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Related Experiment Video

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A Personalized Navigation Route Recommendation Strategy Based on Differential Perceptron Tracking User's Driving

Pengzhan Chen1, Jihua Wu1, Ning Li1

  • 1Taizhou University, School of Intelligent Manufacture, Taizhou 318000, Zhejiang, China.

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This study introduces a personalized path recommendation strategy for autonomous driving that adapts to changing user preferences. The system dynamically updates path weights, ensuring optimal route selection even with evolving user needs.

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Area of Science:

  • Autonomous Driving
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Personalized path planning is crucial for autonomous driving.
  • User path preferences are dynamic and influenced by various factors.
  • Existing strategies may not effectively adapt to changing user needs.

Purpose of the Study:

  • To propose a personalized path recommendation strategy that tracks and adapts to user path preference changes.
  • To develop a system capable of dynamically updating path selection criteria.
  • To ensure optimal path planning for autonomous vehicles under evolving user preferences.

Main Methods:

  • Data collection and establishing relationships with user preference factors.
  • Utilizing dichotomized K-means algorithm for initial preference weight vector determination.
  • Implementing a threshold-based system to detect preference changes and redefining factors or using difference perception for updates.
  • Quantifying the road network based on the user preference weight vector.
  • Employing the Tabu search algorithm for optimal pathfinding.

Main Results:

  • The proposed strategy successfully tracks and adapts to user path preference changes.
  • Dynamic updating of preference weight vectors ensures continued relevance of path recommendations.
  • Simulation results demonstrate the strategy's effectiveness in two distinct scenarios.
  • The system meets the requirements of autonomous driving even when user preferences fluctuate.

Conclusions:

  • The developed personalized path recommendation strategy effectively handles dynamic user preferences in autonomous driving.
  • The adaptive nature of the system ensures robust and personalized route selection.
  • This approach enhances the user experience and efficiency of autonomous vehicle navigation.