00757542

Component

https://doi.org/10.3141/1644-10

http://scholar.google.com...uang&publication_year=1998

The objective of this paper is threefold. First, the feasibility of modeling a large-scale network at a microscopic level of detail is presented. Second, the unique data collection challenges that are involved in constructing and calibrating a large-scale network microscopically are described. Third, the unique opportunities and applications from the use of a microscopic as opposed to a macroscopic simulation tool are described. The possibility and feasibility of modeling a large-scale network using a microscopic simulation model is demonstrated. The requirements of a validated microscopic model for large-scale modeling are: (a) the model must be capable of modeling origin-destination demand tables, (b) the model must be capable of modeling dynamic traffic routing, and (c) the model must be capable of modeling the dynamic interaction of freeway/arterial facilities. The data collection and coding exercise for microscopic models is more intensive than for macroscopic models. The calibration exercise for a microscopic model to a large-scale network, although feasible, is by no means an easy task and does require expert assistance. The Salt Lake metropolitan region study has demonstrated that the data collection, coding, and calibration exercise is approximately a 4-person-year exercise. Model execution times during peak periods are still quite high (from 2 to 17 times the simulation time depending on the number of vehicles) for the PC platform (Pentium 200 with 64 megabytes of random-access memory). Consequently, tools that can extract portions of the large-scale network can allow the modeler to conduct various types of sensitivity analyses within a more realistic time frame.

This paper appears in Transportation Research Record No. 1644, Traffic Flow Theory: Simulation Models, Macroscopic Flow Relationships, and Flow Estimation and Prediction.

English

p. 93-102

1998

Transportation Research Record

030906516X

Figures (7) ; References (7) ; Tables (2)

Arterial highways; Calibration; Data collection; Feasibility analysis; Freeways; Microscopic traffic flow; Origin and destination; Routing; Simulation; Streets; Traffic simulation

Interactions

Salt Lake City (Utah)

Highways; Operations and Traffic Management; I71: Traffic Theory

TRIS, TRB, ATRI

Dec 14 1998 12:00AM

• BAYESIAN REGRESSION-BASED URBAN TRAFFIC MODELS
• CAR-FOLLOWING UNDER CONGESTED CONDITIONS: EMPIRICAL FINDINGS
• CHANGES IN FLOW-DENSITY RELATIONSHIP DUE TO ENVIRONMENTAL, VEHICLE, AND DRIVER CHARACTERISTICS
• COMPARISON OF INTEGRATION, TSIS/CORSIM, AND WATSIM IN REPLICATING VOLUMES AND SPEEDS ON THREE SMALL NETWORKS
• CONTINUOUS LEARNING FRAMEWORK FOR FREEWAY INCIDENT DETECTION
• EMERGENT FUNDAMENTAL PEDESTRIAN FLOWS FROM CELLULAR AUTOMATA MICROSIMULATION
• ESTIMATION OF TIME-DEPENDENT TURNING FRACTIONS AT SIGNALIZED INTERSECTIONS
• FROM PARTICLE HOPPING MODELS TO TRAFFIC FLOW THEORY
• IMPROVED HIGH-ORDER MODEL FOR FREEWAY TRAFFIC FLOW
• INTEGRATION OF DYNAMIC TRAFFIC ASSIGNMENT WITH REAL-TIME TRAFFIC ADAPTIVE CONTROL SYSTEM
• INTRODUCING BUSES INTO FIRST-ORDER MACROSCOPIC TRAFFIC FLOW MODELS
• LINEAR ACCELERATION CAR-FOLLOWING MODEL DEVELOPMENT AND VALIDATION
• MODELING MULTIPLE USER-CLASS TRAFFIC
• MULTIREGIME APPROACH FOR MICROSCOPIC TRAFFIC SIMULATION
• SIMULATION OF AN ARTERIAL INCIDENT ENVIRONMENT WITH PROBE REPORTING CAPABILITY
• URBAN FREEWAY TRAFFIC FLOW PREDICTION: APPLICATION OF SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND EXPONENTIAL SMOOTHING MODELS