Autonomous Route Planning Using Passerby Traffic Distribution

The system performs preliminary actions by predicting the positions and trajectories of moving objects in advance, and pre-planning avoidance routes before collision actually occurs. The route setting device calculates future positions of moving objects based on their current speed and direction, and determines avoidance routes in advance, allowing the robot to execute smooth avoidance maneuvers without sudden deceleration or frequent route recalculations.

The system dynamically adjusts the avoidance strategy based on the robot's state and environmental conditions. When the robot is stationary or moving slowly, more comprehensive detection and prediction is performed. When moving at high speed, the system prioritizes critical avoidance actions. The route setting is dynamically updated based on real-time position, speed, and detected moving objects, optimizing the balance between safety and travel efficiency.

The system calculates and prepares avoidance routes in advance based on predicted positions of moving objects. By determining the optimal avoidance path before execution, the robot can maintain higher speeds during avoidance maneuvers rather than simply slowing down. The preliminary route calculation includes speed optimization, allowing the robot to execute efficient avoidance actions that minimize speed reduction.

The system changes multiple parameters simultaneously during avoidance actions, including route geometry, speed profile, and timing. Instead of merely reducing speed, the route setting device optimizes a combination of parameters: selecting alternative paths, adjusting speed curves along the route, and timing maneuvers to minimize impact on overall travel time. This multi-parameter optimization allows safer avoidance while preserving traveling speed.

The route setting device performs preliminary calculations to determine optimal avoidance routes before the robot encounters moving objects. By pre-calculating multiple potential avoidance paths and their characteristics, the system reduces real-time control complexity. When avoidance is needed, the robot can execute a pre-determined route rather than performing complex real-time path planning, simplifying the control logic while maintaining effective collision avoidance.

The system uses simplified models and representations of the environment and moving objects for route calculation. Instead of processing full complex sensor data in real-time, the route setting device uses copied or simplified representations: predicted positions based on current speed and direction, simplified obstacle models, and pre-defined route templates. This copying approach reduces computational complexity while maintaining sufficient accuracy for avoidance decisions.

The system merges multiple avoidance considerations into a single integrated route planning process. Instead of performing separate detection, prediction, route calculation, and execution steps for each moving object independently, the route setting device combines all these functions into one comprehensive route setting operation. Multiple moving objects are processed simultaneously in a single control cycle, reducing the number of discrete control operations while maintaining responsive avoidance capability.

The route setting device serves multiple functions simultaneously: it detects moving objects, predicts their trajectories, determines avoidance necessity, calculates optimal avoidance routes, and generates control commands all in one unified process. This multi-functional approach eliminates the need for separate specialized modules for each function, reducing overall control complexity while maintaining comprehensive avoidance responsiveness.