Topic：Agent-Based Safety Risk Analysis of Future Air Traffic ManagementDesigns
Speaker: Prof. Henk Blom
Date：June 4 to 11, from 14:30 to 17:00
Venue: Room 320, Weimin Building
Brief Intro of the Speaker：
Prof. Blom is a professor of Delft University of Technology and director of Air Traffic Management Security. He is also the chief scientist of the Dutch National Aerospace Laboratory. Prof. Blom has nearly 30 years of experience in using stochastic modeling analysis theory for security risk analysis, multi-sensor data fusion, and air traffic management security analysis. He is a leader in the development of scientific innovation and has created numerous innovative methods such as interactive multi-model filtering, the Bayesian multi-sensor multi-target tracking system ARTAS (ATM Radar Tracker and Server) of the European Aviation Safety Organization, and agent-based security risk analysis mthod TOPAZ (Traffic Organization and Perturbation AnalyZer ), etc.
1. June 4（Monday）: Motivation and terminology
Lecture 1: Providing motivation of the relevance of proper safety risk modelling and analysis of operations in Air Traffic. To illustrate the power of agent-based safety risk modelling and analysis in learning an advanced operation like free flight.
Lecture 2: Providing insight in safety terminology, aviation accident statistics, safety regulation and safety management. Hands-on exercise: Apply the material from lectures 1 and 2 to a simple mode of transportation.
2. June 5（Tuesday）: Safety risk assessment basics
Lecture 3: Learning the basic safety risk assessment steps. Objective of a safety risk assessment. Identify the operation considered. Pushing the boundary between imaginable and unimaginable hazards. Hands-on exercise: Evaluate a given safety case against what you learned.
Lecture 4: Construction of scenarios. Types of safety risk models. Comparison to safety risk criteria. Hands-on exercise: Continue evaluation of a given safety case against what you learned.
3. June 6（Wednesday）: Agent-based modelling semantics
Lecture 5: Agent-based modelling, Situation Awareness, Multi-Agent Situation Awareness, Differences in multi-agent situation awareness. Hands-on exercise: Evaluate a given accident scenario.
Lecture 6: Models of Human information processing, Human error, Error recovery, Cognitive control model, Complementary sub-models in agent-based modelling of hazards. Hands-on exercise: Continue evaluation of given accident scenario.
4. June 7（Thursday）: Petri net modelling syntax
Lecture 7: Explaining the formalisms of ordinary Petri nets, stochastic Petri nets and coloured Petri nets. Hands-on exercise: Apply the material to simple examples.
Lecture 8: Extensions of Petri nets to Stochastically and Dynamically Coloured Petri nets. Develop an agent-based model of an operation using Petri nets. Hands-on exercise: Apply the material to simple examples.
5. June 8（Friday）: Simulation and validation
Lecture 9: From Petri net model specification to MC simulation. Accuracy of MC simulation results. Acceleration of MC simulation. Hands-on exercise: Reading a given Petri net specification.
Lecture 10: Model validation. Differences between model and reality. Using the MC simulation model for Uncertainty Quantification and Sensitivity Analysis. Hands-on exercise.
6. June 11（Monday）: Q & A
Closing lecture: Benchmark of Agent-based versus Event-sequence based risk analysis. Questions and Answers.
School of Reliability and Systems Engineering