GIS Support for a Traffic Operations Management Plan in Delaware Geospatial Information Systems for Transportation AASHTO GIS-T, Hershey Pennsylvania March 28th, 2011 David Racca Center for Applied Demography and Survey Research University of Delaware dracca@udel.edu
DelDOT ITMS The goals of the Delaware Department of Transportation Integrated Transportation Management System (ITMS) is to keep the efficiency of the transportation system at the highest possible level through real time monitoring, control and information, and is composed of 4 functional areas to include control, monitoring, information and telecommunications. New Castle County Delaware is the target area for implementing congestion management strategies and will join existing information, fill in gaps with new data, prioritize and prepare for new project start-ups, and quantify transportation system performance.
GIS support for the operations plan and traffic analysis addresses the following areas: Standard and effective ways of referencing traffic data to models of the transportation network. Location and processing of vehicle data Location and processing of fixed device measurement data (infrastructure) Location and processing of environment data Integration, ti visualization and dissemination i of the above
The primary issues associated with traffic data and managing it and processing it in GIS are: Travel flow. Most of the data is directional. Standard d and effective ways of referencing traffic data to models of the transportation network. Integrating data of different spatial types, point, line, and polygon. Examples: speed probe data, capacity data, device counters, travel demand Integration of data from different time dimensions. Dealing with large volumes of data. Aggregation and disaggregation. g Integrating across portions of the transportation network. Interrelated measures. Significance of values depend on other factors
DIRECTION
You are referencing information to the GIS model of the travel way. The flow of the traffic and where data is in that flow is the basis of the integration. Generally you are building performance measures about how traffic flows, contributions to the flow, and impediments to the flow. The fundamental issue of referencing that information are the entities within the GIS representation and what you call them, the identification system. The GIS entities are: * Links portions of road of varying lengths * Approaches * Turns right, left, thru, u * demand points origins and destinations * intersections
Data about travel ways is coming in a range of resolutions Some data is about road segments between major intersections Segments between minor intersections and access points Segments that relate to a change in a factor not only dependent on intersections Pavement quality Addresses Elevation Jurisdictional boundaries Property boundaries About points, not segments, incidents
Data across a travel way Address Ranges Traffic Volumes Lane Widths Bid Bridges
Identifying entities A segmentation scheme based on most major and minor intersections, detailed enough to please most everybody X-Y Y? Nearness? Fixed segmentation Linear referencing dynamic segmentation A consistent and integrated approach and guide/standard for managing road network data is needed.
Linear Referencing as Another Option DelDOT Centerline File Delaware Linear Referencing System DELRS Maintenance Rd ID RDWAYID Beginning g and end mile points
Integrating Query on LRS Tables 0 0.5 2.3 4.8 35 45 55 Speed Limit i AADT Values 0 2.5 30000 22000 0 4.1 5.2 Pavement Type Asphalt Concrete Asphalt Skid Values 0 0.2 2.1 5.8 34 30 32 GIS Query Results where: Speed => 45 AADT < 25000 Pavement = Asphalt Skid Value =< 30 2.5 4.1 5.2 5.8
Linear Referencing Tools Overlay union, intersect, query Dissolve/Concatenate t events Locate points (XY) & polygons along routes- Produce the route and mile point of a point or intersecting polygon in space Transform events Go from one linear referencing system to another. Calibrate a lrs A great deal of data processing potential to work with point and segment data
Identification Scheme Based on Delaware s LRS ROAD SEGMENTS: LRSID 16 16 N 0 = RDWAYID * 10000000000 + BEGMP * 100000000 + 1000 * ENDMP (in opposite direction) = RDWAYID * 10000000000 + ENDMP * 100000000 + 1000 * BEGMP
Identification Scheme Based on Point Data Delaware s LRS LRSID 12 12 N 0 = RDWAYID * 100000 + LRSMP * 1000 Intersections can have more than one Intersections can have more than one unique ID based on segments involved
Identification Scheme Based on Approaches Delaware s LRS LRSID 16 16 n 0 = 10000000000 * RDWAYID + (LRSMP +.002) * 100000000 + LRSMP * 1000 OR = 10000000000 * RDWAYID + (LRSMP -.002) * 100000000 + LRSMP * 1000
Turns
Turns created from 2 arcs and directions
LRSID 32 32 C Identification Scheme Movements / Turns = RDWAYID1+LRSBMP1+LRSEMP1+RDWAYID2+ + LRSEMP1 + RDWAYID2 + LRSBMP2 + LRSEMP2 Where: LRSBMP1 = (begmp1 +.002) * 1000 or = (endmp1 -.002) * 1000 LRSEMP1 = (begmp1* 1000) or = endmp1 * 1000) LRSBMP2 = endmp2 * 1000 or begmp2 * 1000 LRSEMP2 = ( endmp2 -.002 ) * 1000 or ( begmp2 +.002) * 1000
A Sample GPS Path
Issues with Speed Probe Data A point measurement of speed from a vehicle is directional though sometimes has no heading information i Issue of where to assign the point in a segment based scheme. The link or the approach? Speed measurements within the intersection are not the approach or link, but the turn Nearness functions used to establish the LRS point don t solve all issues with the raw data
Three approaches being investigated For a given route identify vehicles traveling the entire route and tabulate travel times for the entire route for different times (peak). Group speed probe readings for each direction of a link and establish an average speed for the link. Take each vehicle trip/track and develop speed estimates to each link and turning movement crossed in the trip. Allocation of the times and speeds to the turns and links making up the track.
Where We Are With Transportation System Collections Websites managed by separate agencies Separate libraries Massive amount of information for transportation Reports, tables, figures, power points, spreadsheets, GIS files of various kinds, links and other websites, graphics etc Information is used for various purposes and it is often unpredictable what bits of information will be cataloged and how they will be used Data silos, every user, every project, every subproject, organization of data is barely known to the originator. Folders, even shared folders, don t manage it well
Tagging Tagging is the organization of the information Data type, format, project name, file owner, date, topic area, spatial extent are all examples of tags Views are created from queries on the document library. Such as. select all documents/data referring to traffic counts in Sussex County A balance between search capabilities and amount of time it takes to reference a bit of information.
View Examples Show me. All Files submitted by a certain person All New Files since September 2009 All power point files that deal with the 301 Project All GIS Files For Sussex County that reference traffic counts
Basic Requirements of a Successful Approach Access by various groups and individuals from various places. An adaptable, evolving system Develop a sense of group ownership and the largest involvement by the group. Recognition of user contributions and achievements. Citations. Functional tagging scheme and creation of views. Clear guidelines for use and access The best data security possible given user involvement Ability to group and access content t by various user and group designations
Collaboration A move toward more user involvement Interchange of data within a group Users take a more active continuous role in the development of information resources. Involved in the design, building and maintenance. Interchange of Ideas within a group, options for communication Involvement of Users in the group and a sense of ownership Management of tasks for group efforts, maintaining momentum
A very promising solution MS Sharepoint Document Libraries
A very promising solution MS Sharepoint Document Libraries
GIS Related Features Links to web mapping applications where the links themselves are searchable Google maps GIS data collections of all sorts Maps, figures, and presentations Amenable to users formats and preferences
Link Referencing Similar to Document Referencing
Group Sites
Projects and Goals
Conclusions Integration and archiving require a standard and stable method of referencing point, line, and polygon data, that works across agencies. Traffic data management requires a method for managing data about turns and segments. Preserving and making GIS data available and searchable is as important as the collection of GIS data and the development of applications. MS Sharepoint is a very promising tool that can bring the transportation community and handle the huge amounts of data of many types Integration is most possible at the segment level