Calibration of a Micro-simulation Model With and Without Network Incidents
Incidents, pre-programmed or random, are major sources of congestion on urban freeways. With many urban freeways in the United States operating close to capacity, the need to reduce the impact of incident-related congestion has become critical. Incident Management Strategies (IMS), when properly developed and deployed, have the potential to reduce such urban congestion. The problem addressed in this paper deals with the question of dynamically finding alternate paths in a given network when a section of the network is temporarily incapacitated because of incidents. Instant knowledge of such alternate paths with surplus capacities may enable Traffic Management Centers (TMC) to efficiently divert traffic from the affected portion of the network, thereby helping alleviate congestion. As a part of this effort, the authors adapted a micro-simulation model AIMSUN to assess the impact of deploying IMS’s on an urban network. This paper deals with a major focus area of this study, calibration of the micro simulation model. The calibration of the proposed model is demonstrated on a heavily traveled portion of an urban network in the Detroit metropolitan region. The network contains two freeways in the north-south and east-west directions (Interstate 75 and Interstate 696) instrumented with various intelligent transportation systems (ITS) devices, and a number of major arterials. The model calibration process is conducted in two separate channels. Initially, the model is calibrated without any incident data. Upon completion of no-incident calibration, the model is further validated with incident data. Travel time and traffic volume data (in 5 minute increments) were obtained from sensors installed by the Michigan Department of Transportation at strategic locations on the two freeways. A set of statistical tests are reported that shows excellent correlation between the observed data and the model output. The calibrated model with extensive field data may be used as a tool to assess the traffic consequences of various IMS’s.
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Supplemental Notes:
- This paper was sponsored by TRB committee AHB45 Traffic Flow Theory and Characteristics.
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Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Khasnabis, Snehamay
- Mishra, Sabyasachee
- Swain, Subrat Kumar
- Elibe, Elibe Ama
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Conference:
- Transportation Research Board 92nd Annual Meeting
- Location: Washington DC, United States
- Date: 2013-1-13 to 2013-1-17
- Date: 2013
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: 18p
- Monograph Title: TRB 92nd Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Incident management; Intelligent transportation systems; Microsimulation; Traffic congestion; Traffic control centers; Traffic volume; Travel time
- Identifier Terms: AIMSUN (Computer model)
- Geographic Terms: Detroit (Michigan)
- Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;
Filing Info
- Accession Number: 01478198
- Record Type: Publication
- Report/Paper Numbers: 13-4655
- Files: TRIS, TRB, ATRI
- Created Date: Apr 15 2013 1:14PM