• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.548-559
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• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.63-75
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• 2018

A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.7-18
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• 2009

In 2008, there are 135 service areas, which provide for drivers to convenience on expressways. But there are some problems on parking capacity, because it is failed to calculate the appropriate parking lots of the service area. The fundamental problem is that the size of parking lots is calculated by simple value; despite there are various factors of utilization, congestion, and turnover. This paper describes a study on proper coefficient for calculating the appropriate service area, considering the characteristics of drivers' behavior. We conducted statistical analysis with the surveyed data in "Status of the expressway facilities in 2004." Analysis results show there are some difference by day and night, and vehicle type with the factor of utilization, congestion, and turnover, and there are different usages according to expressway route. The results indicate that the usage of a service area have different characteristics by time and space, and vehicle type.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.13-22
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• 2017

The present study proposes a new methodology for predicting the demand for truck rest areas beside national highways. Previous demand forecasting methods were reviewed first in order to complement them with additional items. The results of the study are as follows. In the demand forecasting process, the primary task is to divide parking demands of trucks into short-term parking and long-term parking. Since short-term and long-term parking vary in utilization, congestion, and turnover rate, different influence factors should be considered according to parking time. Furthermore, the demand characteristics of rest and convenience facilities need to be reflected as well, because they in turn affect the demand for truck rest areas. In sum, the demand forecasting process for destination-type truck rest areas on national highways requires more attention than that for truck rest areas on expressways, and possible influences of various factors should be examined in this process.