An Investigation of the Relationships between Road Geometric Characteristics, Vehicle Speed, Road Lighting Conditions and Traffic Crash Occurrence for Road Safety Design

Sirinapa Jantarakot; Jetsada Kumphong

doi:10.55003/ETH.430303

Authors

Sirinapa Jantarakot Faculty of Technical Education, Rajamangala University of Technology Isan, Khon Kaen Campus, Thailand
Jetsada Kumphong Faculty of Technical Education, Rajamangala University of Technology Isan, Khon Kaen Campus, Thailand

DOI:

https://doi.org/10.55003/ETH.430303

Keywords:

Sri Chan Road, Crashes, Road lighting, Motorcycles, Khon Kaen, Accident Frequency Method

Abstract

This study aims to: 1) examine the relationship between the physical characteristics of roads, road lighting conditions, vehicle speed, and road crash data; and 2) propose guidelines for geometric road design to improve road safety. The study area focuses on Sri Chan Road in Khon Kaen Municipality, Khon Kaen Province, Thailand. Field data collection included the physical characteristics of the road, vehicle speed data, road lighting conditions, and road crash data. The data was analyzed using descriptive statistics, the Accident Frequency Method, and Pearson Product Moment Correlation and Simple Linear Regression Models to explore relationships between variables. Geometric designs were also developed according to engineering principles. The study found that the mean speed of private cars was 35.73 km/h per section of the road (SD. = 4.48), and the mean speed of motorcycles was 35.24 km/h per section (SD. = 3.88). The area studied had an average number of injuries of 41.91 people/road sections. Road width was significantly related to the number of lanes, the presence of a median, and the average speed of private cars and motorcycles. The 85th percentile speed of private cars and the 85th percentile speed of motorcycles was also statistically correlated (p-value < 0.05). Additionally, the intensity of road lighting was negatively correlated with sections where severe road crashes occurred, resulting in fatalities (r = -0.702, p-value < 0.05). Similarly, the results of the Simple Linear Regression Models indicate that the mean vehicle speed is significantly related to the number of traffic lanes at a statistically significant level. Based on these results, geometric designs were proposed to reduce vehicle speeds, such as speed-reducing lines, speed limits near important places, and roundabouts. The findings will be submitted to relevant local authorities for future road safety improvements.

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