Evaluation of Outlier Filtering Algorithms for Accurate Travel Time Measurement Incorporating Lane-Splitting Situations

Obada Asqool,Suhana Koting,Ahmad Saifizul

doi:10.3390/su132413851

Abstract

Malaysia has a high percentage of motorcycles. Due to lane-splitting, travel times of motorcycles are less than passenger cars at congestion. Because of this, collecting travel times using the media access control (MAC) address is not straightforward. Many outlier filtering algorithms for travel time datasets have not been evaluated for their capability to filter lane-splitting observations. This study aims to identify the best travel time filtering algorithms for the data containing lane-splitting observations and how to use the best algorithm. Two stages were adopted to achieve the objective of the study. The first stage validates the performance of the previous algorithms, and the second stage checks the sensitivity of the algorithm parameters for different days. The analysis uses the travel time data for three routes in Kuala Lumpur collected by Wi-Fi detectors in May 2018. The results show that the Jang algorithm has the best performance for two of the three routes, and the TransGuide algorithm is the best algorithm for one route. However, the parameters of Jang and TransGuide algorithms are sensitive for different days, and the parameters require daily calibration to obtain acceptable results. Using proper calibration of the algorithm parameters, the Jang and TransGuide algorithms produced the most accurate filtered travel time datasets compared to other algorithms

Highlights

Like most other countries in the world, the urban areas of Malaysia experience a high level of traffic congestion
Routes A and B because it has the highest number of observations
This paper has addressed for filtering theoftravel time dataRoute for Malaysian sensitive than but less sensitive than has fewer observations than roads with common lane-splitting situations

Summary

Introduction

Like most other countries in the world, the urban areas of Malaysia experience a high level of traffic congestion. It is a grave problem that affects everyone in the country due to the economic and health implications. The traffic congestion costs Malaysia an estimated. RM 13.09 billion (USD 3.2 billion) each year. RM 10.82 billion is the total wage loss, RM 1.08 billion is the fuel loss, and RM 1.19 billion is the total loss due to environmental impact [1]. Modern urbanization leads to increase congestion dramatically, resulting in negative consequences on humanity, such as high travel costs, increased anxiety, and pollution [2,3]. Smarter technologies are required to overcome traffic problems

Objectives

Methods

Results

Conclusion