Development of Traffic Congestion Prediction Solution Using Cellular Neural Network Technology

Traffic congestion is a serious, hot issue for many cities and peripheral roads. Traffic congestion causes many consequences, costs, and discomfort for everyone. Many solutions have been implemented from planning, building roads to installing measuring and warning devices… In this paper, we propose solutions to solve partial differential equations describing traffic conditions using a dedicated chip configured according to cellular neural network technology. Based on previous results, that solved for one street, we develop for part of city with general condition as add more crossroad (3, 4 branches) and develop to partial differential equation systems as well. The solution has been applied for the same input condition and parameters thus, it is reliable and feasible.