- An intersection without a traffic light could be a potentially dangerous place to travel through depending on the mindsets of the of the travelers within it. When travelers are traversing an intersection, they generally have one of two different mindsets that influence the actions they do. One mindset they could have is being focused on saving time as they travel the intersection, causing them to take actions that speed them through while the other is being focused on one’s own safety and taking actions that follow the rules of the intersection to keep themselves and others around them out of accidents. Which mindset a traveler has as they travel through the intersection depends largely on how full the intersection is with other cars and pedestrians. This thesis creates an agent-based model to simulate an intersection found on Monroe Ave. on the Oregon State University campus. This model is then used in a series of tests that fills the model with various numbers of agents to test how the intersection runs under various intersection densities. Data is recorded from each test and fitted onto line graphs which are then compared to each other to look for the approximate density where the mindset of a traveler should switch from being focused on saving time to being focused on personal safety. A conclusion was reached after testing the model under five different density levels and comparing the line graphs from the data gathered from those tests to look for the ideal behavior that the target density would have exhibited.
Key Words: intersection, agent-based modeling system, intersection simulation