A computational model of the car driver interfaced with a simulation platform for future Virtual Human Centred Design applications: COSMO-SIVIC

Bellet, Thierry; Mayenobe, Pierre; Bornard, Jean-Charles; Gruyer, Dominique; Claverie, Bernard

doi:10.1016/j.engappai.2012.05.010

Cited by 12 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The perceived information is matched to existing driving knowledge (driving schemata and envelop zones) to determine future actions that meet the tactical goal of the activated driving schema [182]. In combination with Pro-SiVIC, a vehicle-environment-sensors platform, COSMOD-RIVE was used to develop a Virtual Human Centered Design (V-HCD) platform [181], [183]. V-HCD is potentially a perfect candidate for ADAS or HAD testing, due to the driver modelling on one side and the realistic sensor-vehicle simulation on the other.…”

Section: A Driver Behavior Modulesmentioning

confidence: 99%

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

Siebke

Mai

Prokop

2022

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

Will Advanced Driving Assistance Systems (ADAS) and Highly Automated Driving (HAD) perform in the expected manner? Will they actually make road traffic safer, or will they potentially introduce new critical situations or road accidents? It is almost impossible to address these questions solely through real-world tests. A promising tool to provide appropriate answers in a time-and cost-efficient way without exposing subjects to risk are virtual assessment methods. Reliable safety assessments are only possible, if the traffic simulations provide realistic traffic, including critical situations and road accidents. This paper provides a review of how human error contributes to critical situations and accidents in road traffic. The focus is on the causes and mechanisms of human error, which driver behavior models must address in order to simulate realistic traffic. For this purpose, Rasmussen's error taxonomies are applied to the traffic context and extended with further research. The paper shows the causes of those human errors and that the underlying mechanisms thereof should be taken into account in order to obtain more transparent and realistic driver behavior models. It is shown, which concepts for modelling realistic traffic exist and how virtual safety assessment could benefit from this development. In addition, the driver behavior model DReaM (Driver Reaction Model) is presented to address the issues resulting from existing cognitive driver models.

show abstract

Section: A Driver Behavior Modulesmentioning

confidence: 99%

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

Siebke

Mai

Prokop

2022

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

show abstract

“…Previous attempts have been made to computationally model situational awareness (see e.g. [3,39,64]). Our approach to modeling situational awareness is unique in that we try to explicitly estimate the parts of the visual scene to which a person has attended using a spatio-temporal model for gaze and scene understanding.…”

Section: Related Workmentioning

confidence: 99%

MAAD: A Model and Dataset for "Attended Awareness" in Driving

Gopinath¹,

Rosman²,

Stent³

et al. 2021

Preprint

View full text Add to dashboard Cite

We propose a computational model to estimate a person's attended awareness of their environment. We define "attended awareness" to be those parts of a potentially dynamic scene which a person has attended to in recent history and which they are still likely to be physically aware of. Our model takes as input scene information in the form of a video and noisy gaze estimates, and outputs visual saliency, a refined gaze estimate and an estimate of the person's attended awareness. In order to test our model, we capture a new dataset with a high-precision gaze tracker including 24.5 hours of gaze sequences from 23 subjects attending to videos of driving scenes. The dataset also contains thirdparty annotations of the subjects' attended awareness based on observations of their scan path. Our results show that our model is able to reasonably estimate attended awareness in a controlled setting, and in the future could potentially be extended to real egocentric driving data to help enable more effective ahead-of-time warnings in safety systems and thereby augment driver performance. We also demonstrate our model's effectiveness on the tasks of saliency, gaze calibration and denoising, using both our dataset and an existing saliency dataset. We make our model and dataset available at https://github.com/ToyotaResearchInstitute/att-aware/.

show abstract

“…With a view to better understand and integrate users' needs in the design of innovative advanced driving aid systems (ADAS), IFSTTAR and ESI Group jointly developed a virtual human-centred design platform; the V-HCD (Bellet et al, 2012(Bellet et al, , 2018. As a virtual simulation toolbox, the V-HCD is able to handle human-based simulation, that is to say based on a virtual driver model, to virtually assess accident risks as well as the potential benefits of future ADAS.…”

Section: Design and Development Of A V-hcd Platformmentioning

confidence: 99%

Development of an Immersive Simulation Platform to Study Interactions between Automated Vehicles and Pedestrians

Lévêque

Bellet

Bornard

et al. 2020

Proceedings of the 4th International Conference on Computer-Human Interaction Research and Applications

Self Cite

View full text Add to dashboard Cite

A computational model of the car driver interfaced with a simulation platform for future Virtual Human Centred Design applications: COSMO-SIVIC

Cited by 12 publications

References 11 publications

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

What Do Traffic Simulations Have to Provide for Virtual Road Safety Assessment? Human Error Modeling in Traffic Simulations

MAAD: A Model and Dataset for "Attended Awareness" in Driving

Development of an Immersive Simulation Platform to Study Interactions between Automated Vehicles and Pedestrians

Contact Info

Product

Resources

About