• Journal of Korean Society of Transportation
• /
• v.30 no.4
• /
• pp.95-106
• /
• 2012

Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.6
• /
• pp.1017-1023
• /
• 2017

Duration induced by freeway crashes has a critical influence on traffic congestion. In general, crash duration composes detection and verification, response, and clearance time. Of these, the crash clearance time determined by a crash clearance team has attracted considerable attention in the freeway congestion management since the interest of the first two time stages faded away with increasing ubiquitous mobile phone users. The objective of this study is to identify the critical factors that affect freeway crash clearance time using a Cox's proportional hazard model. In total, 6,870 crash duration data collected from 30 major Korean freeways in 2013 were used. As a result, it was found that crashes during the night, with trailer or larger size truck, and in tunnel section contribute to increasing clearance time. Crashes associated with fatality, completed damage of crashed vehicle (s), and vehicles' fire or rollover after crash also lead to increasing clearance time. Additionally, an increase in the number of vehicles involved resulted in longer clearance time. On the other hand, crashes in the vicinity of tollgate, by passenger car, during spring, on flat section, and of car-facility type had longer clearance time. On the basis of the results, this paper suggested some strategic plans and mitigation measures to reduce crash clearance time on Korean freeway systems.

• Journal of Korean Society of Transportation
• /
• v.31 no.4
• /
• pp.58-66
• /
• 2013

Due to the characteristics of urban freeways such as heavy traffic and high speed, work zone on urban freeways causes the increase of not only the likelihood of crash occurrence but also traffic congestion caused by lane drop, lane change, acceleration/deceleration, and etc. This paper aims to determine the proper length of transition area that satisfies two criteria, mobility and safety, to make the operation of work zone more efficient. For the analysis, three different scenarios were developed by the number of lanes and the proper length of transition area were determined by changing the length from 100m to 500m in 100m increments. The results showed that the proper length of transition area for 3- and 4-lane freeways is 300m, whereas the proper length of 2-lane freeways is 200m. The results indicated that the different length of transition area based on the number of lanes is more desirable and efficient.

• International Journal of Highway Engineering
• /
• v.13 no.2
• /
• pp.49-56
• /
• 2011

Understanding various casual factors affecting the occurrence of freeway traffic crash is a backbone of deriving effective countermeasures. The first step toward understanding such factors is to identify crash risks on freeways. Unlike existing studies, this study focused on the unsafe vehicle maneuvering that can be detected by in-vehicle sensors. The recent advancement of sensor technologies allows us to gather and analyze detailed microscopic events leading to crash occurrence such as the abrupt change in acceleration. This study used an accelerometer to capture the unsafe events. A set of candidate variables representing unsafe events were derived from analyzing acceleration data obtained by the accelerometer. Then, the crash risk was modeled by the binary logistic regression technique. The probabilistic outcome of crash risk can be provided by the proposed model. An application of the methodology assessing crash risk was presented, and further research items for the successful field implementation were also discussed.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.3
• /
• pp.1105-1113
• /
• 2013

Understanding the characteristics of truck-involved crashes is of keen interest because such crashes are highly associated with greater potential leading to severer injury. The purpose of this study is to identify factors affecting injury severity of truck-involved crashes on freeways. In addition, a binary logistic regression technique is applied to identify causal factors affecting truck crash severity under normal and adverse weather conditions. Major findings from the analyses are discussed with truck operations strategies including speed enforcement, variable speed limit, and truck lane restriction, from the safety enhancement point of view. The results of this study would be useful for developing traffic control and operations strategies to reduce truck-involved crashes and injury severity in practice.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.203-213
• /
• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.

• Journal of Korean Society of Transportation
• /
• v.32 no.5
• /
• pp.441-451
• /
• 2014

This study proposes a novel performance measure, which is referred to as Hazardous Spacing Index (HSI), to be used for evaluating safety of traffic stream on freeways. The basic principle of the proposed methodology is to investigate whether drivers would have sufficient stopping sight distance (SSD) under limited visibility conditions to eliminate rear-end crash potentials at every time step. Both Road Weather Information Systems (RWIS) and Vehicle Detection Systems (VDS) data were used to derive visibility distance (VD) and SSD, respectively. Moreover, the K-Nearest Neighbors (KNN) method was adopted to predict both VD and SSD in estimating predictive HSIs, which would be used to trigger advanced warning information to encourage safer driving. The outcome of this study is also expected to be used for monitoring freeway traffic stream in terms of safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.2
• /
• pp.152-167
• /
• 2018

The high-speed weigh-in-motion system can collect the traveling speed and load information of individual vehicles, which can be used in a variety of ways for the traffic surveillance. However, it has a limit to apply the high-speed weigh-in-motion data directly to a safety analysis because high-speed weigh-in-motion's raw data are point measured data. In order to overcome this problem, this paper proposes a method to calculate the conflict rate and the Impulse severity based on surrogate safety measures derived from the detection time, detection speed, vehicle length, vehicle type, vehicle weight. It will be possible to analyze and evaluate the risk of rear-end collision on freeway traffic. In addition, this study is expected to be used as a fundamental for identifying crash risks and developing policies to enhance traffic safety on freeways.