	36
Assessing the feasibility of the theory of planned behaviour in predicting drivers’ intentions to operate conditional and full automated vehicles	34
Identifying the determinants and understanding their effect on the perception of safety, security, and comfort by pedestrians and cyclists: A systematic review	34
An empirical investigation into carpooling behaviour for sustainability	33
Public acceptance of connected vehicles: An extension of the technology acceptance model	33
Assessing the effect of long-automated driving operation, repeated take-over requests, and driver’s characteristics on commercial motor vehicle drivers’ driving behavior and reaction time in highly au	32
Exploration of the effects of task-related fatigue on eye-motion features and its value in improving driver fatigue-related technology	32
Behavioral adaptations of human drivers interacting with automated vehicles	32
Exploring the benefits of conversing with a digital voice assistant during automated driving: A parametric duration model of takeover time	32
Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles	32