Vehicle Sensor Fusion Control for Low-Latency Fleet Routing
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Solution Overview
Problem
Autonomous vehicles face processing power limitations when collecting and assessing vast amounts of sensor data from various sources, leading to inefficiencies in real-time decision-making and routing updates due to overburdened processing capabilities and latency issues in data transmission from external servers.
Innovation Solution
Implementing a centralized operations-control vehicle or roadside base stations with advanced processing power and sensors to collect, process, and disseminate sensor information across a fleet of vehicles, enabling efficient sensor fusion and timely routing instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If sensor data is processed at the vehicle level or transmitted to external servers in large batches, then processing power requirements are reduced at the vehicle, but latency increases and real-time decision-making efficiency deteriorates
Solution Approach 1:
The patent segments the data processing function by dividing it between vehicle-level processors and centralized operations-control vehicles. Each vehicle processes its own sensor data locally for immediate decisions, while simultaneously transmitting data to centralized vehicles for fleet-wide analysis and routing optimization. This segmentation allows parallel processing that reduces latency while maintaining high decision-making efficiency.
2Measurement precision
If vast amounts of sensor data are collected and assessed at the vehicle level, then measurement precision and environmental awareness are improved, but processing power requirements and device complexity increase
Solution Approach 1:
The patent merges processing capabilities by designating certain vehicles as operations-control vehicles with enhanced processing power and sensor arrays. These centralized vehicles aggregate and process sensor data from multiple vehicles in the fleet, performing sensor fusion and comprehensive environmental assessment. This merging allows individual vehicles to maintain simpler processing systems while the fleet collectively achieves high measurement precision through the capabilities of operations-control vehicles.
3Power
If sensor information is transmitted to external servers for processing, then centralized processing power can be utilized, but transmission latency and loss of time increase
Solution Approach 1:
The patent introduces operations-control vehicles as intermediary processing nodes between individual vehicles and external servers. These intermediary vehicles receive sensor data from multiple sources, perform initial processing and sensor fusion, and then transmit consolidated information to external servers or distribute processed data back to vehicles. This intermediary layer reduces transmission latency by performing preliminary processing locally and only transmitting essential aggregated data to external servers.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the processing and distribution of sensor information, leading to improved routing and handling of vehicles by reducing the processing burden on individual vehicles and minimizing latency, thereby enabling more efficient and timely decision-making.
Implementation Method 1
A LIDAR sensor works by emitting a light beam and measuring the time it takes to return. The return time for each return light beam is combined with the location of the LiDAR sensor to determine a precise location of a surface point of an object
Implementation Method 2
A radar antenna may detect and estimate the shape of objects near the vehicle. The radar antennas may be phased array antennas
Implementation Method 3
A camera works by opening an aperture to take in light through a lens, and then a light detector (e.g., a charge-coupled device (CCD) or CMOS image sensor) turns the captured light into electrical signals including color and brightness of each pixel of the image
Data Source
AI summary
In one embodiment, a method includes receiving sensor data from one or more sensors of each of one or more vehicles, processing a combination of the sensor data to generate an assessment of an area surrounding the one or more vehicles based on one or more points-of-view of the area, the one or more points-of-view of the area generated based on synchronizing the combination of the sensor data, and detecting an occurrence of an event based on the assessment of the area. The method further includes identifying one or more instructions corresponding to the event, the instructions associated with a particular vehicle and sending one or more executable instructions based on the instructions to the particular vehicle.