Seminar "Context Prediction in Autonomous Driving"

Organizer: M.Sc. Sina Shafaei

Modul: IN2107

Type: MasterSeminar

Semester: WS 2017/2018

ECTS: 4.0

SWS: 2

Time & Location: 02.09.023 / 15:00-17:00


  • The first session of the seminar (details, topic assignments, team members) will be on 20.10.2017 at 02.09.023, 15:00-17:00
  • The preliminary talk took place on 12th of July 2017, 13:00-14:00 at 02.09.023 on the second floor. Slides


Challenged by the increasing complexity of today's software and physical environments specially in the domain of autonomous driving, new technologies are required which seamlessly integrate with driver and other occupants needs. The development of suitable context prediction methodologies to provide the proactive behavior for the intelligent applications, is however a challenge. The reason is that future context information, hidden in the raw context traces left by users in the real world, is not immediately accessible to applications. Therefore, sophisticated context prediction approaches are required that are able to discover and mine patterns (e.g. of a driver's behavior) from observed context history. In this seminar various topics will be discussed which are among the state-of-the-art in the domain of context prediction and autonomous driving

                                  Topic Team MembersPresentation (Date)
C- Driver Behavior Modeling For Context Prediction12.01.2018
D- Challenges of Deploying Neural Nets for Context Prediction in Fully Automated Driving12.01.2018
E- Neural Networks and Deep Learning in Context Prediction19.01.2018
F- Context Prediction and Reinforcement Learning 19.01.2018
G- Approaches for Optimizing the Accuracy of the Prediction Results 26.01.2018
H- Limitations of Deep Learning Methods in Context Prediction26.01.2018
I- Trajectory Prolongation Approach (Interpolation/Approximation)02.02.2018
J- Ambient Intelligent Systems 02.02.2018
A- Challenges in Designing a Context Prediction Architecture09.02.2018
L- Enabling Proactiveness through Context Prediction09.02.2018