Development of Test Cases for Automated Vehicle Driving Safety Assessment Using Driving Trajectories.

For consumers to have confidence in the safety of automated vehicles (AVs), AVs must be assessed using systematically developed scenarios to verify driving safety and reliability. In particular, verification using scenarios has been widely performed for the assessment and certification of AVs. This study aims to develop test cases based on driving trajectories to assess the driving safety of AVs.

Exploring the impact of green logistics practices and relevant government policy on the financial efficiency of logistics companies.

The coexistence of carbon neutrality and capitalism can be realized if environmentally friendly management is proven to enhance profitability. The focus of green logistics practices (GLPs) is on maximizing energy efficiency in logistics services, potentially leading to cost reductions for companies. Such practices can be supported through public reports, such as Environmental, Social, and Governance (ESG) reports, and government policies, including government certification.

Social Efficiency of Public Transportation Policy in Response to COVID-19: Model Development and Application to Intercity Buses in Seoul Metropolitan Area.

Although more than two years have passed since the appearance of the coronavirus disease 2019 (COVID-19), few policies on public transportation have been implemented to reduce its spread. It is common knowledge that public transportation is vulnerable to COVID-19, but it has not been easy to formulate an appropriate public transportation policy based on a valid rationale. In this study, a modified SEIHR model was developed to evaluate the socioeconomic effects of public transportation policies.

Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles.

Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the driving safety of AVs under the various situations that they potentially face. In this context, these various situations are mostly implemented by using systematically developed scenarios.

Development of freeway-based test scenarios for applying new car assessment program to automated vehicles.

As automated driving technology continues to develop, studies are being conducted to develop various scenarios for assessing the functional safety, failure safety, and mobility of automated vehicles (AVs). As the commercialization of AVs progresses, it is necessary to develop a set of test scenarios for new car assessment programs (NCAPs), so as to provide information on the safety and reliability of AVs to consumers. To provide valuable information regarding newly emerged AVs to consumers who are willing to purchase them, it is necessary to derive specific and well-defined test scenarios based on the safety-in-use.

Safety Monitoring System of CAVs Considering the Trade-Off between Sampling Interval and Data Reliability.

The safety of urban transportation systems is considered a public health issue worldwide, and many researchers have contributed to improving it. Connected automated vehicles (CAVs) and cooperative intelligent transportation systems (C-ITSs) are considered solutions to ensure the safety of urban transportation systems using various sensors and communication devices. However, realizing a data flow framework, including data collection, data transmission, and data processing, in South Korea is challenging, as CAVs produce a massive amount of data every minute, which cannot be transmitted via existing communication networks.

Risk of COVID-19 Infection in Public Transportation: The Development of a Model.

South Korea's social distancing policies on public transportation only involve mandatory wearing of masks and prohibition of food intake, similar to policies on other indoor spaces. This is not because public transportation is safe from coronavirus disease 2019 (COVID-19), but because no suitable policies based on accurate data have been implemented. To relieve fears regarding contracting COVID-19 infection through public transportation, the government should provide accurate information and take appropriate measures to lower the risk of COVID-19.

Passenger, airline, and policy responses to the COVID-19 crisis: The case of South Korea.

In recent years, domestic and international air passenger markets have expanded steadily around the world with the rapid growth of low cost carriers and aggressive route expansion; however, the unprecedented crisis caused by the coronavirus disease 2019 (COVID-19) pandemic resulted in greatly decreased air travel and an uncertain future for the aviation industry. The present study examined South Korean passengers, airlines, and government policy responses to the COVID-19 pandemic, and it suggests policy directions for the pandemic and post-pandemic periods. Air passengers respond to internal and external factors, and their demand for travel will increase with the reduction in global COVID cases and vaccine distribution.

Regional economic structure and airport-centric development strategy formulation: The case of South Korea.

Strategic positioning, in terms of the regional economic structure, is necessary to fully consider regional economic benefit in developing areas surrounding the airport. We propose a novel strategy formulation for an airport surrounding area development that moves the focus away from an approach focused on the airport toward an approach based on regional economic structure. The concept of comparative advantage and SWOT analysis was introduced by utilizing quantitative indices looking at the regional industrial ecosystem to enhance scientific analysis progress from the strategy building prospective.

Decision making framework for the proactive policy conflict management: The case of new airport projects in South Korea.

We propose a decision-making framework on infrastructure policy conflict management based on a scientific approach. We developed a decision-making framework that consists of the systematic conflict structure diagnosis, decision-making accordingly, and feedback to be used consistently in the policy life cycle and applied it to new airport projects in South Korea. We suggested a model structure of conflict factors leading to the generation of conflict situations and damages in the process and developed the conflict level diagnosis table and the conflict level matrix formed of the possibility of conflict generation and the severity based on the table.

Quantitative evaluation of the mitigation effect of low-impact development pavement materials on urban heat island and tropical night phenomena.

Rapid urbanization has led to altered thermal circulations in major cities that are responsible for the increasing occurrence of urban heat islands (UHIs) and events such as tropical nights and heat waves. To effectively mitigate such events, low-impact development (LID) and green infrastructure strategies have been developed. In Korea, LID techniques focus mainly on road pavement materials; however, issues regarding the reliability of measurements due to differences in the measurement equipment and studied specimens persist.

Road safety performance across local governments: a data envelopment analysis approach.

Road safety performance varies among local municipalities since road safety involves multiple inputs (e.g. facilities and programs) and multiple outputs (e.

Association between transportation noise and blood pressure in adults living in multi-storey residential buildings.

Epidemiological studies have demonstrated that transportation noise is associated with blood pressure and hypertension, but little is known about its relationship in the adults living in multi-storey residential buildings, where neighbour noise is frequently heard. This study aimed to investigate the effects of transportation noise exposure on blood pressure in 400 adult residents of multi-storey residential buildings and modifying effects of indoor noise annoyance and self-rated noise sensitivity on the associations between transportation noise and blood pressure. Noise levels were measured on the top of buildings for 24 h, and levels of each house unit were then predicted for different sources and periods using noise maps.

Safety Analysis of Motorcycle Crashes in Seoul Metropolitan Area, South Korea: An Application of Nonlinear Optimal Scaling Methods.

This study identifies the critical factors that affect motorcycle crash severity based on Korean motorcycle crash data in 2009. Motorcyclists, the environment, roadways, other vehicles involved in the crashes, and traffic flow characteristics were used as variables for identifying critical factors. Multivariable statistical methods were used to analyze the data, including categorical principal components analysis (CatPCA) and nonlinear canonical correlation analysis (NLCCA).

Evaluation of countermeasures for red light running by traffic simulator-based surrogate safety measures.

Objective: The conflicts among motorists entering a signalized intersection with the red light indication have become a national safety issue. Because of its sensitivity, efforts have been made to investigate the possible causes and effectiveness of countermeasures using comparison sites and/or before-and-after studies. Nevertheless, these approaches are ineffective when comparison sites cannot be found, or crash data sets are not readily available or not reliable for statistical analysis.

An estimation of vehicle kilometer traveled and on-road emissions using the traffic volume and travel speed on road links in Incheon City.

The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.

Distribution-dependent robust linear optimization with applications to inventory control.

This paper tackles linear programming problems with data uncertainty and applies it to an important inventory control problem. Each element of the constraint matrix is subject to uncertainty and is modeled as a random variable with a bounded support. The classical robust optimization approach to this problem yields a solution with guaranteed feasibility.

Note on evaluating safety performance of road infrastructure to motivate safety competition.

Road infrastructures are usually developed and maintained by governments or public sectors. There is no competitor in the market of their jurisdiction. This monopolic feature discourages road authorities from improving the level of safety with proactive motivation.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots.

Hot spot identification (HSID) aims to identify potential sites-roadway segments, intersections, crosswalks, interchanges, ramps, etc.-with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice.

Injury severity in delivery-motorcycle to vehicle crashes in the Seoul metropolitan area.

More than 56% of motorcycles in Korea are used for the purpose of delivering parcels and food. Since such delivery requires quick service, most motorcyclists commit traffic violations while delivering, such as crossing the centerline, speeding, running a red light, and driving in the opposite direction down one-way streets. In addition, the fatality rate for motorcycle crashes is about 12% of the fatality rate for road traffic crashes, which is considered to be high, although motorcycle crashes account for only 5% of road traffic crashes in South Korea.

Development of an accident duration prediction model on the Korean Freeway Systems.

Since duration prediction is one of the most important steps in an accident management process, there have been several approaches developed for modeling accident duration. This paper presents a model for the purpose of accident duration prediction based on accurately recorded and large accident dataset from the Korean Freeway Systems. To develop the duration prediction model, this study utilizes the log-logistic accelerated failure time (AFT) metric model and a 2-year accident duration dataset from 2006 to 2007.

Accident prediction model for railway-highway interfaces.

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs.

A method for identifying rear-end collision risks using inductive loop detectors.

An innovative feature of this study is to firstly attempt to capture rear-end collision potentials from the analysis of inductive loop detector data. Signals collected from loops are applied for monitoring individual vehicle information on freeways to estimate safe stopping distances in car-following situations. An index to quantify the potential of rear-end collisions is derived, and further employed for developing criteria to evaluate levels of rear-end collision risks.