The information in the links below provide data, references, and background knowledge about autonomous vehicles, and their potential influences. Students submitting to the Modeling the Future Challenge can use these resources to help create their models for how autonomous vehicles might affect the future, but students are not limited to only using references and data from the sites provided. The information found in these links is not owned or operated by the Modeling the Future Challenge and should be properly cited in any submitted report.
This report from a 2016 Mckinsey & Co. study contains data on future opportunities to use autonomous vehicle data. Of particular use for this challenge are exhibits 10, 11, 14, and 15, that identify the likelihood of adoption of autonomous vehicles in certain demographics. These charts are copied below. This data is not claimed or owned by the Modeling the Future Challenge, please cite its use appropriately. When using information from these or other charts in your report, be sure to provide your own mathematical calculations to justify how you arrived at each result. For example, if you note that you expect 15% of vehicles to be autonomous by 2030 in your report, you should not just cite Exhibit 14 below, you should also be able to demonstrate your calculations from other data that result in this number. The information in this Mckinsey & Co. report is not to say what is correct either. What you submit could be completely different from the results of this report, but if you show mathematical models and justification for how you arrived at your numbers, you will be scored well.
The American Association of Motor Vehicle Administrators keeps an online library of information and reports about autonomous vehicles. It contains many different types of reports and datasets that may be beneficial in developing your models for how autonomous vehicles will impact transportation, insurance, and society.
This article at Wired.com describes information gathered from the State of California identifying how many times a driver had to take control of an autonomous vehicle during a test drive, how many miles were driven, and where they were driven. The article also notes that it is difficult to determine why a driver had to take over from the vehicle. This data may be useful in providing some background information on the adoption of autonomous vehicles and their safety, but be cautious in using it as the foundation of any of your models due to its limited depth. This data is not claimed or owned by the Modeling the Future Challenge, please cite its use appropriately.
Background Articles & Videos
Find the latest Autonomous Vehicles news from Wired. See related science and technology articles, photos, slideshows and videos.
An autonomous car (driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars can detect their surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision.
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