| Title |
Forecasting the clearance time of freeway accidents |
| Record ID |
23524 |
Personal Name
Creator |
Smith, Kevin; Smith, Brian L., 1967- |
| Source |
Final report of ITS Center project: Incident duration forecasting; Smart Travel Lab Report No. STL-2001-01 |
Corporate
Contributor |
National ITS Implementation Research Center; Center for Transportation Studies (University of Virginia) |
| Publication Date |
20020000 |
| Abstract |
Freeway congestion is a major and costly problem in many U.S. metropolitan areas. From a travelers perspective, congestion has costs in terms of longer travel times and lost productivity. From the traffic managers perspective, congestion causes a freeway to operate inefficiently and below capacity. There are also environmental costs
associated with congestion such as increased pollution and noise. Researchers have estimated that non-recurring congestion due to freeway incidents such as accidents, disabled vehicles, and weather events accounts for one-half to three-fourths of the total congestion on metropolitan freeways in this country.
The objective of this study is to develop a forecasting model that can predict the clearance time of a freeway accident. This can aid traffic managers in making decisions regarding the appropriate response to freeway incidents. Three models were investigated in this paper; a stochastic model, nonparametric regression model, and classification tree model. The stochastic model was not applied to forecasting future accidents due to the lack of a probabilistic distribution to fit the clearance time data. The Weibull and lognormal distributions have been applied to incident duration in the past, but were not applicable to the accident clearance time data used in this study. The other two models were developed but suffered from poor performance in predicting the clearance time of future accidents. However, the classification tree model appears to be well suited for forecasting the phases of incident duration given a database of incidents with reliable and
informative characteristics. |
| TRT Terms |
Forecasting  ; Freeways ; Accidents ; Nonrecurrent congestion ; Computer models ; Metropolitan areas ; Decision making ; Traffic managers |
| General Subjects |
Classification tree model; Clearance time; Freeway incidents; Incident duration; Nonparametric regression model; Stochastic model |
| Classification |
NTL - OPERATIONS AND TRAFFIC CONTROLS - Congestion |
| Resource type |
Tech Report |
| URL |
http://ntl.bts.gov/lib/23000/23500/23524/paper-Smtih-IncidentDurationForecasting.pdf |
| Format |
PDF |
| Language: |
English |
| Database |
NTL Digital Repository |
TRT
