Intelligent driver agent model for autonomous navigation in a computer simulated vehicular traffic network : a thesis presented in total fulfillment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany (Auckland), New Zealand
The purpose of this study was to investigate the possibilities of automating vehicular traffic
and decrease traffic congestion by developing an intelligent driver agent model that autonomously
navigates through a computer simulated traffic network. The aim was to examine
various path nding algorithms and cost evaluation functions through di erent traffic
conditions so that a basic intelligent driver agent model is designed using the best combination
of algorithms and cost functions found.
A computer simulation of vehicular traffic has been implemented to study different
agent models. The intelligent driver agents developed act as independent entities with
their own emergent properties and individual behaviours. Each simulated vehicle was navigated
through the traffic network to its destination using a user defined algorithm and cost
function. The case studies conducted focused on measuring the travel times of each driver
agent from the starting to the destination point.
The results indicated that the agents traveled at higher average speeds under low density
traffic conditions, while lowering their average speed as the traffic density increased. It was
also discovered that hybrid cost evaluation functions (designed by combining two or more
basic cost functions) perform better in low and medium density traffic, while basic cost
functions perform better under high density traffic conditions. Finally, the results revealed
that Dijkstra pathfinding using a hybrid combination of time and length cost functions
should be used under low and medium density traffic conditions and D* pathfinding using
congestion cost evaluation function under high density traffic conditions.
The conclusion was that the intelligent driver agent model implemented is suitable to
be used as a navigation model for self-driving vehicles in traffic simulation software, but
also given the right technology and social acceptance it is suitable to be implemented as a
navigation model for robot vehicles and deployed in real world traffic situations.