Generating Network-Based Moving Objects: Conception & Implementation Issues

Transcription

1 Free University Bolzano 2006 Generating Network-Based Moving Objects: Conception & Implementation Issues Thomas Brinkhoff FH Oldenburg/Ostfriesland/Wilhelmshaven (University of Applied Sciences) Institute for Applied Photogrammetry & Geoinformatics

2 CONTENTS time Implementation Conclusions Design Conception Observations Time Network Objects Routing Reporting Motivation FH OOW Objective Related work Control Extensibility

3 FACHHOCHSCHULE Fachhochschule Oldenburg/Ostfriesland/Wilhelmshaven (University of Applied Sciences) merger of 3 FHs in 2000 about 10,000 students

4 DEPARTMENT Department Geoinformation accredited programs Applied Geodesy (B.Sc.) 7 semesters, 35 beginners/year Geoinformatics (B.Sc.) 7 semesters, 45 beginners/year Geodesy and Geoinformatics (M.Sc.) 3 semesters (starts SS 2008) Institute of Applied Photogrammetry and Geoinformatics () current projects

5 MOTIVATION Spatio-temporal Applications environment information systems, weather sensor web traffic telematics Spatio-temporal Database Systems data models, query languages user interfaces query processing: storage structures, indexes performance important

6 MOTIVATION Performance Evaluations theoretical analyses experiments synthetic data real data benchmarks Requirements well-defined tests and test data comprehensibility realism scalability

7 EXISTING WORK Generators for Spatiotemporal Data Theodorides, Silva, Nascimento (1999): GSTD algorithm improved by Pfoser & Theodorides (2000): additional parameters for change of direction & rectangles for infrastructure Saglio & Moreira (2001): Oporto generator start distribution positions are randomly changed moving objects attracted / repulsed by other objects

8 OBJECTIVE Assessment The movements of the objects generated by those generators are not typical for cars, pedestrians, trains and so on. Aim Construct a tool that generates moving objects behaving more like road users. simple flexible fast visualization

9 CONCEPTION Observation 1 Moving objects often follow (some kind of) network. infrastructure roads railways rivers, channels pedestrians migration of animals

10 CONCEPTION Observation 2 Most moving objects use a fast path to their destination. non-chaotic motion specific optimization goals

11 CONCEPTION Observation 3 Network connections are often classified and limits the speed. road classes topography, urban areas

12 CONCEPTION Observation 4 The number of moving objects on a network connection influences their speed. threshold traffic jam

13 CONCEPTION Observation 5 The intended route of a moving object may change if the speed on a network connection is considerably under the expected value. detour own experience / information provider / traffic control

14 CONCEPTION Observation 6 The number, start point and destination of moving objects depends on time. rush hour in the morning / evening

15 CONCEPTION Observation 7 The speed of moving objects may be influenced by external events. weather conditions

16 CONCEPTION Observation 8 The maximum speed of moving objects depends on the object. object type age of pedestrian

17 DESIGN Time discrete time stamps Network edges: class => maximum speed, capacity Moving Objects class => maximum speed # on edge => max. speed External Objects Actual Speed class => life span, moving/static position (speed), changing/static shape (rectangle) reduces maximum speed of affected edges

18 DESIGN Route computation of start node data-space oriented approach (main-memory r-tree for NNQ) network-based approach computation of destination node plus: define preferred length of route preferred area

19 DESIGN Route Computation for new objects by event (randomly) by comparison of expected speed und actual speed Number of New Objects numberofnewobjects(time) constant overall number of objects time for routes varies => number of objects varies numberofnewobjects(time) may depend on number of objects reaching their destination Report Probability simulates situations where a moving object reports its position irregularly

20 IMPLEMENTATION ISSUES Basic Facts simple Java 1.1 map viewer (applet or application) main-memory representation of the current moving objects and external objects network read from file or database system

21 IMPLEMENTATION ISSUES Controlling the Generator parameters configuration file! limits of input fields MIN_MAXTIME = 5 MAX_MAXTIME = 400 MAX_OBJCLASSES = 20! settings of the generator urlnez = file:/e:/java/data DSO VIZ outputfile = oldenburg.txt! settings of the applet viewwidth = 500 viewheight = 500 language = E color = white not sufficient flexibility in respect to the requirements discussed before

22 IMPLEMENTATION ISSUES Controlling the Generator (II) complete open source flexibility restricted comparability restricted support open source of carefully (?) selected classes allowing the user to control the generator providing examples complete javadoc providing a web-based exchange platform for modified code network files current web site

23 SUCCESS Development ~1997 implementation of basic map viewer and routing classes 1999/2000 implementation (small effort, useful tool) 2000 short SSDBM paper 2001 proposal for web-based exchanged platform not accepted 2002 Geoinformatica paper (06/2000 submitted) 2003 last important improvements 2003 review for IEEE Data Engineering Bulletin: only few applications : considerably increased usage some kind of standard benchmark support is difficult

24 CONCLUSIONS Summary generator for network-based moving objects realizes several observations control by parameters, configuration file and open source Java classes tools for converting ESRI shape files and TIGER/Line files had become popular often the example files and standard configuration are used

25 CONCLUSIONS Not Realized Features 2,5D/3D movements one-way streets time-scheduled traffic moving objects that follow the network only approximately strict movement regular movement Obstacles for Development strong interweaving with map viewer very high number of objects / very large networks => computing the shortest path is the bottleneck

26 CONTACT Thomas Brinkhoff FH Oldenburg/Ostfriesland/Wilhelmshaven Institut für Angewandte Photogrammetrie und Geoinformatik () Ofener Str. 16/19 D Oldenburg Web: institute/iapg/personen/brinkhoff/