Evaluation of Performance Enhancement for Crash Constellation Prediction via Car-to-Car Communication

A Simulation Model Based Approach
  • Thomas Kuehbeck
  • Gor Hakobyan
  • Axel Sikora
  • Claude C. Chibelushi
  • Mansour Moniri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8435)


Active safety systems for advanced driver assistance systems act within a complex, dynamic traffic environment featuring various sensor systems which detect the vehicles’ surroundings and interior. This paper describes the recent progress towards a performance evaluation of car-to-car communication (C2C) for active safety systems - in particular for crash constellation prediction. The methodology introduced in this work is designed to evaluate the impact of different sensors on the accuracy of a crash constellation prediction algorithm. The benefit of C2C communication (viewed as a virtual sensor) within a sensor data fusion architecture for pre-crash collision prediction is explored. Therefore, a simulation environment for accident scenarios analysis reproducing real-world sensor behaviour, is designed and implemented. Performance evaluation results show that C2C increases confidence in the estimated position of the oncoming vehicle. With C2C enhancement the given accuracy in time-to-collision (TTC) estimation is achievable about 110 ms earlier for moderate velocities at TTC range of [0.5s..0.2s]. The uncertainty in the vehicle position prediction at the time of collision can be reduced about half by integrating C2C communication into the sensor data fusion.


Abbreviate Injury Scale Collision Point Advanced Driver Assistance System Target Vehicle Accident Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Thomas Kuehbeck
    • 1
  • Gor Hakobyan
    • 1
  • Axel Sikora
    • 2
  • Claude C. Chibelushi
    • 3
  • Mansour Moniri
    • 3
  1. 1.BMW AGGermany
  2. 2.HS OffenburgGermany
  3. 3.Staffordshire UniversityUK

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