PURPOSES : Disabled people have a low employment rate and poor working conditions, making it difficult for them to get a job compared to non-disabled people. In this study, we examined the characteristics of the commuting environment for the disabled because they experience many difficulties in the commuting environment owing to the physical influence of the disabled. METHODS : Disabled people are expected to have a higher meaning in commuting satisfaction than commuting time. Therefore, in this study, commuter satisfaction was used as a dependent variable, and an ordered logit model was used because it was composed of a five-point scale. RESULTS : As a result of the analysis, both disabled and non-disabled people were identified as influencing factors in salary, satisfaction with the environment around the residence, work characteristics, and public transportation. The main difference was that disabled people were affected by the household income, length of residence, and commuting area, whereas non-disabled people were affected by the personal income, home ownership, and area of residence. Therefore, it appeared that the household income, stability of residence, and short-distance commuting had a strong influence on the satisfaction of the commuting environment of the disabled. CONCLUSIONS : This study showed that if we understand the determinants of commuting environment satisfaction and various environmental factors, it is expected that effective policies to improve the employment rate of the disabled can be determined.

PURPOSES : This study verifies the appropriateness of the observed traffic volume using car navigation traffic volume data. METHODS : In this study, we developed an annual average daily traffic (AADT) estimation model that can verify the total amount of traffic by using navigation traffic volume data. In addition, a method to verify the appropriateness of the observed traffic volume was developed using time-based navigation traffic volume data that can check the characteristics of traffic volume at each point. RESULTS : As a result of the analysis of this study, it was found that 674 of the 697 short-duration survey spots of the freeways were appropriate and that 23 spots needed to be revised. CONCLUSIONS : As a result of the analysis of this study, it was found that there was a strong positive correlation between the observed traffic volume and the car navigation traffic volume. Thus, the appropriateness of the observed traffic was determined by verifying the total amount of observed traffic and the observed traffic volume by time.

PURPOSES: This study was initiated to estimate expressway traffic congestion costs by using Vehicle Detection System (VDS) data. METHODS : The overall methodology for estimating expressway traffic congestion costs is based on the methodology used in a study conducted by a study team from the Korea Transport Institute (KOTI). However, this study uses VDS data, including conzone speeds and volumes, instead of the volume delay function for estimating travel times. RESULTS : The expressway traffic congestion costs estimated in this study are generally lower than those observed in KOTI's method. The expressway lines that ranked highest for traffic congestion costs are the Seoul Ring Expressway, Gyeongbu Expressway, and the Youngdong Expressway. Those lines account for 64.54% of the entire expressway traffic congestion costs. In addition, this study estimates the daily traffic congestion costs. The traffic congestion cost on Saturdays is the highest. CONCLUSIONS : This study can be thought of as a new trial to estimate expressway traffic congestion costs by using actual traffic data collected from an entire expressway system in order to overcome the limitations of associated studies. In the future, the methodology for estimating traffic congestion cost is expected to be improved by utilizing associated big-data gathered from other ITS facilities and car navigation systems.