Crash Prediction Models for Horizontal Curve Segments on Two-Lane Rural Roads in Thailand

Nopadon Kronprasert,Patipat Kanha,Katesirint Boontan

doi:10.3390/su13169011

Abstract

The number of road crashes continues to rise significantly in Thailand. Curve segments on two-lane rural roads are among the most hazardous locations which lead to road crashes and tremendous economic losses; therefore, a detailed examination of its risk is required. This study aims to develop crash prediction models using Safety Performance Functions (SPFs) as a tool to identify the relationship among road alignment, road geometric and traffic conditions, and crash frequency for two-lane rural horizontal curve segments. Relevant data associated with 86,599 curve segments on two-lane rural road networks in Thailand were collected including road alignment data from a GPS vehicle tracking technology, road attribute data from rural road asset databases, and historical crash data from crash reports. Safety Performance Functions (SPFs) for horizontal curve segments were developed, using Poisson regression, negative binomial regression, and calibrated Highway Safety Manual models. The results showed that the most significant parameter affecting crash frequency is lane width, followed by curve length, traffic volume, curve radius, and types of curves (i.e., circular curves, compound curves, reverse curves, and broken-back curves). Comparing among crash prediction models developed, the calibrated Highway Safety Manual SPF outperforms the others in prediction accuracy.

Highlights

This study aims to develop crash prediction models as a tool to examine the relationship among road geometric conditions, traffic conditions, and crash frequency for horizontal curve segments on two-lane rural roads in Thailand
Data used in the analysis consist of (1) road alignment data including curve length, curve radius, types of curves; (2) road attributes including lane width and shoulder width and traffic data in terms of annual average daily traffic (AADT); and (3) the historical crash data from 2016 to 2018 on each two-lane horizontal curve segment on rural road networks as details in the previous section
Curve segments are among the most hazardous locations which lead to road crashes and economic losses, which are totally unacceptable

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The number of road traffic accidents continues to rise significantly in the last decade. About 1.35 million people are killed on the roads each year, resulting in tremendous social and economic losses [1]. This consequence signals a requirement for urgent action to reduce crash frequency and severity, especially for low- to middle-income countries. Roads in Thailand were ranked the second most lethal in the world in 2015 and were ranked the ninth in 2018 by the World Health Organization with about 16,000 deaths per year [2]

Objectives

Methods

Results

Conclusion