20240025441. State Estimation and Response to Active School Vehicles in a Self-Driving System simplified abstract (Ford Global Technologies, LLC)
State Estimation and Response to Active School Vehicles in a Self-Driving System
Organization Name
Inventor(s)
John Russell Lepird of Pittsburgh PA (US)
Patrick Stirling Barone of Saratoga CA (US)
Alexander Wah Tak Metz of Munich (DE)
State Estimation and Response to Active School Vehicles in a Self-Driving System - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240025441 titled 'State Estimation and Response to Active School Vehicles in a Self-Driving System
Simplified Explanation
The abstract of this patent application describes a system, method, and computer program product for estimating the state of a school transportation vehicle. The method involves capturing sensor data about the vehicle's environment, detecting the presence of a school transportation vehicle in the sensor data, receiving a list of indicators associated with potential states of the vehicle, analyzing data from various sources to determine indicator values, and using these values to compute a probability mass function that represents the likelihood of the vehicle being in each potential state. The method also involves imposing goals on the vehicle's motion control system based on the probability mass function and causing the vehicle to operate accordingly.
- The patent application describes a method for estimating the state of a school transportation vehicle using sensor data and indicator values.
- The method involves capturing sensor data about the vehicle's environment and detecting the presence of a school transportation vehicle.
- A list of indicators associated with potential states of the vehicle is received.
- Data from various sources is analyzed to determine indicator values.
- Indicator values are used to compute a probability mass function representing the likelihood of the vehicle being in each potential state.
- Goals are imposed on the vehicle's motion control system based on the probability mass function.
- The autonomous vehicle operates according to the imposed goals.
Potential applications of this technology:
- Enhancing the safety and efficiency of school transportation vehicles.
- Improving the monitoring and control of autonomous vehicles in school transportation settings.
- Providing real-time information about the state of school transportation vehicles to relevant stakeholders, such as parents, school administrators, and transportation authorities.
Problems solved by this technology:
- Estimating the state of a school transportation vehicle in real-time, which can help in ensuring the safety and security of students.
- Optimizing the operation of autonomous vehicles in school transportation scenarios by considering various indicators and goals.
- Providing a comprehensive understanding of the environment and state of the vehicle to enable better decision-making and control.
Benefits of this technology:
- Increased safety and security for students using school transportation vehicles.
- Improved efficiency and effectiveness of autonomous vehicles in school transportation settings.
- Enhanced monitoring and control capabilities for school transportation systems.
- Real-time information and insights about the state of school transportation vehicles for stakeholders.
Original Abstract Submitted
this document discloses system, method, and computer program product embodiments for estimating the state of a school transportation vehicle. for example, the method includes capturing sensor data that includes information about an environment of an autonomous vehicle. the method further includes detecting a school transportation vehicle in the sensor data, receiving a list of indicators associated with a set of candidate states for the school transportation vehicle, and analyzing data from one or more sources to determine indicator values. the method further includes using the indicator values to compute a probability mass function that includes a likelihood that the school transportation vehicle is in each of the candidate states. the method further includes imposing one or more goals on a motion control system of the autonomous vehicle based on the probability mass function and causing the autonomous vehicle to operate according to the one or more goals.
