Popular scientific abstract
Automated vehicles (AV) will be applied on urban transport and share the space with traditional vehicles with the benefit of reducing the car crashes caused by the human error, harmful emissions and congestion. Similar to all the technology’s emerging period, the miscellaneous considerations from the users are consequent unwound to evaluate and improve the technology based on their user experience, behaviors adaptation, receptivity and trust. As the increase of AV on road, the vulnerable road users (VRU), including pedestrian, cyclist, motorcyclist and the user of scooter are exposed to the unfamiliar traffic environment than ever when they have to adapt the increase of AV on road, will this adaptation developing as time goes or what facilitates their intentions to adapt? Are they truly trust the AV technology or will the trust enhanced with the repeated exposure or improved technology? Will their overall experience change as the repetitive interactions with AV or what influence that experience? Are these results are diverse based on the personality, social status, demographic and other factors? Conversely, by figuring out these questions, the engineers will have the cues to improve the AV with practical feedbacks on road with safety and better performance.
Meanwhile, in conventional traffic scenarios, determinations such “yield or not ”or “who go first” are operated by implicit negotiations between road users and drivers, when pedestrians can refer to the eye contacts and gestures from the drivers. However, with the control taken over from driver to automation functions, the pedestrians are deprived of these cues to communicate with the vehicles leading to an ambiguous even risky crossing experience. Therefore, studying how the interactions between AV/VRU contribute to the design of more functionable, reliable and acceptable external AV interfaces to communicate their intent to road users thus ensuring safety in the mixed urban traffic environment of tomorrow.
Overall, I will investigate the interactions between VRU and AV and the long-term effects such as experience, adoption and trust as well as its relation to the AV eHMI design strategies to accelerate the future AV technology and extensive use.
My affiliation
My host university is University of Leeds.
Contacts of supervisors:
Prof Natasha Merat (Leeds) : N.Merat@its.leeds.ac.uk
Prof Klaus Bengler (TUM) : bengler@tum.de
Dr Yee Mun Lee (Leeds) : Y.M.Lee@leeds.ac.uk
Background
Existing research on new technology focuses on the behavioral intention to use a technology (BI) as a measure of acceptance and seeks to identify influencing factors as the predictors of BI. Researchers have proposed various conceptual modal of technology acceptance such as Theory of Reasoned Action (TRA) model (Fisbein and Ajzen, 1975), Theory of Planned Behavior (TPB) model (Ajzen,1991), Unified Theory of Acceptance and Use of Technology (UTAUT) model (Venkatesh et al. ,2003), with the influential factors of effort expectancy, performance expectancy, social influence and facilitating conditions to predict the intention (Fisbein and Ajzen, 1975; Ajzen,1991; Venkatesh et al. ,2003). With the introduction of AV system, the specific acceptance models are introduced with additional factors of anxiety, perceived safety, attitude towards new technology and fun in the Car Technology Acceptance Model (CTAM) (Osswald et al.,2012) and Automation Acceptance Model (AAM)( Ghazizadeh et al.,2012). Most factors and studies are based on surveys or interviews based on text other than the real world experience when their perceptions and responses are guided by the description provided by the text sources (Rahman et al.,2017). To better investigate the acceptance of VRU towards AV, my research will conduct field experiments make use of the facility in HIKER lab in University of Leeds to validate these models and evaluate the most functioning factors in real case. Meanwhile, the current studies provide the static overview of the results from the observation or studies, my study will focus more on a dynamic and longer-terms effects.
Similarly, the possible effects that can be researched within the interactions between VRU/AV are receptivity and trust. Following the same research process of conducting literature reviews, comparing the existing conceptual modal, evaluating relevant factors and designing empire experiments to validate the results.
Aims and objectives
Aims:
The aim of this PhD projects is a) to train the Marie Curie PhD the complementary skills in collaboration and methods regarding the human factors in AV area as well as in industrial field study, and b)systematical outcomes of interactions between AV/VRU with the overall experience, adoption and trust modal in long-term exposure.
Objectives:
- To understand how VRUs’ experience, trust, and acceptance of AVs change with long-term/repeated exposure to AVs in urban traffic;
- Determine whether these effects are influenced by user characteristics such as gender, age and personality;
- Evaluate the influence of AV eHMI design strategy on VRUs’ experience, trust, and acceptance after their long-term/repeated exposure to AV;
Research description
- Conducting a wide range of literature reviews on current work to know the state-of-the-art of the AV interfaces, AV/VRU interactions, behavior adaptation, conceptual modal of each effect, and method to investigate long-term exposure;
- Designing the experiments making use of the facility of HIKER lab in the University of Leeds, to get the authentic data within the interactions between AV/VRU;
- Analyzing data from empirical studies for validated conclusions;
- Corporation with other ESR, especially with ESR9 to study the insights into the impact of AV eHMI design strategy on the long-term effects of VRUs on experience, trust, and acceptance and with ESR2 and ESR9 to know how VRUs’ over-trust may lead to inappropriate VRU/AV interaction behaviors.
Results
Expected results:
- Patterns of learning strategies of VRUs exposed to AVs in urban traffic, by user type;
- Insights into the impact of AV eHMI design strategy on the long-term effects of VRUs on experience, trust, and acceptance;
- Consider how VRUs’ over-trust may lead to inappropriate VRU/AV interaction behaviour;
My publications
Journals
Kalantari, A. H., Yang, Y., de Pedro, J. G., Lee, Y. M., Horrobin, A., Solernou, A., … & Markkula, G. (2023). Who goes first? A distributed simulator study of vehicle–pedestrian interaction. Accident Analysis & Prevention, 186, 107050. https://doi.org/10.1016/j.aap.2023.107050
Markkula, G., Lin, Y., yslin, Srinivasan, A. R., Billington, J., Leonetti, M., Kalantari, A. H., Yang, Y.,… Merat, N. (2022, June 8). Explaining human interactions on the road requires large-scale integration of psychological theory. https://doi.org/10.31234/osf.io/hdxbs
Kalantari, A.H., Yang, Y., Merat, N., & Markkula, G. (2023, March 17). Modelling vehicle-pedestrian interactions at unsignalised locations: Road users may not play the Nash equilibrium. https://doi.org/10.31234/osf.io/axseu (Preprint)
Conference / Posters
Yang, Y., Lee, Y. M., Merat, N. (2022). Pedestrians’ head movements when encountering automated cars.In 7th International Conference on Traffic and Transport Psychology, Gothenburg, Sweden.
Yang, Y., Lee, Y. M., Kalantari, A. H.,de Pedro, J. G., Horrobin, A., Daly, M., Solernou, A., Markkula, G., Merat, N. (2023). The effect of different infrastructures on driver response to a crossing pedestrian: a distributed simulation study. In Proceedings of the driving simulation conference. Antibes, France (Preprint).
Kalantari, A. H., Yang, Y., de Pedro, J. G., Lee, Y. M., Horrobin, A., Solernou, A., … & Markkula, G. (August, 2023). A distributed simulator study of car-pedestrian interaction. In 7th International Conference on Traffic and Transport Psychology, Gothenburg, Sweden.
Zhang, C., Kalantari, A.H., Yang, Y., Ni, Z., Markkula, G., Merat, N. (2023). Cross or Wait? Predicting Pedestrian Interaction Outcomes at Unsignalized Crossings. https://doi.org/10.48550/arXiv.2304.08260
SHAPE-IT Deliverables
Figalová, N., Mbelekani, N.Y., Zhang, C., Yang, Y., Peng, C., Nasser, M., Yuan-Cheng, L., Pir Muhammad, A., Tabone, W., Berge, S. H., Jokhio, S., He, X., Hossein Kalantari, A., Mohammadi, A., & Yang, X. (2021). SHAPE-IT Deliverable 1.1: Methodological framework for modelling and empirical approaches.https://doi.org/10.17196/shape-it/2021/02/D1.1
Merat, N., Yang, Y., Lee, Y. M., Berge, S. H., Figalová, N., Jokhio, S., Peng, C., Mbelekani, N.Y., Nasser, M., Pir Muhammad, A., Tabone, W., Yuan-Cheng, L., & Bärgman, J. (2021). SHAPE-IT Deliverable 2.2: An overview of interfaces for automated vehicles (inside/outside). https://doi.org/10.17196/shape-it/2021/02/D2.1
References and links
Ajzen, I., 1991. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50 (2), 179–211.
Ghazizadeh, M., Peng, Y., Lee, J.D., Boyle, L.N., 2012. Augmenting the technology acceptance model with trust: commercial drivers’ attitudes towards monitoring and feedback. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 56, no. 1. Sage Publications, Sage CA: Los Angeles, CA, pp. 2286–2290.
Osswald, S., Wurhofer, D., Trösterer, S., Beck, E., Tscheligi, M., 2012. Predicting information technology usage in the car: towards a car technology acceptance model. In: Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. ACM, pp. 51–58.
Rahman, M.M., Lesch, M.F., Horrey, W.J., Strawderman, L., 2017. Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accid. Anal. Prev. 108, 361–373.
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D., 2003. User acceptance of information technology: toward a unified view. MIS Quart. 27 (3), 425–478.
Who am I ?
I am Yue Yang, and as the ESR 4 in the SHAPE-IT project, I work at the Institute for Transport Studies, University of Leeds.
My primary research interests lie in the human – vehicle interactions, with a specific focus on the development of proper kinematics and eHMI for future automated vehicles to enhance safe and smooth interaction with the external road participants.
I received the BEng. in Automation and Control Science, Harbin Institute of Technology (HIT), China. After it, I read for an MSc and obtained the double degree in Human Computer Interaction and Design from Kungliga Tekniska Högskolan (KTH), Sweden and Aalto University, Finland, during this period, I also completed a minor track in the Innovation & Entrepreneurship from EIT Digital Master and Business School.