Application of Swarm Intelligence in Autonomous Cars for Obstacle Avoidance

  • Adil HashimEmail author
  • Tanya Saini
  • Hemant Bhardwaj
  • Adityan Jothi
  • Ammannagari Vinay Kumar
Part of the Studies in Computational Intelligence book series (SCI, volume 771)


Obstacle detection is a major challenge which must be addressed for optimal implementation of self-driving cars. Various approaches have been postulated regarding the same. However, the acquisition of data by the various sensors in a car is shortsighted and constrained due the physical limitations in the scope of the sensors. In this chapter, we propose a model for obstacle avoidance in self-driving cars by integrating swarm intelligence with pre-existing conventional technologies. By establishing bi-directional communication of sensory data between the various cars which may form a network we can overcome the limitations faced by the receptors of a self-driving car.


Self-driving cars Computer vision Convolutional neural networks Swarm robotics Obstacle avoidance 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Adil Hashim
    • 1
    Email author
  • Tanya Saini
    • 1
  • Hemant Bhardwaj
    • 1
  • Adityan Jothi
    • 1
  • Ammannagari Vinay Kumar
    • 1
  1. 1.Amity UniversityNoidaIndia

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