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Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles-A Survey.

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Achieving higher levels of autonomous driving requires accurate situation awareness. This survey explores data fusion and situation awareness challenges for effective decision-making in automated vehicles (AVs).

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automated driving system (ADS)autonomous vehicle (AV)data pre-processingmachine learning (ML)multimodal fusionrule framingsituation awareness (SA)

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Area of Science:

  • Robotics and Artificial Intelligence
  • Intelligent Transportation Systems

Background:

  • Higher automation levels in autonomous vehicles (AVs) necessitate robust situation awareness.
  • Vehicles depend on onboard sensors and V2X communication for environmental perception.
  • Heterogeneous sensor suites are essential for comprehensive situation awareness, but data fusion presents significant challenges.

Purpose of the Study:

  • To analyze the influence of data pre-processing, particularly data fusion, on situation awareness for AV decision-making.
  • To identify key challenges in fusing data from heterogeneous sensors for accurate environmental context.
  • To provide insights into research directions for enhanced contextual awareness in AVs.

Main Methods:

  • Comprehensive review and analysis of recent scientific literature on autonomous driving, sensor fusion, and situation awareness.
  • Taxonomic classification of challenges and solutions related to data fusion in AVs.
  • Identification of critical factors influencing effective decision-making.

Main Results:

  • Data fusion and situation awareness are critical for optimal decision-making in higher automation levels.
  • Challenges in fusing heterogeneous sensor data hinder accurate environmental context creation.
  • Existing research presents several hurdles that need addressing for advanced AV capabilities.

Conclusions:

  • Accurate contextual awareness, achieved through effective data fusion and pre-processing, is paramount for advanced autonomous driving.
  • Addressing current fusion challenges is crucial for realizing the full potential of higher automation levels.
  • This survey offers a unique perspective on research directions for achieving robust contextual awareness.