Lidar Signal Coding to Mitigate Autonomous Vehicle Interference
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional lidar sensor systems in autonomous vehicles are susceptible to interference, leading to inaccurate point clouds due to detection of light signals emitted by other lidar systems, which increases as the number of autonomous vehicles grows.
Innovation Solution
Incorporating a code in the light signals emitted by lidar sensor systems that can differentiate them from signals emitted by other systems, allowing the detection system to determine whether the received signal was emitted by itself, and dynamically altering these codes based on orientation, geospatial position, interference detection, and time to minimize interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional lidar sensor systems detect light signals within a predefined frequency band, then the system can operate with simple detection mechanisms, but the detector becomes susceptible to interference from other lidar systems
Solution Approach 1:
The patent applies parameter changes by modulating the light signal with unique codes (such as pseudo-random sequences or frequency shifts) that differentiate signals from different lidar systems. The detector is configured to recognize these specific codes, allowing it to filter out interference from other systems while maintaining operational simplicity. This resolves the contradiction by changing the signal parameter (adding unique identification codes) rather than complicating the detection mechanism itself.
2Productivity
If the number of autonomous vehicles with lidar systems increases, then the coverage and utility of the system expands, but the probability of interference between systems increases
Solution Approach 1:
The patent applies segmentation by dividing the shared electromagnetic spectrum into distinct, identifiable signal segments through the use of unique codes for each lidar system. Each system is assigned a specific code (such as a unique pseudo-random sequence or frequency offset), allowing multiple systems to operate simultaneously without interference. The detector segments incoming signals based on these codes, accepting only those matching its assigned code while rejecting others, thus enabling scalable deployment without increasing interference probability.
3Measurement precision
If the detector detects all light signals within the frequency band, then no signal is lost, but the point cloud includes inaccuracies from detected interference signals
Solution Approach 1:
The patent implements feedback by having the detector continuously monitor incoming light signals for the presence of recognized codes. When a signal with the correct code is detected, it is processed and added to the point cloud. When a signal without the correct code (interference) is detected, it is rejected. This feedback mechanism ensures that only valid signals contribute to the point cloud, maintaining measurement precision without losing information from legitimate signals, as the system adapts its acceptance criteria based on code recognition.
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
This approach effectively reduces the probability of interference by ensuring that each lidar sensor system emits unique codes, thereby improving the accuracy of point clouds generated by autonomous vehicles, especially in scenarios with multiple vehicles.
Implementation Method 1
Based on a time between when the lidar sensor system emits the light signal and when the detector detects the light signal after the light signal has reflected off the object, the lidar sensor system can determine a distance between the object and the lidar sensor system
Implementation Method 2
The light signal reflects off an object and returns to a detector of the lidar sensor system
Implementation Method 3
a lidar sensor system emitting a light signal that is constructed by the lidar sensor system such that the emitted light signal has a code therein, wherein the code can differentiate the emitted light signal from another light signal emitted by another lidar sensor system
Data Source
AI summary
An autonomous vehicle having a lidar sensor system is described. A computing system is configured to determine that the lidar sensor system is to update a code that is included in light signals emitted by the lidar sensor system. The computing system transmits a command signal to the lidar sensor system, wherein the command signal causes the lidar sensor system to transition from emitting light signals with a first code therein to emitting light signals with a second code therein, wherein the first code is different from the second code.