Modeling Weather Conditions Consequences on Road Trafficking Behaviors

TL;DR

This paper introduces a model that predicts how adverse weather conditions impact traffic flow by adjusting vehicle speeds, using a thresholded linear approach that adapts locally across road networks for accurate forecasting.

Contribution

It presents a novel thresholded linear model based on MARS for dynamically modeling weather effects on traffic speeds across networks.

Findings

Model accurately forecasts traffic speeds under varying weather conditions.

The approach adapts locally to different road segments for precise predictions.

Provides a practical tool using live weather data for traffic management.

Abstract

We provide a model to understand how adverse weather conditions modify traffic flow dynamic. We first prove that the microscopic Free Flow Speed of the vehicles is changed and then provide a rule to model this change. For this, we consider a thresholded linear model, corresponding to an application of a MARS model to road trafficking. This model adapts itself locally to the whole road network and provides accurate unbiased forecasted speed using live or short term forecasted weather data information.