Remote Vehicle Perception Using Sensor Sharing From Connected Vehicles
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Solution Overview
Problem
Remote driving systems face challenges when the vehicle's sensors are insufficient to provide a complete environment view, which can endanger the vehicle and surrounding vehicles, especially in situations where the driver is incapacitated or the vehicle is severely damaged.
Innovation Solution
The system augments the vehicle's sensor view by connecting with surrounding connected vehicles to obtain supplemental sensor information, which is integrated with the vehicle's sensor information to generate a comprehensive environment view for remote operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the vehicle uses only its own sensors for remote driving, then the system complexity is low, but the sensor information is insufficient to provide a complete environment view
Solution Approach 1:
The patent merges sensor data from multiple connected vehicles with the ego-vehicle's sensor data to create a comprehensive environment view. The sensor fusion module combines data from surrounding vehicles' sensors (cameras, LIDAR, radar) with the ego-vehicle's sensor information, integrating multiple data sources to overcome the limitation of individual vehicle sensors and provide complete environmental awareness for remote driving operations.
Solution Approach 2:
The system enables universal sensor utilization by allowing any connected vehicle's sensors to serve the ego-vehicle's remote driving needs. The sensor sharing mechanism allows vehicles in the connected fleet to contribute their sensor capabilities to assist the ego-vehicle, making the sensor resources across the fleet universally applicable to any vehicle that requires assistance, thereby reducing information loss without proportionally increasing individual vehicle complexity.
2Reliability
If the vehicle requests sensor information from surrounding connected vehicles, then the environment view is improved, but the communication and coordination complexity increases
Solution Approach 1:
The system performs preliminary actions by establishing communication protocols and sensor sharing agreements with surrounding connected vehicles before remote driving assistance is needed. The vehicles maintain pre-configured communication channels and sensor data streams, so when the ego-vehicle requires assistance, the sensor information is already available and synchronized, reducing the complexity of real-time coordination and improving reliability by ensuring data availability ahead of time.
Solution Approach 2:
The system implements feedback mechanisms where the ego-vehicle receives sensor information from surrounding vehicles, evaluates the completeness and quality of the environment view, and adjusts its sensor information requests accordingly. The remote operator provides feedback on the sufficiency of the environment view, which triggers additional sensor requests or maneuvers to acquire missing information, creating a closed-loop system that improves reliability while managing communication complexity through adaptive feedback-driven requests.
3Loss of information
If the vehicle maneuvers to obtain supplemental sensor information, then the sensor coverage is improved, but the time to complete the remote driving task increases
Solution Approach 1:
The system applies partial action by requesting only the specific sensor information that is insufficient for the current remote driving task, rather than acquiring all possible sensor data. The sensor information request module analyzes the gap between available and required sensor coverage, and maneuvers the vehicle only to the extent necessary to obtain the missing critical information, avoiding excessive maneuvering that would waste time. This selective approach improves environment view completeness while minimizing time loss.
4Measurement precision
If the system integrates sensor information from multiple vehicles, then the environment view is comprehensive, but the data processing complexity increases
Solution Approach 1:
The system segments the sensor information integration process into distinct functional modules: sensor data reception, data validation, sensor fusion, and environment model generation. Each module handles specific aspects of the data processing pipeline, allowing parallel processing of different sensor types and vehicles' data independently. This segmentation reduces overall data processing complexity by breaking down the complex integration task into manageable, specialized sub-tasks while maintaining comprehensive and accurate environment perception.
Data Source
AI summary
Systems and methods are provided for augmenting a sensor view of a vehicle. The system can determine that the vehicle needs operation assistance to complete a remote driving task. Sensor information can be requested from the vehicle. Based on the sensor information, the system can determine that the sensor information is insufficient to perform the remote driving task. The system can connect with one or more surrounding vehicles connected to the vehicle to obtain supplemental sensor information. The sensor information and the supplemental sensor information can be applied to complete the remote driving task.