A report describing and assessing the national data sources available for strategic transport planning. Prepared as part of the ABI 3 L project

Transcription

1 abi 3 l A report describing and assessing the national data sources available for strategic transport planning Prepared as part of the ABI 3 L project March 2012 Prepared by: ABI 3 L Project Team THIS REPORT MAY NOT BE REPRODUCED OR DISTRIBUTED IN PART OR IN WHOLE WITHOUT THE EXPRESS PERMISSSION OF THE ABI3L CONSORTIUM MEMBERS LCP Consulting Ltd, The Stables, Ashlyns Hall, Chesham Road, Berkhamsted, Hertfordshire, HP4 2ST UK Tel: +44 (0) Fax: +44 (0) LCP Consulting Ltd 2012 all rights reserved. The copyright in this document, which contains information of a proprietary nature, is vested in LCP Consulting Ltd. The content of this document may not be used for purposes other than that for which it has been supplied and may not be reproduced, either wholly or in part, in any way whatsoever, nor may it be used by, or its contents divulged to, any person whatsoever without the prior written permission of LCP Consulting Ltd.

2 abi 3 l Contents Executive Summary... 1 Data Map... 3 Model Structure... 4 Report Structure... 6 The ABI 3 L Project... 7 Transport Infrastructure GB Road Network Data GB Rail Network Data GB Port Infrastructure Database Network Rail Rules of the Plan Network Rail Working Timetable Rail Traffic Data Rail Terminal Capacities Freight Assets Continuing Survey of Road Goods Transport (CSRGT) DfT Freight Assets Road and Rail Cost Models Alignment Table for Commodities Asset-Commodity Compatibility Commodity-Commodity Compatibility Density Matrix Freight Mover Road Haulage Association database Census Data (2001) Operator Licence Database Intensity Matrix Freight Owner FAME SIC Codes... 82

3 abi 3 l 21. Database of large businesses in England and Wales Database of large businesses in Scotland Large Warehouse Database Storage and Production Infrastructure Environment Agency Public Registers Generalised Land Use Database GIS Map of NUTS 4 Districts Setting Boundary Conditions Maritime Statistics Channel Tunnel Traffic Deep Sea Feeder Costs Cross-Channel service transport costs between European regions and GB ports Frequency of Sea Services Trade Data Trade Forecasts Other Data Sources Holding and Re-Order Costs Population Demographics and RPI Basket Future Data Sources Works Cited

4 abi 3 l List of tables Figure A1: ABI3L Data Map: Overview... 3 Figure A2: ABI3L Data Map Key... 4 Figure A3: Model Structure... 5 Figure A4: Production Within Regions... 5 Figure B: ABI3L Data Map: Transport Infrastructure Figure 1.1 Fields in Road Network Figure 1.2 Shapefile of GB Road Network Data for South East of England Figure 2.1 Shapefile of GB Rail Network Data for South East of England Figure 2.2 TIPLOC to Stanox Lookup Data Sample Figure 3.1 GB Port Infrastructure Database Data Structure Figure 3.2 GB Port Infrastructure Database Additional Fields Data Structure Figure 3.3 GB Port Infrastructure Database Additional Fields Data Structure Figure 4.1 Network Rail Rules of the Plan Data Sample Figure 5.1 Network Rail Working Timetable Raw Data Sample Figure 6.1 Rail Traffic Data Sample Figure C: ABI3L Data Map: Freight Assets Figure 8.1 CSRGT Queries and Levels of Suppresion Figure 8.2 CSRGT Data Structure Figure 8.3 Example CSRGT Survey Page Figure 8.4 Example CSRGT Survey Page Figure 8.5 Example CSRGT Survey Page Figure 8.6 Example CSRGT Survey Page Figure 9.1 DfT Freight Assets Rigid Body Data Sample Figure 9.2 DfT Freight Assets Total Vehicle Numbers Data Sample Figure 9.3 DfT Freight Assets Artic Body Data Sample Figure 10.1 Road Cost Model Figure 11.1 Alignment Table for FAME Data Sample Figure 11.2 CSRGT Commodity Groupings Figure 11.3 ABI3L Commodity Groupings... 53

5 abi 3 l Figure 12.1 Asset-Commodity Compatibilty Data Sample Figure 13.1 Commodity-commodity Compatibilty Data Sample Figure 14.1 Density Matrix Data Sample Figure 14.2 Density Matrix Data Calculation Sample Figure D: ABI3L Data Map: Freight Mover Figure 15.1 Road Haulage Association Database Data Sample Figure 15.2 Road Haulage Association Database Comparison to VOSA Data Figure 17.1 Operator Licence Database Operating Centres Data Sample Figure 17.2 Operator Licence Database Licence Status Data Sample Figure 18.1 Intensity Matrix Data Sample Figure 18.2 CSRGT Data Sample Figure 18.3 Intensity Matrix Sample Calculations Set Figure 18.4 Intensity Matrix Sample Calculations Set Figure 18.5 Intensity Matrix Sample Calculations Set Figure 18.6 Intensity Matrix Sample Calculations Set Figure E: ABI3L Data Map: Freight Owner Figure 19.1 FAME Database Company Details Data Sample Figure 19.2 FAME Database Company Details Data Sample Figure 20.1 SIC Codes Data Sample (UK SIC 2007) Figure 20.2 SIC Codes 2003 and 2007 Data Sample Comparison Figure 20.3 SIC Codes 2007 Data Category Structure Figure 21.1 Databases of Large Businesses in England and Wales Data Structure Figure 21.2 Databases of Large Businesses in England and Wales Data Sample Figure 22.1 Databases of Large Businesses in Scotland Data Structure Figure 22.2 Databases of Large Businesses in Scotland Data Structure Figure 23.1 Large Warehouse Database Data Sample Figure F: ABI3L Data Map: Storage and Production Infrastructure Figure 24.1 Environment Agency Public Registers Data Sample Figure 25.1 Generalised Land Use Database Sample Figure 26.1 GIS Map of NUTS 4 Districts South East Sample Figure G: ABI3L Data Map: Setting Boundary Conditions Figure 27.1 Maritime Statistics Data Sample

6 abi 3 l Figure 28.1 Channel Tunnel Traffic Data Sample Figure 31.1 Frequency of Sea Services Data Sample Figure 32.1 Trade Data Sample Figure G: ABI3L Data Map: Setting Boundary Conditions Figure 34.1 Holding Costs Data Sample Figure 34.2 Re-Order Costs Data Sample

7 abi 3 l Executive Summary This report describes a structured review of all the sources of statistical data that are available to support the strategic planning of freight and logistics in the UK. It has been completed as part of the ABI3L research project to apply agent-based modelling to strategic planning in the freight industry. The project is part funded by the Technology Strategy Board (TSB), and commenced at the beginning of September 2010 with a dedicated team established at Cranfield School of Management's Complex Systems Research Centre. The consortium is led by MDS Transmodal in partnership with LCP Consulting, and Barloworld Supply Chain Software. The aims, objectives, structure and methodologies of ABI 3 L are described in more detail in the next section; the summary is as follows: ABI 3 L will create complex systems models to help determine the investments and policies required for freight and logistics to move to a low-carbon world that also delivers improved economic growth. The agent-based modelling approach allows forecasting on the basis of the likely behaviour of decision makers, whereas existing methods are normally optimisation exercises for individual actors; however, the freight industry is a far more complex system. The output of the project is to demonstrate proof of concept of the application of agent-based modelling to this highly complex area of strategic planning. Agent-based modelling using complex systems thinking has been successfully applied in other areas, but never before on this scale, and never with freight. As part of the modelling work, it was a necessity to compile data on infrastructure, freight demand, freight assets and commodities to input to the model, either in total or in summary form. The project team has completed that task and the process has identified 40 different sources of data. The process of compiling that data and aligning the different sources has identified: Unexpected richness in data that is available but appears to be seldom used Profound issues of copyright in the potential for commercial use of the data Inconsistencies between data sources that make alignment and interpretation difficult Questions over sampling methods and the underlying statistical reliability of the data if it is used at a more granular level for strategic planning Some gaps where data that the team judged to be desirable is simply not captured or available in any way While inconsistencies and gaps have been identified, the team has worked to ensure that these have not been a barrier to creating the proof of concept model; the outputs will provide powerful insights and clearly demonstrate the applicability of the tool. However, as the project moves to its next stage and the potential to provide evidence-based policy making, there will be a requirement to tie back the model to more auditable detail. Page 1 of 126 March 2012

8 abi 3 l This report has therefore been prepared by LCP Consulting on behalf of the consortium to describe the data sources, their origins, the ease (or difficulty) in updating them, any restrictions of copyright or access in their use together with any inconsistencies and gaps that were discovered. We understand that HM Treasury have a policy commitment to improving evidence-based planning. In that context we hope that this important area of the economy might be served with better data prepared on a more integrated basis. Members of ABI3L would welcome the opportunity to discuss the long-term data issues with appropriate parties, subject to protecting copyright and confidentiality where appropriate. Page 2 of 126 March 2012

9 abi 3 l Data Map FIGURE A1: ABI3L DATA MAP: OVERVIEW Page 3 of 126 March 2012

10 abi 3 l FIGURE A2: ABI3L DATA MAP KEY The Data Map shows flows of data into, around, and out of the ABI3L model. Data Sources were evaluated by the project team to be either high-quality, medium-quality or low-quality. Some sources have yet to be classified. Not all inputs on the Data Map are incorporated into the proof of concept model. Some are included on the map as their use has been considered for an update to the data used in the proof of concept model. Model Structure The model s operation centres on stacks of Movement Requests. These are generated by Freight Owners, and fulfilled by Freight Movers. The Freight Mover element contains 2 components: Scheduled Freight Mover Agents (rail and ship) operate scheduled routes. SFMAs exercise agency over which routes to operate and assess their performance in terms of route loads: killing routes that are not economically viable and experimenting with the generation of new routes using existing environmental infrastructure (railway terminals and routes, and sea ports). Unscheduled freight mover agents (UFMA) have no schedule constraints and therefore exercise agency over their asset fleet in terms of numbers and type. Each agent measures its performance in terms of asset utilisation and compares its own performance with other agents in the same locality. Each Freight Mover has attached to it a number of Freight Assets, which are used to fulfil Movement Requests. The simulation output of the model combines Movement Requests with information about Policy, Cost Models, Infrastructure, Boundary Conditions and the Environment. The current form of the simulation is a GIS map with movements represented as dots; however, this will be customised for the specific requirements of future projects. Page 4 of 126 March 2012

11 abi 3 l The diagram below shows the operational layout of the model. Figure A4 shows the flows within regions. Inputs and outputs to a region can be calculated from CSRGT data. The RPI Shopping Basket and Population Densities can be used to calculate the consumption of a commodity within a region. This represents the retail consumption; the rest is divided by warehouses and factories, and is presumed to be consumed in production. There is no production for retailers, and production equals consumption for warehouses. This means that production for manufacturers can be back-calculated. FIGURE A3: MODEL STRUCTURE FIGURE A4: PRODUCTION WITHIN REGIONS Page 5 of 126 March 2012

12 abi 3 l Report Structure This report is grouped into analysis areas; these are ringed on the data map on page 3. These areas are: Transport Infrastructure (purple) these are data sources pertaining to the infrastructure environment that the model uses. This concentrates on Great Britain only. Freight Movers (orange) these data sources provide information on freight movers, and their asset fleet. Freight Owners (yellow) these data sources provide information on freight owners, i.e. those who require freight to be moved. Freight Assets (red) these data sources provide information on the asset fleet available in Great Britain, and what commodities these assets can carry. Storage and Production Infrastructure (green) these data sources provide information on the businesses and warehouses around the country, as well as NUTS4 operational borders. Some of these data sources are also used in the Freight Owner model. Setting Boundary Conditions (blue) these are data sources that are used to manage the imports and exports from Great Britain seen in the model. The commentary and analysis on each data source describes where data is from, how it is processed, whether it is generally accessible or its access is restricted, what would be required to collect the data from scratch, how difficult it would be to update the data, and how critical updates are to the model. Constraints and inconsistencies in relation to other data are also outlined where applicable, along with recommendations and requirements for improvement in future model implementations. Page 6 of 126 March 2012

13 abi 3 l The ABI 3 L Project Brief Agent Based Intelligent, Integrated and Innovative Logistics (ABI 3 L) is a research and development project part funded by the Technology Strategy Board (TSB). The project kicked off at the beginning of September 2010 with a dedicated team established at Cranfield School of Management's Complex Systems Research Centre. The consortium is led by MDS Transmodal in partnership with LCP Consulting, and Barloworld Supply Chain Software. The project will create complex systems models to help determine the investments and policies required for freight and logistics to move to a low-carbon world that also delivers improved economic growth. This project is innovative as integrated planning, policy and design across the freight modes is completely new. Agent-based modelling using complex systems thinking has been successfully applied in other areas, but never before on this scale, and never with freight. Project ABI 3 L is one of 12 'intelligent logistics' initiatives to have been awarded funding through the TSB in a competition designed to identify solutions to some of the UK's biggest transport and logistics challenges, including the need to ease congestion and reduce carbon emissions. The initiatives have been launched by the Government-backed Technology Strategy Board with funding support from the Department for Transport, The Department of Business Innovation and Skills, HM Treasury and linking with the Engineering and Physical Sciences Research Council (EPSRC). Why ABI 3 L? ABI 3 L is a modelling tool designed to support freight transport policy and investment decisions. It is needed by policy makers at both national and regional levels, freight operators across the modes of road, rail and shipping, and investors in capacity and infrastructure. These actors work in a complex and inter-dependent world of freight and logistics that directly drives as much as 8% of GDP and enables the entire economy to function. The Government's primary agenda is to re-establish economic growth in the context of the comprehensive spending review that has reduced the public investment capacity in transport infrastructure for 2012/13 by 1.42bn to 1.43bn, increasing to 1.427bn to 1.428bn by 2018/19. This will require that private investment is introduced and takes the strain, that investment outcomes will need to be more certain and that planning and design focus should be more precise. The Government's parallel agenda is its commitment to an 80% reduction in carbon emissions by All the current research indicates that freight and logistics will fail to make a proportional contribution to this target on current trajectories. Radical policy measures will be needed to drive change combined with fundamental supply chain restructuring. Page 7 of 126 March 2012

14 abi 3 l Furthermore the data to support the definition of such radical measures for carbon reduction and provide investors with confidence is constrained by inconsistencies in classification, incomplete sampling and a lack of integration. ABI 3 L is building a complex modelling framework and organising the data to provide a decision support platform. It will answer questions like: Where, what and how big should investments in freight and logistics capacity be to drive growth and reduce carbon? What will be the network impacts in terms of public infrastructure for capacity and congestion across the modes? What fiscal and regulatory policy measures will support and drive the required change? Partners Project ABI 3 L has brought together a number of organisations to provide a breadth of knowledge and experience. A short summary on each of them follows. MDS Transmodal MDS Transmodal is the leading specialist in freight transport economics consultancy in the UK and the author of the GB Freight Model currently used by the Department for Transport. The company is an innovator in its approach to understanding and analysing the freight industry through amassing large databases and creating models. Strategic transport planning advice to improve efficiency and sustainability is a key component of MDS Transmodal's work. Page 8 of 126 March 2012

15 abi 3 l Cranfield School of Management Cranfield School of Management is one of Europe's leading university management schools renowned for its strong links with industry and business. It is committed to providing practical management solutions through a range of activities including post- graduate degree programmes, management development, research and consultancy. The Complex Systems Research Centre (CSRC) moved to the School of Management in Its aim is to develop and present the theory and implications of Complex Systems thinking for Management Science - both as a collaborative research theme, and as an integrating conceptual framework. It provides an overarching scientific perspective within which strategy, operations, human resources, economics and finance all find their place. LCP Consulting LCP Consulting is a leading specialist in customer-driven supply chain management. With over 20 years' experience in the field, we identify where supply chains make major contributions to how businesses operate profitably and compete effectively. We support businesses review, re-design and implement changes to their end-toend operations. Our fact-based diagnostics pin point exactly where & how to cut costs, enhance operational efficiency and invest for the future. Barloworld Supply Chain Software Barloworld Supply Chain Software is a world class supply chain planning company, providing expertise, tools and solutions to help companies optimise their supply chain networks, inventory and transportation. The company has over 20 years' experience in supply chain planning, with more than 400 software installations across over 600 international clients, supported from offices in Europe, South Africa, U.A.E, Spain, China, USA and partners worldwide. Barloworld Supply Chain Software is part of the Logistics arm of Barloworld Plc, a South African multinational with over 18,900 employees and a turnover of more than $5.5 billion. Page 9 of 126 March 2012

16 abi 3 l The Technology Strategy Board The Technology Strategy Board is a business-led executive non-departmental public body, established by the government. Its role is to promote and support research into, and development and exploitation of, technology and innovation for the benefit of UK business, in order to increase economic growth and improve the quality of life. It is sponsored by the Department for Business, Innovation and Skills (BIS). Page 10 of 126 March 2012

17 abi 3 l Transport Infrastructure FIGURE B: ABI3L DATA MAP: TRANSPORT INFRASTRUCTURE Page 11 of 126 March 2012

18 abi 3 l 1. GB Road Network Data Source: MDST Within the Great Britain Freight Model (GBFM) there is a national road network. This covers Great Britain (England, Wales & Scotland but not Northern Ireland). There are 27,000 links. This network is derived from a DfT-sourced network from around the year This network was then simplified so as to reduce the processing time required to find routes through it. After assignment of a national origin postcode district to destination postcode district HGV matrix, any links with zero traffic were removed from the network. Some significant roads have been added such as the completion of Manchester s M60. There is the option of adding tolls to any link but in general it has been assumed that tolls are unlikely to significantly affect routing and for simplicity have not been included. An obvious exception to this is the M6 toll road. As a lot of freight is discouraged from using the M6 toll due to the toll charges, this road has simply not been included in the network with all through traffic being assigned to the M6, and local traffic on the A5 / A38. Many road upgrades do not alter the general routing of traffic, e.g. A1 to the east of Leeds, so it is not crucial that these routes are upgraded in the network. FIGURE 1.1 FIELDS IN ROAD NETWORK Field Name Comments Redacted in this document version Each link has a speed attached to it. This represents the typical uncongested car speed. For freight, these speeds are scaled down different scalings for different road types and area types. In GBFM, the least generalised cost route is calculated from origin to destination and traffic assigned along this route: effectively all-or-nothing assignment. As cars make up the majority of traffic, there is no consideration of congestion in the network. Once the traffic is assigned, it is possible to calculate turning movements at junctions. The data is available in MapInfo Interchange Format (*.mid, *.mif) and Shapefile (*.shp) formats. There are a number of advantages to using this network: Page 12 of 126 March 2012

19 abi 3 l It is recognised by the DfT because it is the road network used in GBFM the freight component of the DfT s National Transport Model. It is a relatively simple network with national coverage so that it is relatively quick to run assignment algorithms. It already exists and MDST are familiar with it. MDST own the IPR for this road network. It has been suggested that the proof of concept model proceeds using this network and if an improved newer / alternative network is found at a later date, it can be substituted in. The DfT reputedly have a newer road network, although the partners have yet to see or evaluate this. FIGURE 1.2 SHAPEFILE OF GB ROAD NETWORK DATA FOR SOUTH EAST OF ENGLAND Summary: How acquired Originally from DfT, but with processing to simplify the network by MDST involving considerable time and effort How public domain Not public domain due to the value added and the original network source Page 13 of 126 March 2012

20 abi 3 l How difficult to source if starting from scratch It would be simpler to adapt the existing network (e.g. add new roads) rather than start from scratch. However, if a good road network with more representative HGV speeds became available, it may be worth using that. Other options include using the freely available Ordnance Survey GIS road layers, and converting them into a network (although speeds would have to be attached and a glitch-free network generated). Approximate days work required for future update (given experience of acquiring this time) Simply adding new roads is relatively straight-forward. Approximately half a day was required to add the eastern sections of the M60. How regularly should be updated for ABI3L models It is quite rare for a new road to significantly change the capability of the network, so acquiring an update every 5-10 years may be adequate. However if the output of interest was local to a particularly significant new road, then results would be more robust if the network included the road enhancements. How crucial updates are to the model Local updates may be significant for local analyses, but generally frequent updates are of relatively low importance. Constraints and Inconsistencies The team is not in possession of a comparable database; therefore, there are no inconsistencies in relation to other data used in the project. The IPR for this database lie within the project team, so there are no constraints to its use within this project. Potential for Improvement The DfT reputedly have a newer road network, although this has not yet been confirmed. Page 14 of 126 March 2012

21 abi 3 l 2. GB Rail Network Data Source: MDST A national rail GIS network is used to assign rail traffics to the model. There are 2754 links. Locations, such as junctions, stations, depots, are represented by TIPLOC and Stanox codes. These are added to the database along with loading gauge (relating to height of bridges etc.). The loading gauge field could require updating as several routes have been / are being / will be upgraded. Field for links: Loading gauge Fields for point locations: TIPLOC code, Name (e.g. station) The network details all rail lines as they might appear in a national road atlas; it does not have detailed info of track layouts etc. FIGURE 2.1 SHAPEFILE OF GB RAIL NETWORK DATA FOR SOUTH EAST OF ENGLAND Network Rail s timetables are defined in terms of TIPLOC location codes. Stanox codes are another similar means of defining railway locations. There is a lookup list to translate from one to the other. Page 15 of 126 March 2012

22 abi 3 l FIGURE 2.2 TIPLOC TO STANOX LOOKUP DATA SAMPLE Redacted in this document version The Network Rail historic traffic data defines routes as a series of Stanox codes (e.g. around 40 Stanox locations between Felixstowe and Manchester). Therefore, traffic is assigned to the network by finding the shortest path between subsequent Stanox locations. There are some imperfections to the network. In reality, some routes exist where one goes over another and there is no means of getting from one route to the other. However in the network, sometimes these movements are mistakenly possible. Prior to considering this data source, MDST discussed rail networks with the DfT. After some suggestion that they had a good rail network, it appeared that they have several, all with their own deficiencies. The general impression was that this model is not too bad as long as no attempt is made to look at track level. Summary How acquired Originally from a GIS layer, but with processing to ensure the network s integrity, then TIPLOC & Stanox codes added. How public domain Not public domain due to the value added in terms of linking the locations to the network involving considerable time and effort. How difficult to source if starting from scratch The background network itself could be easily sourced from freely available Ordnance Survey GIS layers. However the TIPLOC / Stanox locations would be difficult to source. There is little need to update this network from scratch. Any changes to rail infrastructure can be incorporated into the existing network. Page 16 of 126 March 2012

23 abi 3 l Approximate days work required for future update (given experience of acquiring this time) Simply adding new rail lines is relatively straight-forward. Approximately half a day would be required to add a new line. How regularly should be updated for ABI3L models A similar importance to the road network i.e. acquiring an update every 5-10 years may be adequate. How crucial updates are to the model Local updates may be significant for local analyses, but generally frequent updates are of relatively low importance. Constraints and Inconsistencies The team is not in possession of a comparable database; therefore, there are no inconsistencies in relation to other data used in the project. The IPR for this database lie within the project team, so there are no constraints to its use within this project. Potential for Improvement Correcting the errors found where certain routes cross over would fix a known shortcoming in this database. The DfT are reputed to have a number of rail models, it could be worth exploring the possibility that these could be combined into a definitive model. Page 17 of 126 March 2012

24 abi 3 l 3. GB Port Infrastructure Database Source: MDST This is a database (spreadsheet list) of the port infrastructure in Great Britain. Each record is one terminal or quay. It was last updated in approximately The relevant fields in the database are detailed below. FIGURE 3.1 GB PORT INFRASTRUCTURE DATABASE DATA STRUCTURE Redacted in this document version There are some additional fields (in light blue) that MDST intend to produce data / estimates for. These are detailed below: FIGURE 3.2 GB PORT INFRASTRUCTURE DATABASE ADDITIONAL FIELDS DATA STRUCTURE Redacted in this document version A very small sample of the data is below, showing only a fraction of the available columns. Page 18 of 126 March 2012