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Table of contents
1 Introduction
1.1 Automated driving vehicles in society
1.1.1 A note on terminology
1.1.2 History
1.1.3 Current research status
1.2 Motivation of the thesis
1.3 Contributions of the thesis
1.4 Structure of the document
2 State of the Art
2.1 Decision Making
2.1.1 Related works
2.2 Ethical decision-making
2.2.1 Normative Ethics
2.2.2 Artificial moral agents
2.3 Behavior prediction
2.3.1 Vehicle prediction
2.3.2 Pedestrian prediction
2.4 Game theory
2.4.1 Related works
2.5 Conclusion
3 MDP for decision making
3.1 Theoretical background
3.1.1 AV’s Architecture
3.1.2 Markov Decision Process
3.2 AV decision-making model
3.2.1 State and action sets
3.2.2 Transition function
3.2.3 Reward function
3.3 Results and discussion
3.3.1 Value iteration
3.3.2 Simulation
3.3.3 MDP policy results
3.4 Conclusion
4 Dilemma Deliberation
4.1 Dilemma situations
4.2 The definition of harm
4.2.1 Dv for collision
4.2.2 Vulnerability constant
4.3 Ethical deliberation process
4.3.1 Ethical Valence Theory
4.3.2 Ethical Optimization
4.3.3 Value iteration for dilemma scenarios
4.4 Results and discussion
4.4.1 Using EVT as ethical deliberation
4.4.2 Using the Ethical Optimization profiles to deliberate
4.5 Conclusion
5 Road User Intent Prediction
5.1 Broadening the scope
5.2 Intent estimation
5.2.1 Simulated Environment
5.2.2 Agent’s decision model
5.2.3 Estimating other agents’ intent
5.3 Incomplete game model
5.3.1 Nash equilibrium
5.3.2 Harsanyi’s Bayesian game
5.3.3 Decision making procedure
5.4 Simulation results
5.4.1 Multi-agent simulation
5.5 Final remarks
6 Conclusion
6.1 Final remarks
6.2 Future research perspectives
A Simulation set-up
A.1 Webots simulation structure
A.2 Controlling a car-like vehicle
A.3 Controlling the pedestrian
A.4 Necessary modifications
Bibliography
