Traffic Management using Logistic Regression with Fuzzy Logic

Abstract

Traffic congestion is one of the major problems in most of the cities across the globe and it leads to several other problems like pollution, time wastage, long traffic queues on roads and may cause accidents. Improvement of Road infrastructure is not always the feasible solution to resolve the problem. In real life scenario shorter distance route towards the destination attracts majority of people and at times it may aggravate traffic jam conditions. Therefore, a real time traffic information for intelligent decision making to decide the route preference is required. Moreover, a system which considers the factor of distance towards the destination along with real time traffic situation on that route will add to the solution to the congestion problem. certain parameters such as distance, weather condition, road location, day of week and time are considered to formulate the problem and to find solutions to these problems This paper outlines a combination of logistic regression with fuzzy logic such that a smart decision to preferred path can be taken. It is used to compute the probability of each possible path by considering the real time traffic information, distance and road condition and later is used to take decisions in an uncertain scenario. Proposed Method considers the number of parameters like distance, weather condition, road location, day of week and time.