01042605

Component

https://doi.org/10.3141/2024-14

http://scholar.google.com...iams&publication_year=2007

Conventionally, most traffic forecasting models have been applied in a static framework in which new observations are not used to update model parameters automatically. The need to perform periodic parameter reestimation at each forecast location is a major disadvantage of such models. From a practical standpoint, the usefulness of any model depends not only on its accuracy but also on its ease of implementation and maintenance. This paper presents an adaptive parameter estimation methodology for univariate traffic condition forecasting through use of three well-known filtering techniques: the Kalman filter, recursive least squares, and least mean squares. Results show that forecasts obtained from recursive adaptive filtering methods are comparable with those from maximum likelihood estimated models. The adaptive methods deliver this performance at a significantly lower computational cost. As recursive, self-tuning predictors, the adaptive filters offer plug-and-play capability ideal for implementation in real-time management and control systems. The investigation presented in this paper also demonstrates the robustness and stability of the seasonal time series model underlying the adaptive filtering techniques.

01088321

English

pp 116-125

2007

Transportation Research Record: Journal of the Transportation Research Board

9780309104517

Print

Figures (5) ; References (11) ; Tables (3)

Kalman filtering; Least squares method; Real time control; Real time information; Time series; Traffic flow; Traffic forecasting

Adaptive filters; Plug and play capability; Seasonal variations; Short term; Short term forecasts

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Feb 8 2007 6:42PM

• Bayesian Approach Based on Geographic Information System to Identify Hazardous Roadway Segments for Traffic Crashes
• Data Collection Based on Global Positioning System for Travel Time and Delay for Arterial Roadway Network
• Data Collection Time Intervals for Stochastic Short-Term Traffic Flow Forecasting
• Decision Support System for Predicting Traffic Diversion Impact Across Transportation Networks Using Support Vector Regression
• Evaluating Highway Capacity Investments Using a Geographic Information Systems-Based Tool: Trip-Based Full Marginal Cost Approach
• Forecasting of Short-Term Freeway Volume with v-Support Vector Machines
• Fuzzy Optimization Approach: Comparison with the Classical Optimization Method Using the Problem of Timing a Traffic Signal
• Information Technology Used to Evaluate Nontraditional Traffic Monitoring Systems
• Methodology for Selection and Development of TransXML Schemas
• Quantum-Frequency Algorithm for Automated Identification of Traffic Patterns
• Transportation Asset Management and Visualization Using Semantic Models and Google Earth
• Visualizing and Analyzing Activities in an Integrated Space-Time Environment: Temporal Geographic Information System Design and Implementation
• Wavelet-Based Pavement Distress Image Edge Detection with À Trous Algorithm