State transportation agencies are cautiously dipping their toes into the waters of “artificial intelligence” and “machine learning” to find applications in the transportation field. There are many potential uses, according to a new report, including opportunities to track assets like crosswalks, and to clear traffic incidents faster, which could lessen the need for major capacity investments. Agencies have also identified some lessons and pitfalls of the technology as they pilot new tools.
artificial intelligence
Bellevue, WA, plans to use AI to leverage cameras for safety
Agencies that aspire to achieve zero traffic fatalities need to know where to invest for the biggest crash reductions. Advances in artificial intelligence are allowing DOTs to leverage their existing camera technology in order to extract large quantities of data that can then inform decisions about how to improve or control intersections. The city of Bellevue, WA, recently announced a plan to study footage from its traffic cameras in order to “analyze the correlation between past collisions” and near misses, according to a press release.
Computers are making roadside data collection quicker, easier, and more accurate
Researchers recently developed ways of combining the vast information available from Google Street View with custom AI programs to generate highly accurate inventories of street signs. The effort focused specifically on stop and yield signs, but these kinds of algorithms could be used to identify other types of infrastructure and even replace or augment time-consuming street audits.