RegTraffic: A Regression Based Traffic Simulator for Spatiotemporal Traffic Modeling, Simulation and Visualization

TL;DR

RegTraffic is an interactive web-based traffic simulator that uses regression analysis to predict and visualize congestion in interconnected road segments, aiding traffic management and planning.

Contribution

It introduces a novel regression-based approach for dynamic, interactive, and visual spatiotemporal traffic modeling of correlated road segments.

Findings

Predicts traffic congestion with MSE of 1.3 Km/h

Achieves RMSE of 1.71 Km/h in congestion prediction

Provides effective visualization on geographical maps

Abstract

Traffic simulation is a great tool to demonstrate complex traffic structures which can be extremely useful for the planning, development, and management of road traffic networks. Current traffic simulators offer limited features when it comes to interactive and adaptive traffic modeling. This paper presents RegTraffic, a novel interactive traffic simulator that integrates dynamic regression-based spatiotemporal traffic analysis to predict congestion of intercorrelated road segments. The simulator models traffic congestion of road segments depending on neighboring road links and temporal features of the dynamic traffic flow. The simulator provides a user-friendly web interface to select road segments of interest, receive user-defined traffic parameters, and visualize the traffic for the flow of correlated road links based on the user inputs and the underlying correlation of these road links. Performance evaluation shows that RegTraffic can effectively predict traffic congestion with a Mean Squared Error of 1.3 Km/h and a Root Mean Squared Error of 1.71 Km/h. RegTraffic can effectively simulate the results and provide visualization on interactive geographical maps.