An Enhanced Map-Matching Algorithm for Real-Time Position Accuracy Improvement with a Low-Cost GPS Receiver.

Area of Science:

• Geomatics Engineering
• Computer Science
• Robotics

Background:

• Low-cost global positioning systems (GPS) often suffer from limited accuracy, hindering real-time applications.
• Accurate vehicle localization is crucial for autonomous driving and advanced navigation systems.

Purpose of the Study:

• To propose a real-time method for improving the position accuracy of low-cost GPS devices.
• To enhance horizontal accuracy by leveraging digital road map data and map-matching techniques.

Main Methods:

• Utilizing a digital road database and map-matching algorithms to link vehicle location to map positions.
• Employing the iterative closest point (ICP) algorithm for rotation and translation compensation between GPS and map data.
• Applying the least squares method to correct rotational errors and eliminate residual disparities for precise map linking.

Main Results:

• The proposed method effectively distinguishes vehicle direction on the road, enhancing horizontal accuracy.
• Real-time implementation on a low-cost embedded system demonstrated significant improvements in position accuracy.
• Experimental results validated the effectiveness of the integrated GPS and digital map approach.

Conclusions:

• The developed method offers a practical solution for enhancing the accuracy of low-cost GPS positioning in real-time.
• Integration of digital map information and advanced algorithms like ICP significantly improves vehicle localization.
• This approach provides a foundation for more reliable and precise navigation systems in resource-constrained environments.