Motorway travel time prediction based on toll data and weather effect integration

TLDR

The study aims to develop a route‑planner and travel‑time prediction system for French interurban motorways using electronic toll‑collection data integrated with weather information. Speed and travel‑time estimates are derived from toll‑collection data, and the prediction algorithm incorporates weather effects. The resulting tool accurately estimates and predicts travel time, produces OD matrices, reveals traffic trends, and supports weather‑responsive traffic management.

Abstract

This study reports the main findings of the Travel time Prediction based on electronic Toll collection (ETC) data with wEather effect integration on mOtorways (TPTEO) project aiming at developing and implementing a route planner tool and travel time prediction system on the interurban motorway network managed by French motorway AREA Company. One of the main innovative characteristics of this project is the use of toll collection data (TCD) to derive speed and travel time estimation and prediction. This data source is becoming more and more available on motorway facilities and provides an efficient way not only to estimate and predict travel time but also to achieve the origin–destination (OD) matrices elaboration and exhibit trends in traffic. Based on the previous studies on weather effect quantification, the prediction algorithm is designed to account for the weather impact during the prediction process. The resulting tool is considered to be accurate enough and paves the way for developing weather responsive advanced traffic management and information systems.