Modeling Weather Conditions Consequences on Road Trafficking Behaviors

10/08/2012
by   Guillaume Allain, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/24/2019

Remote Estimation of Free-Flow Speeds

We propose an automated method to estimate a road segment's free-flow sp...
research
10/28/2020

Multimodal End-to-End Learning for Autonomous Steering in Adverse Road and Weather Conditions

Autonomous driving is challenging in adverse road and weather conditions...
research
06/15/2023

Localization with Anticipation for Autonomous Urban Driving in Rain

This paper presents a localization algorithm for autonomous urban vehicl...
research
10/24/2022

Exploring the impact of weather on Metro demand forecasting using machine learning method

Urban rail transit provides significant comprehensive benefits such as l...
research
06/03/2017

M/G/c/c state dependent queuing model for a road traffic system of two sections in tandem

We propose in this article a M/G/c/c state dependent queuing model for r...
research
07/29/2019

Road Accidents in the UK (Analysis and Visualization)

Analysis of road accidents is crucial to understand the factors involved...
research
10/19/2019

A Statistical Analysis of Recent Traffic Crashes in Massachusetts

A statistical analysis implemented in the Python programming language wa...

Please sign up or login with your details

Forgot password? Click here to reset