Planning and decision-making for autonomous vehicles

Wilko Schwarting, Javier Alonso Mora, Daniela Rus

Research output: Contribution to journalArticleScientificpeer-review

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In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning, and decision-making for autonomous vehicles have led to great improvements in functional capabilities, with several prototypes already driving on our roads and streets. Yet challenges remain regarding guaranteed performance and safety under all driving circumstances. For instance, planning methods that provide safe and system-compliant performance in complex, cluttered environments while modeling the uncertain interaction with other traffic participants are required. Furthermore, new paradigms, such as interactive planning and end-to-end learning, open up questions regarding safety and reliability that need to be addressed. In this survey, we emphasize recent approaches for integrated perception and planning and for behavior-aware planning, many of which rely on machine learning. This raises the question of verification and safety, which we also touch upon. Finally, we discuss the state of the art and remaining challenges for managing fleets of autonomous vehicles.
Original languageEnglish
Pages (from-to)187-210
JournalAnnual Review of Control, Robotics, and Autonomous Systems
Publication statusPublished - 2018

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • autonomous vehicles
  • intelligent vehicles
  • decision-making
  • motion planning
  • artificial intelligence
  • verification
  • fleet management


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