Floating Car Data and Fuzzy Logic for classifying congestion indexes in the city of Shanghai

Maja Kalinic,Jukka M Krisp

doi:10.5194/ica-proc-2-57-2019

Abstract

Abstract. In this paper, we use Floating Car Data from the city of Shanghai and Fuzzy Inference model to detect congestion indexes throughout the city. We aim to investigate to which extent traffic congestion is severe during afternoon rush hour. Additionally, we compare our results to the ones obtained by calculating congestion indexes on conventional way. Although we do not argue that our model is the best measure of congestion, it does allow the mechanism to combine different measures and to incorporate the uncertainty in the individual measures so that the compound picture of congestion can be reproduced.

Highlights

Is there any congestion on my way to work today? How can I avoid it? If I cannot avoid it, how much time will I need to spend in it? These are just some of the questions coming from ever-growing demand of drivers
Conventional methods of gathering data are still necessary but rather insufficient for obtaining good traffic information. Their restricted coverage and expensive costs of implementation and maintenance makes them less attractive than alternative methods. One such alternative and cost – effective method is based on collecting data from "in-vehicle" devices through mobile phones or GPS and it is broadly known as Floating Car Data (FCD) acquisition method (Cohn and Bischoff, 2012)
Its role is becoming increasingly crucial in the development of new Intelligent Transportation Systems (ITS)

Summary

Introduction

These are just some of the questions coming from ever-growing demand of drivers Such questions require traffic data to be accurate, reliable, timely and as complete as possible. Conventional methods of gathering data (such as loop detectors) are still necessary but rather insufficient for obtaining good traffic information. Their restricted coverage and expensive costs of implementation and maintenance makes them less attractive than alternative methods. Floating Car Data (FCD) is an alternative and rather complement source of high quality data to the existing technologies. It is capable of improving safety, efficiency and reliability of the transportation system. We further discuss our findings in relation to results obtained from conventional methods of detecting congestion indexes

Floating Car Data in Traffic Monitoring

Congestion Index measures

Fuzzy Logic Theory and Fuzzy Inference System in Traffic events modelling

Fuzzy Inference Model for detecting Congestion Index in districts of Shanghai

Findings

Analyses results