Autonomous Vehicle Trajectory Deviation Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in detecting and reporting improper road behavior by other vehicles, such as aggressive or unsafe driving, due to limited communication with human drivers or other autonomous systems, which can lead to potential collisions and safety concerns.
Innovation Solution
Equipping autonomous vehicles with sensors and processors to collect data on surrounding environments, detect deviations in trajectories of adjacent vehicles, and transmit records of unsafe behavior to remote processors for identification and regulatory action, including image recognition for license plate analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If autonomous vehicles collect and analyze large amounts of environmental data to detect driving anomalies, then the ability to identify unsafe behaviors improves, but the computational resources and processing complexity increase
Solution Approach 1:
The system segments the complex task of environmental data analysis into specialized modules: trajectory prediction module, behavior detection module, and anomaly identification module. Each module processes specific aspects of the data independently, reducing overall computational complexity while maintaining detection accuracy.
Solution Approach 2:
The patent introduces an intermediary processing layer that filters and pre-processes environmental data before it reaches the analysis modules. This intermediary layer reduces the volume of data requiring full processing, thereby decreasing computational resources needed while preserving critical detection capabilities.
2Reliability
If autonomous vehicles continuously monitor trajectories of adjacent vehicles to detect deviations, then safety monitoring improves, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system employs periodic sampling of trajectory data at optimized intervals. The monitoring frequency is dynamically adjusted based on detected conditions, maintaining safety monitoring capability while significantly reducing energy consumption during normal operating conditions.
Solution Approach 2:
The system changes the monitoring parameter from continuous to interval-based data collection. By adjusting the time interval between measurements based on traffic conditions and vehicle states, the system maintains reliable safety monitoring while optimizing energy consumption.
3Loss of information
If autonomous vehicles transmit detailed records of detected deviations to remote processors, then regulatory enforcement improves, but data transmission bandwidth requirements increase
Solution Approach 1:
The system extracts only the critical information needed for regulatory enforcement from the full environmental data set. Instead of transmitting complete raw data, the system extracts and transmits only the essential deviation parameters, vehicle identifiers, and location data, significantly reducing transmission bandwidth requirements while preserving information completeness.
Solution Approach 2:
The patent creates a condensed copy of the essential information from the full data record. This summary copy contains only the necessary elements for regulatory action, reducing data transmission volume while maintaining the integrity and completeness of the information required for enforcement.
4Difficulty of detecting and measuring
If autonomous vehicles use multiple sensors and processors to collect and analyze environmental data, then detection capability improves, but device complexity increases
Solution Approach 1:
The patent designs a multi-functional integrated processor that can handle data from multiple sensor types (cameras, radar, LiDAR) and perform various processing tasks (trajectory prediction, behavior analysis, anomaly detection). This universal processor reduces the need for separate dedicated processing units for each sensor type, thereby reducing overall device complexity while maintaining enhanced detection capability.
Data Source
AI summary
A vehicle comprises one or more sensors, and a processor coupled with the one or more sensors and stored inside a housing of the vehicle. The processor can be configured to collect data regarding the environment surrounding the vehicle from the one or more sensors; detect a second vehicle and an observed trajectory of the second vehicle from the collected data, the observed trajectory indicating a position or speed of the second vehicle over a time period; compare the observed trajectory with one or more expected trajectories of the second vehicle; responsive to determining a deviation between the observed trajectory and at least one of the one or more expected trajectories satisfies a condition, generate a record indicating the deviation and including a video of the second vehicle that corresponds to the observed trajectory; and transmit the record to a remote processor.