ESR12 – AV Occupants’ Perception of Safety in relation to AV behaviour

Popular scientific abstract

Vehicle automation has been identified as a game-changer in fields of vehicle and transportation, with substantial mobility and safety potentials. The theories and technologies that are related to perception, planning and control have gained considerable development. However, the interaction between the automation and users, and the user’s reaction to the automation are still not considered sufficiently. For instance, we don’t know to what extent is the automation reliable and will we feel safe in a driving automation. That leads to some unwanted consequences, such as undertrust and disuse of some automated driving systems, overtrust and misuse of some driving assistance systems. That is why we often hear the accidents about a driving automation.

Under the framework of SHAPE-IT to facilitate the safe, acceptable, integration of user-centered and transparent automated vehicles into tomorrow’s mixed urban traffic environments. I, as ESR12, will solve the problems that how to make users trust the driving automation and how to make users feel safe in an automated vehicle. I need to know how user’s perceived safety and trust work in automated vehicles. Then, try to improve the driving style of automation to enhance driver’s perceived safety and trust. Mathematical model is a good way to describe perceived safety and trust in vehicle automation. Driving simulator and on-road experiments will be performed to research what factors can affect perceived safety and trust, additionally to obtain the model parameters. Furthermore, I will investigate how perceived safety and trust can be enhanced by adapting the automated driving style. The expected results of my research would come from three aspects. Firstly, the methods to develop natural, trusted, and accepted interactions between automated vehicles and the users inside. Secondly, the model of perceived safety. Lastly, the recommendations for human-automated vehicle interaction design, to facilitate them being perceived as safe.

My affiliation

Contact details to my supervisors:

Riender Happee (Supervisor 1):

Meng Wang (Supervisor 2):


Trust is a vital factor that determines user’s willingness to use and rely on the automated systems [1]. Therefore, many researchers tried to explain and model trust, which can give insights into the interaction design in automated vehicles. However, many trust models are conceptual models [2], [3]. For the measurement of trust, although questionnaire is the most popular measurement of trust, it is not realistic to use questionnaire to obtain on-road driver’s trust level in real time. Therefore, surrogate measures need to be created to obtain driver’s subjective feelings in real time.

Perceived safety is a psychological item which has a close relationship with trust, being pivotal for the user’s acceptance of automated vehicles. It captures the subjective evaluation of safety by users of automated driving systems but also by other road users interacting with automated vehicles. The models from the existing researches are similarly conceptual ones and are always combined with trust models in some driver acceptance model of automated driving systems [4]–[6]. Consequently, building a mathematical model of perceived safety to predict driver’s perceived safety in real time is also necessary. 

These existing researches can only provide a basis concept of perceived safety and trust. Some others built effective metrics for perceived safety but need further research to confirm real-time capability [7]. In addition, how to explain the relationship between perceived safety and trust and how to enhance perceived safety and keep trust in an appropriate level still need further research and experiments.

I am Xiaolin He,  a master of engineering from China. The topic of my master is human adaptive design of ADAS. Before I started SHAPE-IT project, I was an engineer in SAIC Volkswagen engaging in driving automation development. My knowledge on human adaptive design and driving automation will help a lot with this project.

Aims and objectives

There are currently 4 overall objectives of my ESR-project

  1. To find out which factors determine perceived safety and trust and to what extent they affect perceived safety and trust.
  2. To model perceived safety and trust. The model can be used to design automated driving styles.
  3. To explain the relationship between perceived safety and trust.

To adapt the driving style or control the movements of the vehicle to enhance perceived safety and trust.

Research description

The general goal of my research is to study perceived safety and trust in automated vehicles considering their modelling, their relationship between each other and the enhancement. Some new models and methods are going to be created and control theories are likely to be used to adapt the driving style of the automation in order to enhance the perceived safety and trust. The following approaches would be used to fulfill the aims.

  • Literature review

In this phase, survey of literature will be conducted to have a better understanding of perceived safety and trust on the determinants and the modelling method. After the literature review, the factors which determine perceived safety and trust can be basically found. Meanwhile, I can lean some effective ways to obtain drivers perceived safety and trust.

  • Experiment on the simulator for the data collection

After some determinants are basically found, experiment on the simulator would be designed and conducted to find out and validate the factors which have an influence on perceived safety and trust. I need to design the scenarios, collect some data from the vehicle, other road users and the users inside the automated vehicle. Then, based on the experiment control and analysis of the data, the factors can be found.

  • Modelling of perceived safety and trust including indicator selection, mathematical modelling and calibration of the model on driving simulator

At this stage, based on some models of functional safety, models of perceived safety and trust will be built with the subjective feelings of drivers. Then, simulator experiment will be conducted again to calibrate the model.

  • Adapting the driving style by controlling the movements of the automated vehicle to enhance perceived safety and trust based on the model.

Based on the mathematical model of perceived safety and trust, the mechanism of perceived safety and trust will be explained well. Therefore, we can get the optimized movements which can be implemented to the controller. Then, a higher perceived safety and trust level will be built.

  • On -road experiment and simulator and to calibrate and validate the adaptive design for Level 2 and Level 4 separately.

Simulator experiment will be conducted to calibrate and validate the effectiveness of adaptive for Level 4. Then, the design from simulator will be transferred to vehicle to validate the effectiveness of adaptive design in real world for Level 2.


The expected results of my research are as following:

  • Publications (journal papers, conference papers, dissertation thesis)
  • Model of perceived safety and trust
  • Methodology for the adaptive design of automated vehicle in order to get a higher level of perceived safety and trust.
  • Open datasets and codes

My publications

To come…

References and links

[1]          J. K. Choi and Y. G. Ji, “Investigating the Importance of Trust on Adopting an Autonomous Vehicle,” Int. J. Hum. Comput. Interact., vol. 31, no. 10, pp. 692–702, 2015, doi: 10.1080/10447318.2015.1070549.

[2]          K. A. Hoff and M. Bashir, “Trust in automation: Integrating empirical evidence on factors that influence trust,” Hum. Factors, vol. 57, no. 3, pp. 407–434, 2015, doi: 10.1177/0018720814547570.

[3]          Frederick Steinke, Tobias Fritsch, and Lina Silbermann, “A Systematic Review of Trust in Automation and Assistance Systems for Older Persons’ Overall Requirements,” eTELEMED 2012, Fourth Int. Conf. eHealth, Telemedicine, Soc. Med., no. c, pp. 155–163, 2012.

[4]          K. Garidis, L. Ulbricht, A. Rossmann, and M. Schmäh, “Toward a User Acceptance Model of Autonomous Driving,” vol. 3, pp. 1381–1390, 2020.

[5]          Z. Xu, K. Zhang, H. Min, Z. Wang, X. Zhao, and P. Liu, “What drives people to accept automated vehicles? Findings from a field experiment,” Transp. Res. Part C Emerg. Technol., vol. 95, no. February, pp. 320–334, 2018, doi: 10.1016/j.trc.2018.07.024.

[6]          J. C. Zoellick, A. Kuhlmey, L. Schenk, D. Schindel, and S. Blüher, “Amused, accepted, and used? Attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention,” Transp. Res. Part F Traffic Psychol. Behav., vol. 65, pp. 68–78, 2019, doi: 10.1016/j.trf.2019.07.009.

[7]          F. A. Mullakkal-Babu, “Modelling Safety Impacts of Automated Driving Systems in Multi-Lane Traffic,” Delft University of Technology, 2020.