A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A hybrid method for real-time short-term predictions of traffic flows in urban areas
Short-term traffic forecasting is driven by an increasing need of new services for user information and new systems for dynamic control. Our research focuses on reproducing anticipated traffic conditions by means of statistical methods traditionally applied in artificial intelligence problems. Although we strongly believe that the effects of specific traffic events can only be predicted through transportation model based simulations in real-time, yet the fluctuations affecting the ordinary traffic conditions of a day-type can well be forecasted without.
A hybrid method for real-time short-term predictions of traffic flows in urban areas
Short-term traffic forecasting is driven by an increasing need of new services for user information and new systems for dynamic control. Our research focuses on reproducing anticipated traffic conditions by means of statistical methods traditionally applied in artificial intelligence problems. Although we strongly believe that the effects of specific traffic events can only be predicted through transportation model based simulations in real-time, yet the fluctuations affecting the ordinary traffic conditions of a day-type can well be forecasted without.
A hybrid method for real-time short-term predictions of traffic flows in urban areas
Attanasi, Alessandro (author) / Meschini, Lorenzo (author) / Pezzulla, Marco (author) / Fusco, Gaetano (author) / Gentile, Guido (author) / Isaenko, Natalia (author)
2017-06-01
549342 byte
Conference paper
Electronic Resource
English
A Short-Term Demand Forecasting Model from Real-Time Traffic Data
| British Library Conference Proceedings | 1993