Abstract
Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. These reports must be processed before any statistical analysis, which is cumbersome and time-consuming. Our dataset presents the processed disengagement data from 2014 to 2019, crash data till the 10th of March 2020 and supplementary road network and land-use data extracted from OpenStreetMap. Primary data are manually assessed and converted into an easily processed format. Our processed data will be advantageous to the research community and enable accelerated research in this domain. For example, the data can be utilised to discern trends in disengagement, observe the distribution of disengagement causes, and investigate the contributory factors of the crashes. Such investigations can subsequently improve the reporting protocols and make policies and laws for the smooth deployment of this disruptive technology.
Highlights
Background & SummaryAutonomous Vehicles (AVs) are being widely tested on public roads in several countries around the world
The latitude and longitude of every crash location were extracted from Google maps, and the “street view” feature of Google maps was used to discern location characteristics
The car model of the non-AVs involved in the crash mentioned in the reports was used to discern the “vehicle type” and resources like Wikipedia and manufacturers’ websites were used
Summary
Autonomous Vehicles (AVs) are being widely tested on public roads in several countries around the world. Neglecting latent within period variation may result in the loss of crucial explanatory variables This loss of information by using discrete-time intervals can institute error in model estimation because of unobserved heterogeneity[16,17], and studies using this data are required to be updated in the light of new information available. In this context, we present the processed disengagement data from 2014 to 2019, crash data till the 10th of March 2020 and supplementary road network and land-use data of the AV testing locations in California. The processed data can bring consistency in the studies since different authors might use different appellations and can be readily imported to modelling and analysis software, thereby facilitating reproducible research
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