Gerald Sequeira

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Crash Severity Prediction using data-base approaches

In this project, students will learn about different metrics for crash severity. The students have to solve the problem of predicting the crash severity using database approaches.
The following are the tasks:
1. Collecting the data through vehicle-to-vehicle and Occupant simulations in LS-dyna.
2. Literature Survey on Crash Severity Metrics and selection of the metrics for prediction. 
3. Analysing the data in Matlab and creating a database including all the selected metrics.
4. Literature survey on data learning techniques.
5. Selection of the required technique for data learning and creating a prediction model.
6. Developing a prediction model and demonstrating results.

Requirements:
1. Matlab (must)
2. LS-dyna (Students will be guided)





Integrale Fahrzeugsicherheit SS2022

  • Grundlagen integraler Sicherheit
  • Unfallforschung, Biomechanik u. Sicherheitsanforderungen
  • Pkw-Auslegung für Insassen-u. Partnerschutz, Sensorik
  • Gesetzliche und andere Anforderungen an die passive Sicherheit
  • Fahrzeugsicherheit im Entwicklungsprozess: Modellbildung Funktionsentwicklung, Unfalldatenanalyse, wesentliche Entwicklungsschritte
  • Systeme der Fahrzeugsicherheit: Architektur, Bauform und Wirkungsweise von Auffahrwarnung, Intelli-gente Bremsassistenz, Spurverlassenswarnung, Spurwechselwarnung, Lichtsysteme, präv. Fußgängerschutz

Weitere Kurse

IAE-Student Project Ultrasonic

Group Project – Challenges and Potential of using Ultrasonic Sensor in the near field as Safing sensor

Supervisors: Professor Thomas Brandmeier and Mr. Gerald Joy Alphonso Sequeira

The students will model investigate the ultrasonic sensor in the near field (0.5 to 10m) i.e. just before the crash to validate the predictions made in the far and midfield by other sensors. There are many challenges such as speed limit for use of ultrasonic sensor, attenuation of the signal strength due to the wind, doppler shift, etc. These challenges will be listed and have to be investigated experimentally to understand is it possible to extend these limits and reduce attenuation.

Additionally, there are opportunities by using multiple sensors to find the position and the using multiple frames the direction of movement.

In the last phase, the noise of the sensor signal to the weather conditions such as rain or fog would be investigated in the CARISSMA indoor test area.

By doing this group project the students will
- learn about signal processing and ultrasonic sensors
- scientifically analyzing the sensor and building test cases for analysis
- Testing experience for automotive perception problem
- Experience in weather influence on the sensors

Required tools:
- the students’ notebooks or pc pool lab
- 2x Ultrasonic sensor (Texas Instrument with board)
- Matlab

Vehicle Crash Mechanics and Biomechanics

After successfully completing the module, students know the basic concepts and knowledge in vehicle safety and crash mechanics. The program is structured to cover the important topics related to the vehicle safety: Crash modelling for frontal and lateral collisions and rollovers, finite element analysis, occupant protection strategies, Passive vehicle safety systems (airbag control unit, conventional crash sensors, algorithms, safety actuators) and biomechanics. At the completion of this course, students should be able to understand crash processes, to construct and simulate simple crash models, understand human anatomy and its mechanics during vehicle crash.

Vehicle Crash Mechanics and Biomechanics WS 22/23

After successfully completing the module, students know the basic concepts and knowledge in vehicle safety and crash mechanics. The program is structured to cover the important topics related to the vehicle safety: Crash modelling for frontal and lateral collisions and rollovers, finite element analysis, occupant protection strategies, Passive vehicle safety systems (airbag control unit, conventional crash sensors, algorithms, safety actuators) and biomechanics. At the completion of this course, students should be able to understand crash processes, to construct and simulate simple crash models, understand human anatomy and its mechanics during vehicle crash.

The following topics are covered: • Basic terms and definitions in vehicle safety • Crash Mechanics • Crash Modelling, Multibody Modelling, Finite Element Analysis • Passive Safety Systems • Frontal and lateral collision, Rollover • Crash- & Safety-Sensors, Crash detection Algorithms, Use of environmental sensors in Passive Safety • Irreversible and reversible Safety Actuators • Emergency Medicine • Biomechanics