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Enhanced analytical decision support tools The Scheme level. Final workshop of the DISTILLATE programme Great Minster House, London Tuesday 22 nd January 2008 Dr Simon Shepherd ITS, University of Leeds. Objectives.
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Enhanced analytical decision support tools The Scheme level Final workshop of the DISTILLATE programme Great Minster House, London Tuesday 22nd January 2008 Dr Simon Shepherd ITS, University of Leeds
Objectives • To enhance existing predictive models to represent a wider range of policy instruments • To improve the ability of users to apply models
Suggested Themes 1. Demand restraint measures 2. Public transport improvements 3. Land use measures 4. Soft measures (attitudinal) 5. Slow modes and small scheme impacts 6. Data issues 7. Model use
Demand restraint modelling • Cordon location –short cut approach • Area based charging • Parking choice model
A short cut approach • Aim to develop a method between judgement and GA based approach • Use fact that Top 15 MC tolls gave high proportion of first best benefits • Charge a high cost trip somewhere – not necessarily on the high cost links • Use SLA to design where best to place cordon and catch the high cost flows
Summary cordon location • Proven for networks of Cambridge, York, Leeds and Edinburgh • Adapted for simulation networks of Shrewsbury and Cambridge • Approach included in DfT webtag advice • Now being used on Nottingham network
Area based charging • Adapt models to charge for trips within an area rather than per crossing of a cordon • Allow exemptions or discounts for residents • Implemented in SATURN • Tested on a Cambridge network
Parking model - Aims • Develop a simple parking location choice model with the demand spread over multiple time periods • Integrate within assignment stage of the transport modelling process • Develop a modelling framework that can be used to test parking demand management policies • Illustrate the method with practically available data for a realistic network of Leeds
Implemented for Leeds SATURN model Car park 2 Car park 1
Parking summary • Car park choice for multiple user classes and across time periods has been incorporated within an equilibrium assignment approach (matching Lam et al) • Impact of car park pricing structures/capacity can be modelled with the approach • Further possible extensions – departure time choice, elastic demand, etc.
Improved Public transport modelling • DRACULA – Bus reliability • STM Partial modelling of Trip chaining (extended park and ride)
DRACULA – Bus reliability • Incorporates interactions between bus operation, passenger arrivals, boarding times and private traffic. • Simulation helps understand impacts on reliability and tested alternatives to increase reliability • York case study
The DRACULA model of Route 4 • The bus route in red • DRACULA model: • 138 junctions (39 signalised) • 260 links • 21 bus stops • 2 bus lanes
Results of model validation • Ten simulation runs, over a period of 1.5 hours, 12 services each run • Modelled average journey times correspond well with observation • Model correctly predicting journey time delays at the key sections en-route
Summary of results • Headway variation and number of passengers boarding interrelated: • Unreliability increases with congestion and passenger demand • Passenger demand has more serious impact on headway variability than on total journey time • Extension of bus-lane itself does not improve reliability, but combined with signal gating strategy will bring benefit • Reduced boarding time (advanced ticketing system) brings in most significant improvements
STM – Park and Ride • Treats trip chaining in terms of park and ride at Glasgow underground stations (Subway system). The entire Subway system can be modelled. • Uses model of capacity constraint including ‘overflow’ model to transfer excess demand at car parks. • Used to investigate interaction between direct travel to Glasgow centre and by Subway park and ride in context of strategicmodel.
Subway choice sets • Additional program used to generate viable Subways for choice for each OD movement. • Based on routes for direct travel • Currently up to 5 Subways possible ( a middle possibility and 2 side alternatives)
Subway catchment zones Subway catchment area (blue) and mode shares for this
Run I (50% increase in jobs) – impact on Subway system % mode share increases for all the catchment zones – Subway increases by about 16%
QUESTIONS? Contact : Dr Simon Shepherd Institute for Transport Studies University of Leeds S.P.Shepherd@its.leeds.ac.uk Tel : 0113 343 6616