DISSEMINATION OF FORECASTED TRAFFIC INFORMATION
Sherif Ishak, Haitham Al-Deek, Ahmed Abdelrahman
Abstract
Sherif Ishak, Haitham Al-Deek, Ahmed Abdelrahman
Abstract
Dissemination of real time and predicted traffic information ensures that the traveling public is aware of the prevailing and anticipated traffic conditions on the network, and consequently, assists them in making appropriate decisions to avoid congestion, whenever possible. This information is often best represented by travel times and delays roadway segments. Essentially, the timeliness of traffic information is crucial since travelers frequently need to make trip decisions based on anticipated rather than current traffic conditions. In essence, short-term travel time forecasting provides both transportation users and providers with valuable information that is fundamental to decision support systems. The forecasting horizons are typically in the range of 10 to 30 minutes. The paper presents a real-time and predictive traffic information system on I-4 in Orlando, Florida. The information is presented to travelers in an individualized format based on their trip attributes (origin, destination, and departure time). Freeway travelers can receive instantly the travel times and delays along the path of their trip in both real-time and predictive modes. While the system is capable of providing additional information that is vital to traffic management centers and supports highway performance monitoring functions, the paper focuses only on information that is pertinent to the travelers and is likely to affect their trip decision making process.
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Dissemination of real time and predicted traffic information ensures that the traveling public is aware of the prevailing and anticipated traffic conditions on the network, and consequently, assists them in making appropriate decisions to avoid congestion, whenever possible. This information is often best represented by travel times and delays roadway segments. Essentially, the timeliness of traffic information is crucial since travelers frequently need to make trip decisions based on anticipated rather than current traffic conditions. In essence, short-term travel time forecasting provides both transportation users and providers with valuable information that is fundamental to decision support systems. The forecasting horizons are typically in the range of 10 to 30 minutes. The paper presents a real-time and predictive traffic information system on I-4 in Orlando, Florida. The information is presented to travelers in an individualized format based on their trip attributes (origin, destination, and departure time). Freeway travelers can receive instantly the travel times and delays along the path of their trip in both real-time and predictive modes. While the system is capable of providing additional information that is vital to traffic management centers and supports highway performance monitoring functions, the paper focuses only on information that is pertinent to the travelers and is likely to affect their trip decision making process.
Key concepts: Transport engineering, Process (computing), Computer science, Traffic congestion, Travel time, Operations research, Path (computing), Real-time data