Simulating the Effects of Eco-Friendly Transportation Selections for Air Pollution Reduction

TL;DR

This paper presents a simulation method using map search logs to evaluate how eco-friendly transportation choices can reduce air pollution, demonstrating significant emission reductions and travel time improvements.

Contribution

It introduces a novel combinatorial optimization approach to simulate and assess the impact of eco-friendly transport mode selection on air pollution reduction.

Findings

CO2 emissions reduced by 9.23%

Average travel time decreased by 9.96%

Won first prize at KDD Cup 2019

Abstract

Reducing air pollution, such as CO2 and PM2.5 emissions, is one of the most important issues for many countries worldwide. Selecting an environmentally friendly transport mode can be an effective approach of individuals to reduce air pollution in daily life. In this study, we propose a method to simulate the effectiveness of an eco-friendly transport mode selection for reducing air pollution by using map search logs. We formulate the transport mode selection as a combinatorial optimization problem with the constraints regarding the total amount of CO2 emissions as an example of air pollution and the average travel time. The optimization results show that the total amount of CO2 emissions can be reduced by 9.23%, whereas the average travel time can in fact be reduced by 9.96%. Our research proposal won first prize in Regular Machine Learning Competition Track Task 2 at KDD Cup 2019.