DOI QR코드

DOI QR Code

Performance Test of APIS, DELOS Algorithm using Paramics

Paramics를 이용한 APID, DELOS평가

  • Nam, Doohee (Dept. of Information & System Engineering, Hansung University)
  • 남두희 (한성대학교 정보시스템공학과)
  • Received : 2013.06.24
  • Accepted : 2013.08.16
  • Published : 2013.08.31

Abstract

The central core of the Traffic Management System is an Incident Management System. Whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Algeria freeway system. After review and analysis of existing incident detection methodologies, Paramics was utilized to test the performance of APID, DELOS algorithms. The existing system of Algeria freeway was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The Paramics simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

교통관리 시스템에서 돌발상황 관리시스템은 매우 중요한 역할을 차지하고 있다. 여러 종류의 알고리즘이 사용되고 있는데 이 중에서 APID, DELOS가 가장 많이 사용되고 있다. 검지알고리즘의 경우는 localization이 중요하며 교통상황에 적합한 파라미터의 검증과, 검지기 자료의 유효성 문제가 지적되고 있다. 본 논문에서는 APID, DELOS 돌발상황 검지알고리즘의 평가를 위해 방법론 및 시나리오를 구성하여 교통여건별, 시나리오별로 평가하였다. 특히, 알제리의 실제 도로망을 이용하여 평가를 진행하였다. 모든 조건을 만족하는 하나의 돌발상황 검지알고리즘을 개발한다는 것은 어려우며 각 도로 및 교통조건에 맞추어 최적의 알고리즘을 적용하는 것이 바람직할 것으로 판단된다.

Keywords

References

  1. D. Nam st. al. "Test of Incident Detection Algorithms", Journal of Transportation Studies, Vol. 22, No. 7, 12/ 2004
  2. KHC, "Algorithm for Freeway Managment System," Final Report, 2000
  3. Abdulhai, Baher and Ritchie, Stephen G.(1999) Enhancing the universality and transferability of freeway incident detection using a Baysian-based neural network, Transportation Research Part C, Vol. 7
  4. Dia, Hussein and Rose, Geoff(1997) Development and evaluation of neural network freeway incident detection models using field data, Transportation Research Part C, Vol. 5C
  5. Gall, Ana I., and Hall, Fread L.(1989) Distinguishing between incident congestion and recurrent congestion: a proposed logic, Transportation Research Record 1232
  6. Persaud, Bhagwant N., and Hall, Fread L.(1989) Catastrophe theory and patterns in 30-second freeway traffic data - implications for incident detection, Transportation Research Part A, Vol. 23A