EnvironmentMonitoring Class Reference#

Demo: demo::EnvironmentMonitoring Class Reference
Demo
demo::EnvironmentMonitoring Class Reference

Environment Monitoring software component. More...

#include <environment_monitoring.hpp>

Public Member Functions

void integrateWithSensors (SensorType sensorType)
 Integrates with various sensors to perceive the surrounding environment.
 
void processSensorData ()
 Processes sensor data in real-time to generate a comprehensive understanding of the environment.
 
void makeDecisionsAndPlanTrajectories ()
 Makes decisions and plans trajectories based on the perceived environment and predefined rules.
 
void controlVehicleSystems ()
 Controls the vehicle's acceleration, steering, and braking systems to execute planned maneuvers.
 
void ensureSafetyCompliance ()
 Complies with safety regulations and prioritizes passenger and pedestrian safety.
 

Detailed Description

Environment Monitoring software component.

Implementation Class: EnvironmentMonitoring SW-CLS-ENVMON ../../../../_images/arrow-right-circle.svg
implements: SW-COMP-011

The Environment Monitoring software component aggregates sensor data to create a full internal model of the environment and algorithms to make automated decisions based on these inputs. It integrates with various sensors, processes sensor data in real-time, generates a comprehensive understanding of the road, traffic, and obstacles, makes decisions and plans trajectories based on the perceived environment and predefined rules, and controls the vehicle's acceleration, steering, and braking systems to execute planned maneuvers while complying with safety regulations and prioritizing passenger and pedestrian safety.

Member Function Documentation

◆ controlVehicleSystems()

void demo::EnvironmentMonitoring::controlVehicleSystems ( )

Controls the vehicle's acceleration, steering, and braking systems to execute planned maneuvers.

This function controls the vehicle's acceleration, steering, and braking systems to execute planned maneuvers. It sends commands and signals to the vehicle's control systems, adjusting the vehicle's motion parameters to follow the planned trajectories and safely navigate through the environment.

◆ ensureSafetyCompliance()

void demo::EnvironmentMonitoring::ensureSafetyCompliance ( )

Complies with safety regulations and prioritizes passenger and pedestrian safety.

This function ensures that the Environment Monitoring software component complies with safety regulations and prioritizes passenger and pedestrian safety. It incorporates safety checks, risk assessment algorithms, and collision avoidance mechanisms to avoid potential hazards and mitigate risks during automated driving operations.

◆ integrateWithSensors()

void demo::EnvironmentMonitoring::integrateWithSensors ( SensorType  sensorType)

Integrates with various sensors to perceive the surrounding environment.

Parameters
sensorTypeThe type of sensor to integrate.

This function integrates with various sensors, including cameras, radar, and LIDAR, to perceive the surrounding environment. It takes as input the type of sensor to integrate and establishes the necessary communication channels with the sensor hardware to receive the sensor data.

◆ makeDecisionsAndPlanTrajectories()

void demo::EnvironmentMonitoring::makeDecisionsAndPlanTrajectories ( )

Makes decisions and plans trajectories based on the perceived environment and predefined rules.

This function makes decisions and plans trajectories based on the perceived environment and predefined rules. It applies decision-making algorithms and trajectory planning techniques to analyze the internal model of the environment, evaluate potential actions, and generate optimal trajectories that satisfy safety constraints, traffic regulations, and predefined objectives.

◆ processSensorData()

void demo::EnvironmentMonitoring::processSensorData ( )

Processes sensor data in real-time to generate a comprehensive understanding of the environment.

This function processes sensor data in real-time to generate a comprehensive understanding of the road, traffic, and obstacles. It applies computer vision, signal processing, and data fusion techniques to the received sensor data, extracting relevant features and constructing an internal model of the environment for further analysis and decision-making.


The documentation for this class was generated from the following file: