Measuring the marginal cost of congestion.
-
2008-12-01
Details
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
- Traffic flow
- Traffic density
- Traffic volume
- Traffic models
- Toll roads
- Congestion pricing
- Traffic flow--Texas--Mathematical models
- Traffic flow--California--Mathematical models
- Toll roads--Texas--Mathematical models
- Toll roads--California--Mathematical models
- Congestion pricing--Texas--Mathematical models
- Congestion pricing--California--Mathematical models
-
Publication/ Report Number:
-
Resource Type:
-
Geographical Coverage:
-
Corporate Publisher:
-
Abstract:This study attempted to estimate the effect of additional vehicles joining the traffic stream when it is near ; capacity. The study used data from highways I-35, I-45 in Texas and I-80 in California aggregated at different time ; intervals. Various macroscopic traffic flow models, Catastrophe model and the bottleneck model were studied in ; order to identify models that best represent the speed-flow relation for the traffic data over complete range of flow. ; The Catastrophe model and the bottleneck model did not fit the data well, while three macroscopic models, ; the Modified HCM, Newell-Franklin and Van Aerde model were found to fit the data well. Using congestion ; pricing theory the optimum toll rates were calculated for each of these three models. The optimum toll rates were ; then compared with the toll rates on some of the existing variably priced toll roads the US. The optimum toll rates ; estimated using Modified HCM, Newell-Franklin and Van Aerde model were $0.65, $0.81 and $0.97 per mile ; assuming the value of travel time savings as $20/hr for the near capacity flow. These toll rates were found to be ; lower when compared with the maximum toll rates on three of the existing variable toll facilities which charge ; about $1/mile during the hours of extreme congestion.
-
Format:
-
Funding:
-
Download URL:
-
File Type:
-
Collection(s):
-
Main Document Checksum:urn:sha256:5c75219b26b340ff91cc332b0f6a2d97dec97a105960997b9e73038f240fc15c