Solving Traffic Problems in the State of Kerala, India: Forecasting, Regression and Simulation Models

Executive Summary Indian states have been facing traffic related issues including traffic congestions and accidents for decades. The situation has worsened with time due to the increasing population. This article investigates the causes behind the accidents and provides recommendations and measures that would bring forth an improvement in the traffic conditions. The research uses forecasting models to confirm the existence of traffic problem in the State of Kerala. The various reasons for the accidents were enumerated and classified. Using regression models, the relationship between the number of accidents, deaths, and injured were obtained. In addition, the relationship between the number of accidents and the number of vehicles on road were examined along with the type of vehicle, design of the roads, the design of traffic, and the design of road network. In addition, a simulation model is presented to study the effect of the change in design of roads on the traffic situation. As an example, a 15-minute time period can be used to count the number of vehicles of each type (buses, cars, and trucks) travelling in both directions on a major highway. This data can then be categorized into slow and fast moving traffic. The Mean time between arrivals, percentages of slow and fast vehicles, percentages of vehicles travelling in both directions can be calculated and used in ARENA simulation software to perform discrete event simulation. Various scenarios are simulated; and waiting times and potential number of accidents are found for each of the scenarios. Based on forecasting, regression and simulation models, this article provides several recommendations and managerial insights, which are believed to alleviate the traffic problems in the State of Kerala. The solution approaches from this research could be used for addressing similar traffic situations in other states of India, which could result in saving millions of lives over the next decade.