IMOST Integrated Modeling for Safe Transportation

Goal

Building on the well-established paradigm of model-based design of embedded safety-critical systems, which has proven to facilitate early detection of design faults and thus to enhance system quality and reliability, IMoST strives for extending the scope of this design technique to also cover the human operator of such systems and his/her interaction with the system and environment. 

Traditional model-based design establishes models of the embedded system and of relevant parts of its technical environment and exploits these for an analysis of their joint dynamics. Due to the current evolution of embedded functionality from embedded control to operator assistance

systems, the overall dynamics is gradually moving towards a human-in-the-loop behavior. As the dynamics of such systems cannot be fully understood without co-modeling and co-analysis of all the agents involved, including the human operator, IMoST addresses a seamless semantic integration of the most appropriate modeling paradigms for those individual agent types. This entails detailed models of human operator behavior —both normative and erratic— in road traffic situations as well as models formalizing multiple viewpoints of embedded system dynamics, and models of the environment as perceived and partially controlled by the embedded system and the human operator. The IMoST enterprise thus involves

1. to establish valid models of human operator behavior in relevant road trafficc situations through a combination of empirical research and deductions from insights of the cognitive sciences,

2. to tightly integrate these with appropriate models of vehicle and environment dynamics and embedded system interaction,

3. so as to facilitate tools supporting full model-based validation, in particular prediction of the safety impact, of operator assistance systems. 

This is a first stepping stone towards the joint vision of the partners in the competence network SafeTRANS to address safety of transportation systems through a holistic approach integrating an engineering and a psychological perspective within a comprehensive model-based design framework. 

The project is supported by the Ministry of Science and Culture of the state of Lower Saxonia.

Persons
Publications
Integrating Anticipatory Competence into a Bayesian Driver Model

Möbus, Claus and Eilers, Mark; Proceedings of Human Modelling in Assisted Transportation (HMAT) Workshop; 006 / 2011

Predicting the Effect of Driver Assistance via Simulation

Fränzle, Martin and Gezgin, Tayfun and Hungar, Hardi and Puch, Stefan and Sauter, Gerald; Human Modelling in Assisted Transportation; 001 / 2011

Prototyping Smart Assistance with Bayesian Autonomous Driver Models

Möbus, Claus and Eilers, Mark; Handbook of Research on Ambient Intelligence and Smart Environments: Trends and Perspectives; 001 / 2011

Schätzung der TTC des rückwärtigen Verkehrs beim Einfädeln auf die Autobahn.

Steenken, R. and Lethaus, F. and Baumann, M. and Weber, L. ; 005 / 2011

Using Guided Simulation to Assess Driver Assistance Systems

Fränzle, Martin and Gezgin, Tayfun and Hungar, Hardi and Puch, Stefan and Sauter, Gerald; FORMS/FORMAT 2010; 001 / 2011

A Hierarchical Task Analysis of merging onto a freeway. - Comparison of driver’s and driver model’s task representation

Kassner, A., Baumann, M., Weber, L.; Human Modelling in Assisted Transportation; 11 / 2010

Das Einfädelverhalten in fließenden Verkehr auf der Autobahn: Der Einfluss von Lückengrößen

Steenken, R., Kassner, A., Baumann, M., Weber, L., Colonius, H.; Beiträge zur 52. Tagung experimentell arbeitender Psychologen; 003 / 2010

Effects of Situational Characteristics on Drivers' Merging into Freeway Traffic

Baumann, M., Steenken, R., Kassner, A., Weber, L., Lüdtke, A.; Human Modelling in Assisted Transportation; 11 / 2010

Learning of a Bayesian Autonomous Driver Mixture-of-Behaviors (BAD-MoB) Model

Eilers, Mark and Möbus, Claus; Advances in Applied Digital Human Modeling; 007 / 2010

Lernen eines modularen Bayesian Autonomous Driver Mixture-of-Behaviors (BAD MoB) Modells

Eilers, Mark and Möbus, Claus; 3. Berliner Fachtagung für Fahrermodellierung - Zwischen kinematischen Menschmodellen und dynamisch-kognitiven Verhaltensmodellen; 006 / 2010

Mixture of Behaviors and Levels-of-Expertise in a Bayesian Autonomous Driver Model

Möbus, Claus and Eilers, Mark; Advances in Applied Digital Human Modeling; 007 / 2010

Modeling Complex Real-time Behavior and Planning of Interventions by Counterfactual Reasoning with Bayesian Models

Möbus, Claus; Proceedings of KogWis 2010 : 10th Biannual Meeting of the German Society for Cognitive Science; 10 / 2010

Further Steps towards Driver Modelling according to the Bayesian Programming Approach

Möbus, Claus and Eilers, Mark; Digital Human Modelling, Conference Proceedings; 007 / 2009

Mixture of Behaviors in a Bayesian Driver Model

Möbus, Claus and Eilers, Mark and Zilinksi, Malte and Garbe, Hilke; Der Mensch im Mittelpunkt technischer Systeme, 8. Berliner Werkstatt, Mensch-Maschine-Systeme; 10 / 2009

Probabilistic and Empirical Grounded Modelling of Agents in (Partial) Cooperative Traffic Scenarios

Möbus, Claus and Eilers, Mark and Garbe, Hilke and Zilinksi, Malte; Digital Human Modelling, Conference Proceedings; 007 / 2009

First Steps towards Driver Modelling According to the Bayesian Programming Approach

Möbus, Claus and Eilers, Mark; Symposium Cognitive Modelling; 10 / 2008

Probabilistic and Empirical Grounded Modeling of Agents in Partial Cooperative (Traffic) Scenarios

; Workshop Proceedings Mensch & Computer 2008, DeLFI 2008 und Cognitive Design 2008; 009 / 2008

Duration

Start: 31.03.2007
End: 30.03.2010