Zhengdong HUANG Wuhan University 1 Data for transport planning and management Why integration and management? Issues in transport data integration Technical aspect Institutional aspect Action examples Conclusions 2
People Constraints Activities Household Income Employment Age Perception Modes Schedule Type of activity Space Land use Zone Road network Places 3 Factors leading to CONGESTION: Infrastructure shortage or deficiency Motor vehicle increase Overly high density Less organized spatial structure EMISSION: CO2, NOx Noise SAFETY Accident 4
Socio economic data (census, land use ) Transport infrastructure t (roads, facilities...) Transport services (public transit ) Travel demand and system use (household, activities, employment, freight ) Transport impact (performance measure, environment ) 5 System data Service data Facilities data Condition data Project data Supply attributes Safety data Emissions System performance Performance measures Demand attributes Economic data Demographic data Land use data Travel data Traveller behaviour data System impacts Air quality data Other Land use data Energy data Economic environment growth data 6
Planning tasks Supply data Demand data Performance data Impact data Land use transport UTMS Road network Road network; node; transit Land use Land use; Socio-economic i Speed; volume; Discrete choice Distance Socio-economic Travel time Socio- Time; Volume; Activity-based Location economic; incidents travel diary Traffic Road network; Time; Speed; O-D assignment node volume Micro- Land use; Road network; Speed; volume simulation Socio-economic Operations Road network Speed; volume; incidents Impact analysis Road network Congestion Noise; Noise; VMT; emissions 7 Spatial Point Line Area Attribute Temporal Point Activity Activity Activity site & site & str. site & building link TAZ Activity & its attributes Activity schedule Spati al Line Rd ntwk & Bus route Link & TAZ Link performance Link travel time Area TAZ & Land use TAZ data Land use Change Attribute TAZ matrix Change Temporal Compare 8
Data is the key for planning and control Huge amount of transport data Spatial span: region, city, district, site Temporal span: year, month, day, hour Activity span: plan, construction, maintenance, monitor Needed data go beyond the transport system itself 9 Integration: to coordinate or blend distinct data into a unified whole Data source From different agencies From different data collection devices From volunteers Data type Spatial: areal, linear, point data Temporal: hour, day, month, year Spatio temporal: both attributes 10
11 data standardizing interfacing and interoperability data warehousing (assemble data, provide information for decision making) spatial a and dtemporal referencing eee aggregating and disaggregating 12
Transport data needs to be spatially and temporally anchored GIS as a data integrator Spatial vs non spatial Points, lines, and polygons Vectors and images Different layers Different sources 13 14
Data are linked by their spatial locations. The geo- referenced approach provides a framework for information exchange and data integration. By anchoring socio economic activity information to locations, a series of spatial operations becomes possible for transport analysis Travel demand forecasting Freight routing Incident management The ITS industry 15 Activity site description (e.g. address) Geo-referenced spatial base (e.g. street network) Naming or coding system (e.g. name & address) Activities (e.g. work, shopping) Activity info with geo-referenced locations Location reference system 16
Name based Link IDs using either a planar or non planar graph representation Cross street matching Landmark Road based Linear referencing Street addresses Coordinate based Grid GPS Ground survey 17 Types and reliabilities of referencing bases vague Post code Street name Administrative unit Telecom zone Place Street t address Point of interest accurate Building Street intersection certain uncertain 18
Land use &other units overlap connect Route on / end TAZ Stop in in connect spread on combine reference Activity Sites Road network on / along compose & Locations Road segment (Link) define end Intersection (Node) 19 Institutional political, economic, social or organizational i lfactors Process architectures, functions, activities, information flows Data geo/spatial, locational and temporal Technology computing and communication platforms and dcomponents 20
Planar networks Link node Non planar networks Network + attribute Multi dimensional i l 3 D D/4D 4 D Node impedance Node attribute Traversals (routes) Dynamic segmentation O D pairs Table Lanes Links + attribute Visualisation Graphical present Temporal changes Attributes +? 21 Transport data model: UML conceptual view of spatio- temporal transportation object representation (Chen et al, 2009) 22
GIS Transport Model Multi-purpose Single purpose Data-driven Model-driven Geographic context t Abstract t context t Many topologies Single topo (link-node) Chain structures link-node structure Spatially-indexed Sort-indexed Many fields Few fields 23 24 Dueker & Butler, 2000
Transition of Zonal data and attributes Aggregating from small zones to large zones Disaggregating From large zones to small zones 25 Aggregation Interpolation Disaggregation 26
Source zones Adm. Units Source zones Land use Adm Units Building Disaggregation Interpolation Land use Building Interm. zones Land use Grid cell Building Aggregation Target zones TAZ; Other zones Target zones TAZ; Other zones (a) Interpolation (b) Disaggregation-aggregation 27 Monte Carlo simulation (Spiekermann & Wegener, 2000) Doubly constraint methodhuang et al2007 Implementation in ArcGIS 28
Homogeneous zones Land use 29 Population disaggregated to raster cells 30
31 London ibus data management TfL, 2006 32
An example of a smart card information system (Pelletier, 2011) 33 Data integration between design tool (CAD) and management tool (GIS) CAD design file CAD map design CAD attribute management Data exchange GIS database Query Statistics Web service Geo- Design 34
Autodesk MAP ESRI GeoDesign 35 36
Large amounts of sector data Most data are regarded as confidential Difficult to share, waste of time and money No mechanism for public data sharing 37 Urban transport administrative structure in China Ministry of Public Security Provincial Government Ministry of Construction Provincial Dept. of Public Security Provincial Dept. of Construction Municipal i Government Bureau of Traffic Management Construction Committee Planning Committee Transport Committee Bureau of Land Resource and Urban Planning Institute of Planning and Design Institute of Transport Planning Institute of Survey and Mapping Companies of Public Transport Passenger Transport Management Administrative link Technical link 38
The Construction Committee (CC) Land Resource and Planning Bureau (LRPB) The Bureau of Public Security (BPS) The Wuhan municipal government The Planning Committee (PC) The Transport Committee (TC) The Statistical Bureau (SB) 39 Urban transport planning and management Related agencies BTM: Traffic control Vehicle control LRPB: Transport planning Land use control Urban development PC: Long-range plan Large projects TC: Public transport Inter-city transport CC: Annual road plan Construction market Road inventory EPB: Emission control SB: Socio-economic info 40
Governmental agencies Pay ygrowing gattention to data collection Have necessary technical capacity or support Less effective usage Inadequate inter agency cooperation Institutional data sharing Easier: vertical (CG Province City) City) Difficult: horizontal (e.g. LRUB TC PC EPB) Data availability to the public 41 Maintaining a database of common street network Road network planning (LRPU) New road construction (CC) Surveying and mapping (ISD) Database of Street Network Assigning traffic signs (BTM) Assigning street name (Municipality) Assigning gstreet number (BPS) 42
Transport modelling tasks Data requirements Resident travel Household: demand Income Size Trip Generation: Occupation Regression; Age structure Category Trip Characteristics: Trip distribution: Trip rate Gravity; Trip ppurposep Intervening opport.; Origin / Destination Entropy Trip duration Mode Modal split: Diversion curve; Behavioural choice Route assignment: Minimum; Stochastic; Equilibrium; Multi- path TAZ: Distances Travel time Land-use classification Geographical location Large-scale attraction Road network: Road segments / Links and their connectivity Data sources LRPU: IUTP IUPD ISD BPU BTM SB BPS CC Other Travel Demand: - Floating population; - Outward travellers; - Freight within city; - Outward freight City: Total population Total trip structure GDP Socio-economic index PC TC 43 44
GSDI to promote awareness and implementation of complimentary policies, common standards, d and effective mechanisms for the development of interoperable digital geographic data and technologies to support decision making at all scales for multiple purposes. US NSDI the technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of geospatial data 45 To promote access to and usage of fdigital geospatial information of value to multiple users To improve discovery of and public access to primarily governmental geospatial data resources To reduce duplication i of effort among collaborating organizations developing, publishing and building applications on geospatial data and services using open standards and accessible solutions 46
Organizational commitment and arrangements to stand up and build upon spatial data and services within a heterogeneous community of producers and users The spatial information, and dits integration ti Technologies, standards, specifications for discovery, visualization, and use of primarily digital geographic information 47 Vision of Geospatial One-stop Local Users Federal Users National Policy Makers State Users Tribal Users Civilian Users Commercial Users International Users DoD Users Other standards- d Geospatial One-Stop Portal based portals Local Governments State Governments Civilian Sector Commercial Sector Federal Government Transport Tribal Sector Governments and NAMAs - Manila DoD John Moeller (FGDC) 48
49 Transport Asset Data Integration: The Pennsylvania Experience 50 http://www.fhwa.dot.gov/infrastructure/asstmgmt/dipatoc.cfm
51 Basic requirements for standard data of fundamental geographic g information (GB 21139 2007) Standard for urban geospatial framework data (CJJ 103 2004) Technical standard: urban geospatial informationinfrastructure infrastructure sharing service techniques (CJ/T 384 2011, from 2012 05 01) 52
A GIS based data sharing platform Provided by information centre of LRPB for all municipal agencies Through h ad hoc administrative network 53 Administration ONE MAP SET Key maps Base maps Liu, 2011 54
Data is exploding: satellite image, traffic Data for transport go beyond the system itself Great opportunity exists for integrating and streamlining transport relateddatarelated data in a more efficient way Effective data usage depend on Technical improvement Institutional cooperation A joint effort on ONE platform 55 Zhengdong Huang Wuhan University Email: zdhuang@whu.edu.cn 56