KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Simulation-Based Analysis on Dynamic Merge Control at Freeway Work Zones in Automated Vehicle Environment

자율주행차 환경에서 고속도로 공사구간의 동적합류제어에 대한 시뮬레이션 분석

  • 김선호 (서울대학교 공과대학 건설환경공학부) ;
  • 이재현 (서울대학교 공과대학 건설환경공학부) ;
  • 김용주 (서울대학교 공과대학 건설환경공학부) ;
  • 이청원 (서울대학교 공과대학 건설환경공학부)
  • Received : 2018.08.31
  • Accepted : 2018.09.21
  • Published : 2018.12.01
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Abstract

As the era of AVs (Automated Vehicles) comes to a close, many researches related to AVs have been conducted. Up until now, research on traffic flow impact of AVs has been the main topic, and research on traffic management for AVs is still in beginning stage. This study analyzed the effect of Dynamic Merge Control (DMC) in manual vehicle (MV) and AV environment at work zone. Dynamic Late Merge (DLM) and DLM with Dynamic Early Merge (DEM) are compared by simulation. Simulation results showed that DLM improves travel time and work zone throughput compared to no merge control case in both MV and AV environment. In the case of additional operation of DEM, the improvement effect was not observed in MV environment, but it was improved in AV environment. As a result, DMC operation in AV environment was as effective as the improvement in transition from MV to AV environment. Therefore congestion reduction at freeway work zone by DMC will be possible in future AV environment, and the improvement of DMC can be suggested.

자율주행차 시대가 가까워지면서 관련 연구가 활발히 진행되고 있다. 지금까지는 자율주행차의 교통류 영향 분석에 대한 연구가 주로 수행되었으며, 자율주행차에 대한 교통관리 연구는 아직 시작 단계이다. 본 연구는 공사구간에서 일반차와 자율주행차 환경에서의 동적합류제어 효과를 분석하였다. 동적지연합류와 동적지연합류에 동적조기합류까지 추가로 운영한 경우를 시뮬레이션을 통해 비교하였다. 시뮬레이션 결과에 따르면 동적지연합류는 일반차 환경과 자율주행차 환경 모두 운영하지 않은 경우와 비교했을 때 통행시간과 공사구간의 통과교통량을 개선시켰다. 동적조기합류까지 추가 운영한 경우는 일반차 환경에서 추가 개선효과를 확인할 수 없었으나, 자율주행차 환경에서는 추가 효과가 나타났다. 결과적으로 자율주행차 환경에서 동적합류제어 운영은 일반차 환경이 자율주행차 환경으로 변화시 개선되는 수준만큼 추가로 개선 효과가 있는 것으로 분석되었다. 따라서 향후 자율주행차 환경에서도 동적합류제어를 통한 고속도로 공사구간의 혼잡 개선이 일정부분 가능할 것으로 판단되며, 이를 통해 동적합류제어의 개선 방안을 제시할 수 있다.

Keywords

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Fig. 1. Concepts of DMC

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Fig. 2. DMC Algorithm

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Fig. 3. DMC on Hypothetical Network

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Fig. 4. Traffic Demands for Each Scenario

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Fig. 5. Travel Time for No Control Cases under Fixed Demand

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Fig. 6. Travel Time under Fixed Demand

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Fig. 7. Travel Time Improvement Rate Compared to No Control under Fixed Demand

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Fig. 8. Travel Time and Improvement for DMC Cases Compared to No Control under Variable Demand

Table 1. Driving Parameter for Manual Vehicle and Level 4 Automated Vehicle

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Table 2. Scenario Composition of Vehicle Types and DMC

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Table 3. Descriptive Statistics of Travel Time through the Network

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Table 4. DMC Operating Percentage of Time on Traffic Demand

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Table 5. Travel Time Improvement of DMC Scenarios for AV Compared to Scenario 1(No Control for MV)

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Table 6. Comparison of Cumulative Throughput at Work Zone

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