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NISMOD national transport model: Road network capabilities

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Simon Blainey, Milan Lovrić, John Preston, University of Southampton

From household to global: simulating national infrastructure to inform decision-making

18 April 2018

Institution of Civil Engineers, London

ITRC-MISTRAL’s unique approach is already changing the way that governments and businesses approach infrastructure investment. This event demonstrated examples from the around the world to show how these changes can transform decision-making.

Simon Blainey, Milan Lovrić, John Preston, University of Southampton

From household to global: simulating national infrastructure to inform decision-making

18 April 2018

Institution of Civil Engineers, London

ITRC-MISTRAL’s unique approach is already changing the way that governments and businesses approach infrastructure investment. This event demonstrated examples from the around the world to show how these changes can transform decision-making.

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NISMOD national transport model: Road network capabilities

  1. 1. NISMOD National Transport Model: Road Network Capabilities Simon Blainey, Milan Lovrić, John Preston University of Southampton ITRC-MISTRAL showcase, 18 April 2018
  2. 2. Building on NISMOD Transport Model v1 • Multimodal simulation model • Spatially-disaggregated forecasts for 2011-2100 for 144 local authority-based zones • Short run times • Based on open source data BUT • No underlying OD matrix • No coupling between adjacent links/nodes • Limited representation of inter-modal competition • Low resolution of networks • Closed system – no representation beyond GB
  3. 3. NISMOD Road Model – how does it work? • Transport model predicts highway demand based on an OD matrix): – For passenger and freight vehicles. – Elasticity-based simulation model. – Network assignment to major road network based on prior route set generation. – Implemented in Java (GeoTools). • Fast-track case study: – Four local authority districts. • Full scale highway model: – Based on major road network for Great Britain (A roads and motorways). – OD matrix estimation based on TEMPRO trip end data, trip length distr., AADF count data. – Calibration based on traffic counts. – Offline route set generation to reduce run time.
  4. 4. Capacity utilisation • After the network assignment of passenger and freight vehicle flows, the capacity utilisation of the road network can be assessed. • Capacity utilisation = actual flow / max. flow • Capacity “pinch points” can be identified – candidates for policy interventions.
  5. 5. Interventions (road expansion and development) (a) No intervention (b) Road expansion (c) Road development • Predicted road capacity utilisation after policy interventions: ‒ Bigger reduction in capacity utilisation ‒ Localised effect ‒ Smaller reduction in capacity utilisation ‒ Spread out effect
  6. 6. Interventions (congestion charging) • Congestion charging policy: – Adjusts travel costs for road links on which the policy applies. – Pricing structure table [Vehicle Type x Time of Day]. • Examples: Vehicle Type 0 – 7 7 – 11 11 – 16 16 – 20 20 – 24 CAR £0.50 £0.60 £0.50 £0.60 £0.50 VAN £1.20 £1.20 £1.20 £1.20 £1.20 RIGID £25.00 £25.00 £25.00 £25.00 £25.00 ARTIC £25.00 £25.00 £25.00 £25.00 £25.00 Vehicle Type 0 – 7 7 – 18 18 – 24 CAR £0.00 £11.50 £0.00 VAN £0.00 £11.50 £0.00 RIGID £0.00 £11.50 £0.00 ARTIC £0.00 £11.50 £0.00 Itchen Bridge toll: London congestion charge zone:
  7. 7. Interventions (vehicle electrification) 5% 45% 35% 10% 5% 15% 40% 30% 10% 5% ELECTRICITY PETROL DIESEL LPG HYDROGEN ELECTRICITY PETROL DIESEL LPG HYDROGEN 2015 (base year) 2020 (no intervention) 2020 (electrification) (a) Fuel type market shares (b) Predicted car fuel consumptions • Based on predefined values for each year associated with strategy • Changes to energy consumption → energy demand model.
  8. 8. Road disruption • Road disruption (e.g. due to flooding) is inputted as a list of blocked road links. • Before network assignment: 1. Blocked road links are removed from the road network (graph). 2. All routes that have at least one link blocked are removed from the route set. • Removed routes are remembered so that they can be restored.
  9. 9. This afternoon – try out the demonstrator!
  10. 10. Acknowledgments The authors acknowledge funding of the work described here by the EPSRC (Engineering and Physical Sciences Research Council of the UK) under Program Grants EP/I01344X/1 and EP/N017064/1 as part of the Infrastructure Transitions Research Consortium (ITRC, www.itrc.org.uk) and MISTRAL projects. We also thank all ITRC colleagues for their continuing help in developing and adapting the modelling approach presented here. This presentation contains Ordnance Survey data ©Crown copyright and database right (2018). www.itrc.org.uk S.P.Blainey@soton.ac.uk M.Lovric@soton.ac.uk Further InformationFurther Information

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