The High-Speed Autonomous Vehicle Navigation project is a groundbreaking initiative aimed at designing and simulating an advanced navigation system for autonomous vehicles. Set against the dynamic backdrop of Shanghai's streets, the primary goal of this project is to ensure vehicles can dynamically detect and evade obstacles even while navigating at high speeds.
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Carla Simulator Integration:
- Emulates a Tesla Model 3's journey through Shanghai's intricate roadways.
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Dynamic Obstacle Evasion:
- Advanced algorithms in place for real-time obstacle detection and avoidance.
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Probabilistic Roadmap:
- Utilized for plotting potential step points, facilitating optimal path planning.
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Dijkstra's Algorithm:
- Deployed to trace the shortest and most efficient navigation path.
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Synchronized Subsystem Data with PID Controller:
- Ensures streamlined vehicle operations by coordinating data flow from various subsystems.
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Performance Optimization with Scipy’s Optimizer:
- Minimizes unpredictability and boosts vehicle speed, guaranteeing consistent obstacle evasion.
Our endeavor has been lauded for its innovation and impeccable execution, culminating in a coveted spot among the top ten nominations for the Principles of Safe Autonomy project showcase of UIUC in Fall 2022.