Some validation tests of the OTM, ver. 5.0 Goran Vuk, DTF, DTU Christian O. Hansen, CTT, DTU Presentation outline: 1. Introduction to the model 2. Base.

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Presentation transcript:

Some validation tests of the OTM, ver. 5.0 Goran Vuk, DTF, DTU Christian O. Hansen, CTT, DTU Presentation outline: 1. Introduction to the model 2. Base year 2004 validation Travel distances and trip rates Model elasticities Assignment results 3. Back casting to the year Conclusions Goran,

Introduction to the model The OTM is a tactical traffic model for the Greater Copenhagen Area, where the model’s first version was built in 1996 with the main objective to forecasts the future demand for metro’s phases 1 and 2. The model’s fourth version was built in summer OTM 4 was broadly applied in a number of road and public transport infrastructure projects, one of them being the Metro City Ring project.

Introduction to the model Model criticism Validation of the model structure and model forecasts (Vuk & Overgaard 2003, and Vuk & Overgaard 2006) was carried out due to the fact that the model over-predicted passenger volumes in the new metro line (phases 1 and 2). The articles had pointed out certain areas of possible model improvements. Although we found many explanations for over- predictions, the quality of travel matrices was questioned.

Introduction to the model A group of clients headed by the Ministry of Transport decided to fund a project to improved the model and matrices. General purposes: Reduce uncertainty of the OTM model Obtaining data to describe traffic patterns better Use data from the metro in the matrices Use of the matrices to obtain better knowledge on the transport system Re-estimate and recalibrate the traffic model

Introduction to the model The direct reason that initiated the start of the OTM 5.0 project was the wish to be able to reduce the uncertainty related to demand forecasts for the future use of the Metro City Ring.

Introduction to the model Some definitions: 1. The OTM covers the Greater Copenhagen Area. 2. The OTM is a traffic model for both personal and goods transport. 3. The OTM is a workday model, i.e. weekends are omitted. 4a. The OTM is a tour/trip model, i.e. the activity chains are simplified into tours and trips. 4b. The OTM person travel model has six model segments (sub-models), defined by travel purposes. The model segments are executed independently of each other.

Travel distances Person trips, ´000 HWHEHSHOnHOBSTotal Car driver Car passenger Public Transport Bicycle Walk Total

Travel distances Trip length (zone-to-zone trips x zone-to-zone dist. / tot. trips), km HWHEHSHOnHOBSTotal Car driver Car passenger Public Transport Bicycle Walk Total

Distribution of trips per distance, all modes and travel purposes, % Travel distances

Day person-km (trips x length / population), km HWHEHSHOnHOBSTotal Car driver (47%) Car passenger (21%) Public Transport (19%) Bicycle (9%) Walk (4%) Total person-km per day 8.8 (31%) 1.8 (6%) 3.8 (13%) 7.8 (27%) 4.4 (16%) 1.9 (7%) 28.5 (100%)

The observed trip rate in the TU 2000 GCA data was 3.1 trips/person/day The observed trip rate in the TU 2005 GCA data was 3.2 trips/person/day The OTM 5.0 calculated trip rate (matrix trip sum / population) is 3.3 trips/person/day Trip rates

Elasticities – all purposes Cost elasticity, all travel purposes CarPTBicycleWalk Car Public Transport Travel time elasticity, all purposes CarPTBicycleWalk Car Public Transport

Cost elasticity, commuters CarPTBicycleWalk Car-0.13 (-0.10) Public Transport (-0.42) Travel time elasticity, commuters CarPTBicycleWalk Car-0.24 (-0.15) Public Transport (-0.26) Elasticities - commuters

Cost elasticity, private trips CarPTBicycleWalk Car-0.10 (-0.10) Public Transport (-0.42) Travel time elasticity, private trips CarPTBicycleWalk Car-0.13 (-0.15) Public Transport (-0.26) Elasticities – private trips

Cost elasticity, business trips CarPTBicycleWalk Car-0.03 (-0.10) Public Transport (-0.42) Travel time elasticity, business trips CarPTBicycleWalk Car-0.09 (-0.15) Public Transport (-0.26) Elasticities – business trips

Assignment results Number of boardings by public transport modes, observed vs. calculated, ‘000 PT modes Observed 2004 Calculated 2004 % difference Bus Metro S-tog Regional train Lokalbaner 18 0 Total

Assignment results Public transport trips across the Harbour corridor, observed vs. calculated, 2004 PT modes Observed 2004 Calculated 2004 % difference Knippelsbro Metro Langebro Sjællandsbroen Kalvebodbanen Kalvebod bro Total

Assignment results Car traffic across the Harbour corridor, observed vs. calculated, 2004 Observed 2004 Calculated 2004 % difference Knippelsbro Langebro Sjællandsbroen Kalvebod bro I alt

Assignment results, metro boardings, 2004 Metro Station Observed 2004 Calculated 2004 Absolute difference Relative difference Vanløse % Flintholm % Lindevang % Solbjerg % Frederiksberg % Forum % Nørreport % Kongens Nytorv % Christianshavn % Islands Brygge % DR Byen % Sundby % Bella Center % Ørestad % Vestamager % Amagerbro % Lergravsparken % Total %

Back casting to Assignment results Trips per average workday in 2000 and 2004, ‘ % difference Car driver2,0072, Car passenger1,0501, Public transport Bicycle1,0731, Walk Total6,0446,2082.7

Back casting to Assignment results Car traffic across the Harbour corridor, observed vs. calculated, 2000 Counted 2000Modelled 2000Abs. difference% difference Knippelsbro34,60035, Langebro68,50065,643-2,857-4 Sjællandsbroen51,10042,686-8, Kalvebod bro76,90079,0422,1423 Total231,100222,485-8,615-4

Car elasticities are in general lower than the PT elasticities. Car users are more sensitive to changes in travel time than to changes in driving costs. Public transport users are more sensitive to changes in fares then to changes in travel time. Elasticities differ with respect to travel purpose. Conclusions (1)

2004 model assignment results for public transport modes give on an overall level a difference of only up to 7% to the counted boardings. Similarly, the 2004 model assignment results for car traffic over the Harbour corridor differ from the counted traffic by only +/- 10%. Conclusions (2)

Back casting to 2000 shows that the total traffic rose from 2000 to 2004, car traffic increased sharply, and accordingly the public transport decreased. The 2000 model assignment results for car traffic over the Harbour corridor differ from the counted traffic by only +/- 4%, with exception of Sjællandsbroen. Conclusions (3)