CCCSEF 2019
Traffic congestion is a huge part of millions of people’s everyday life. The struggle to get to work is tiring and irritating, as traffic jams can last up to several hours. The goal of the experiment was to determine if Intelligent Self-Driving (ISD) cars can be used to decongest traffic. To test if ISD cars can be used to decongest traffic, a control simulation that represented a traffic jam was created. The average speed of the system through 500 iterations of the simulation was recorded. An ISD car was introduced and trained to help increase the average speed of the system. The ISD was then tested in the congested simulation and average speed of the system was recorded through 500 iterations. The control simulation had an average speed of 4.05 mi/h, which scales to 40.5 mi/h in a real-life situation. Through the introduction of ISDs, the system’s average speed increased to 6.14 mi/h (scales to 61.4 mi/h). The system where ISDs were added randomly, averaged 6.31 mi/h ( scales to 63.1 mi/h). The standard deviation of the system speeds were 0.33, 0.18, and 0.15 for the control, ISDs entering slow, and ISDs entering randomly systems respectively. The ISDs helped increase overall system speed and reduce speed fluctuations. These results indicate that ISDs can help decongest traffic systems effectively and can have major benefits for cities and counties.