• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.631-638
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• 2023

This paper is to introduce methodologies of travel time reliability evaluation using daily traffic volumes. The methodologies include desirable speed concept, the relation between averaged daily speeds and daily traffic volumes, the standardized way in integration of travel time deviations obtained from continuous highway sections. The study began with traffic data collection from a freeway line with long lasting congestion. And then, provided establishment of the relation between averaged daily speeds and daily traffic volumes, and usability of Point estimate method (PEM) to integrate travel time deviations of sections. Based on the relation between averaged daily speeds and daily traffic volumes, it is identified that travel time reliability begins to decrease around LOS (Level of Service) C even before LOS D or F. It may be concluded that travel time reliability could be evaluated based on daily traffic volumes in highway sections using standardized PEM. The methodologies introduced in the paper, could be useful in practicing evaluation of travel time reliability during the works of highway operation or highway planning.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.106-118
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• 2020

This study examined the impact of COVID-19 on traffic demand (Average Daily Traffic : ADT) by analyzing the available data on highway traffic volume and the spread of COVID-19 cases in Korea. This study used the data from 228 permanent traffic counts (PTCs) on highways from January to May of 2019 and 2020 to analyze the change in ADT. The first cases of infection in Korea occurred on January 20, 2020, and the maximum daily number of infections was 909 on February 29. On April 30, 2020, the daily number of infections decreased to four. The ADT decreased by 3.3% due to the impact of COVID-19. Considering that the traffic volume has increased 2.3% annually over the past decade, the actual decrease in ADT due to the COVID-19 is estimated to be 5.6% (3.3% + 2.3%). The ADT for weekends decreased significantly, compared to during the week. An analysis of the changes in ADT according to the road type revealed decreases in the following: urban roads -4.6%, rural roads -3.2%, and recreational roads -0.7%. Urban roads decreased the most, and tourist roads decreased the least.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.406-414
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• 2015

Existing relative researches for traffic were studied under favorable weather or excluding impact of weather. This study present traffic volume variation according to rainfall intensity in national highway provincial road and rainfall-factor. Continuous traffic count section match AWS after selecting to analyze provincial road 256 section. Weekdays ADT(Average Daily Traffic) and rainfall-factor are influenced by rainfall a little because of business travel. But non-weekdays ADT and rainfall-factor are influenced much more than weekdays because of leisure travel. Estimated AADT(Annual Average Daily Traffic) by adjusting rainfall-factor is lower MAPE than non-adjusting rainfall factor. So, rainfall have to be considered when estimating AADT. ADT decrease according to rainfall intensity, continuous studies considered rainfall intensity are needed when road design and operation.

• Journal of Korean Society of Transportation
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• v.15 no.2
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• pp.105-122
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• 1997

본 연구는 대각선 횡단보도의 정량적 설치기준을 정립하기 위하여 이상적인 조건에서의 교차로 각현시별 임계차선 교통량의 합($\sum_i$ CVi)을 600~1,800대로 변화를 주어 실험적 시뮬레이션 방법을 적용하였다. TRANSTY-7F 모형을 이용한 교차로 평균차량 지체도와 본 연구에서 정립한 보행지체모형을 이용한 교차로 평균 보행지체도와의 관계를 변수로 하여 대각선 횡단보도의 정량적 설치기준을 각 조건별로 산정한 결과 다음과 같은 결론이 도출되었다. 첫째, 동시신호시 교통량과 보행량의 비율이 1:1일 경우 대각횡단비율 20~40%에서는 $\sum_i$ CVi=1,050~1,150대 이하에서 대각선 횡단보도를 설치시 지체도 감소에 대한 편익을 얻을 수 있다. 둘째, 동시신호시 교통량과 보행량의 비율이 1:2일 경우 대각횡단비율 20~40%에서는 $\sum_i$ CVi=1,150~1,200대 이하에서 대각선 횡단보도를 설치시 지체도 감소에 대한 편익을 얻을 수 있다. 셋째, 선행 좌회전신호시 교통량과 보행량의 비율이 1:1일 경우 대각횡단비율 20~40%에서는 $\sum_i$ CVi=600~750대 이하에서 대각선 횡단보도를 설치시 지체도 감소에 대한 편익을 얻을 수 있다. 넷째, 선행 좌회전신호시 교통량과 보행량의 비율이 1:2일 겨우 대각횡단비율 20~40%에서는 $\sum_i$ CVi=750~900대 이하에서 대각선 횡단보도를 설치시 지체도 감소에 대한 편익을 얻을 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.10-20
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• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.67-77
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• 2003

The purpose of this study is to provide the criteria for implementing unprotected left turn at intersections with variation of traffic volume on a cross road approach. Using Transyt-7F model, the delays calculated from permissive and protected left turn signal system were compared by gradually increasing the left turn volume for a certain opposing through volume up to the volume limits to which permissive left turn is more effective, Average stopped delay of the intersection was used as the measure of effectiveness in this study. The major conclusions are (1) the lighter the traffic gets in a cross road, the more the allowable left turn volume increases. The allowable left turn volume when the ratio of cross traffic to the concerned approach traffic is 0.6 appears about 50% more than the volume when the ratio is 1.0. (2) Comparing to the criteria of the manual of traffic safety facility, the results when the traffic ratio is 0.6 seem to be most similar the criteria of manual and the results when the traffic ratio are 0.8 and 1.0 appears to be lower than the criteria of manual. (3) The possible amount of making a left turn that is inversely proportional to the opposing through traffic, decreases as the number of opposing through lanes increases. The products of volume need to be used as the criteria of permissive left turn with considerable cautions because of its low consistency.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.561-573
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• 2018

In order to design the ventilation in the road tunnel, it is necessary to know the ratio of average annual daily traffic by vehicle type. In general, the road tunnels are onedirectional tunnel, so the traffic of each vehicle type does not change along the tunnel. On the other hand, in the case of network road tunnels, since the connections in the tunnels are complex, the traffic of vehicle-type varies depending on the network composition of tunnels. In the studying the easy method for calculating the ratio of vehicle type for the network road tunnel are proposed with using incidence matrix.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.119-128
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• 2008

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in rainy days of 2006. We compare the normal travel patterns with those of rainy days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in rainy days as we expect, and also show different travel patterns for weekday and weekend.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.79-88
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• 2007

Design Hourly Volume (DHV) is the hourly volume used for designing a section of road. DHV is also used to estimate the expected number of vehicles to pass or traverse the relevant section of road in a future target year. The Design Hour Factor (DHF) is defined as the ratio of DHV to Average Annual Daily Traffic (AADT). In addition to high precision of predicted traffic volume, in order to design a roadway to be the proper scale, applying appropriate DHFs considering traffic flow characteristics and type of area which surrounds the relevant roadway is important. This study categorizes sections of expressway (Suh Hae An Expressway) according to their area type and estimates DHFs utilizing traffic data obtained from a vehicle detection system (VDS). This study shows that DHFs calculated using VDS data are different from those using traffic data acquired from a coverage survey. While AADTs from both data show similar values, peak hour volumes from both data show significant differences especially for recreational areas. DHFs from the coverage survey are quite different from the values provided by the Korean design guide or previous research results and DHFs for urban areas are higher than recreational areas. However, DHFs from VDS shows similar values to previous research results. The result of this study suggests that using VDS for estimating DHFs is more reliable than using a coverage survey.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.759-766
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• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.