How Data Annotation Services Fuel Self-Driving Industry 2021-Part4
Recently, the California Public Utility Commission (CPUC) announced on Twitter that cruise can provide driverless car passenger service without the participation of safety officers.
Cruise then twittered, saying it was the first company to get such a license.
It is worth noting that Waymo is listed in the list of applications published by CPUC as well, and has passed the exemption application like Cruise.
Earlier, Cruise CEO Dan Ammann said in a blog post that although cruise is not the first company to get a fully automatic driving test license, they want to be the first company not to use safe drivers in San Francisco.
“Today, we are honored to be the first company to obtain an autonomous driving service license to test passenger transport,” Cruise’s head of government affairs Prashanthi Raman said in a statement.
Specifically, Cruise has obtained the test license of the California motor vehicle authority (DMV)’s and the passenger service license of CPUC’s automatic driving.
Cruise has been recognized by DMV and CPUC, which means it has become the first company to carry out an automatic driving test with the participation of passengers. It is worth noting that cruise is still unable to charge passengers any fees at present.
CPUC has certain requirements for the automatic driving companies that have obtained this license.
Cruise and other companies involved in the test must submit quarterly reports on passenger-carrying operations and a plan on how to provide safety protection for passengers.
As a matter of fact, Cruise has put forward the plan of launching all unmanned Robotaxi services in 2019 and has postponed it to 2020. At that time, Dan Ammann, its chief executive, said in his blog that, for performance and safety reasons, although the US regulatory authorities had lowered down some requirements, they still needed to delay.
After nearly two years, cruise finally got what he wanted.
The passenger-carrying plan is about to be realized, and Cruise may promote the commercialization test of the driverless vehicle in the next step.
Cruise filed an application with the California motor vehicle administration on March 29, 2021, to allow its self-driving vehicles to charge for passenger and transportation services.
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According to Cruise’s application, its fully driverless vehicles will operate in some special situations, such as late-night, early morning in “certain routes” under good weather conditions” with speeds of 30 miles/h.
At present, the California motor vehicle administration has not yet approved its application. After that, Cruise needs CPUC permission to start commercial testing.
However, it is not known whether cruise will become the first commercial operation company this time. Waymo, its old rival, is on the same starting line.
In January 2021, Microsoft made a decisive investment and injected $2 billion into Cruise. In addition, Microsoft will provide cruise with AWS Azure cloud computing platform to improve profitability.
“The progress of digital technology is redefining all aspects of our work and life, including how we transport people and goods. As the preferred cloud service for cruise and general motors, we will help them expand their scale with the help of azure, and make self-driving travel the mainstream,” Satya NADELLA, CEO of Microsoft, said in the cooperation statement
Last year, at the CVPR 2019, Andrej Karpathy, the Senior Director of AI at Tesla responded to the question below:
how to estimate the volume of labeled data required to train and validate the self-driving cars for a particular scenario?”
378 hours of data.
The more accurate annotation is, the better algorithm performance will be.
Any tiny error during a driving experience may lead to dreadful results. Nowadays, people are more and more concerned about the driving safety issue as several self-driving automobile accidents happened.
For technology-type car companies, from 0 to 1 has been completed, but they still need to reduce costs and increase efficiency and move towards larger-scale production.
With the tremendous amount of training data and the high accuracy requirement, a high-quality data annotation service is crucial to guarantee autonomous vehicles are safe for the public.
Common Data Labeling Types Include:
It’s challenging for self-driving manufacturers to internally meet the burgeoning demand for high-quality data annotation.
The labeler used to annotate point by point, which cost lots of time.
3D annotation and video annotation are considered the toughest services in data labeling. At present, object tracking algorithms based on machine learning have already assisted video annotation. The annotator annotates the objects on the first frame, and then the algorithm tracks the ones in the subsequent frames. The annotator only needs to adjust the annotation when the algorithm doesn’t function well. It is 100 times faster than before.
Thanks to an AI-assisted system, the corresponding parts can be automatic can be transcribed and the human only needs to check and modify the wrong parts.
Nowadays, some AI-assisted tools come to practice, standing out in 2 factors.
- Cost reducing: With the help of AI-assisted capabilities, clients can save more money as the labor cost goes down.
- Time reducing: Make the large-scale requirement of training data done in a short time. Using AI-assisted tool can improve efficiency multiple times
Can we get rid of the human workforce?
The answer is no.
In fact, manually labeled data is less prone to errors regarding quality assurance and data exceptions.
The human workforce cannot be totally replaced by some tools leading with an AI-based automation feature, especially dealing with exception, edge cases, complex data labeling scenarios, etc.
ByteBridge is a human-powered and ML-powered data labeling tooling platform. We provide scalable, high-quality training data for ML/AI industry with flexible workflow.
Quality and Accuracy
- ML-assisted capacity can help reduce human errors by automatically pre-labeling
- The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy.
- Consensus — Assign the same task to several workers, and the correct answer is the one that comes back from the majority output.
- All work results are completely screened and inspected by the machine and human workforce.
In this way, ByteBridge can affirm our data acceptance and accuracy rate is over 98%.
- Progress preview: client can monitor the labeling progress in real-time on the dashboard
- Result preview: client can get the results in real-time on the dashboard
- Real-time Outputs: client can get real-time output results through API. We support JSON, XML, CSV, etc., and we can provide customizable datatype to meet your needs.
3D Point Cloud Annotation Service
ByteBridge self-developed 3D Point Cloud labeling, quality inspection tool, and pre-labeling functions can complete high-quality and high-precision 3D point cloud annotation for 2D-3D fusion or 3D images provided by different manufacturers and equipment, and provide one-station management service of labeling, QA, and QC.
More info: ByteBridge Launches World’s First Mobile 3D Point Cloud Data Labeling Service
3D Point Cloud Annotation Types:
- Sensor Fusion Cuboids: 12 categories include car, truck, heavy vehicle, two-wheeled vehicle, pedestrian, etc.
- Sensor Fusion Segmentation: obstacles classification, different types of lanes differentiation
- Sensor Fusion Cuboids Tracking
① Tracking the same object with the same ID, labeling the leaving state;
② Point clouds or time-aligned images could be provided, point clouds outputs only.
A collaboration of the human-work force and AI algorithms ensure a 50% lower price compared to the conventional market.
As the quality of the labeled dataset determines the success of the self-driving industry, cooperation with a reliable partner can help developers to overcome the data labeling challenges.
We can provide personalized annotation tools and services according to customer requirements.
If you need data labeling and collection services, please have a look at bytebridge.io, the clear pricing is available.
Please feel free to contact us: email@example.com
1 Introduction of Giant Self-driving Company Waymo
2 Either Algorithm or Calculation Force is more Important for Automatic Driving?
3 Which One is More Important to Automatic Driving, Algorithm or Computing Power
4 How Data Labeling and Annotation Services Empower Self-Driving Bus?
5 Labeling Service Case Study — Video Annotation — License Plate Recognition