0. Introduction

Instructor: A. Horni
Co-instructors: F. Ciari, D. Grether
Lecture type: Presentation with exercises

Learning Objectives:

• Creating and analyzing traffic count comparisons
• Getting a rough idea of further validation measures
• Using the On-The-Fly-Visualizer (OTFVis)

 

Slides

Content:

• 1. Traffic Counts
  • 1.1 Output Formats
  • 1.2 Preprocessing
  • 1.3 Parameters
  • 1.4. Post Creation
• 2. Validation Issues
  
  • 2.1 Further Validation Measures: Examples
  • 2.2 Problem and Future Work
• 3. Visualizers
• Exercises
  • Exercise 1
  • Exercise 2
  • Exercise 3

 

Find this tutorial @: http://www.matsim.org/node/412

 

1. Traffic Counts 

MATSim provides automated comparisons of the simulation results with traffic counts. To date average hourly volumes can be used. For the Swiss scenarios predominantly the following source is used: ASTRA traffic count data.

The comparison is automatically generated every 10th iteration. Generated output is located in the output-directory of the iteration (usually something like output/ITERS/it.10/).

 (Adopted from User guide traffic counts)

Future Tasks:

• Include variance, max, min, median in station plots not only average value
• Include length and vehicle type classes (e.g., trucks vs. motorcycles) in station plots.

1.1 Output Formats 

• Tables in text files:

• KML file for Google Earth:

 

• HTML to browse the count stations by link:

 

1.2. Preprocessing

Example CH:

 

 

 

1.3 Parameters 

The counts-module offers the following config-parameters:

<module name="counts">
   mandatory:
	<param name="inputCountsFile" value="/path/to/counts.xml" />
	<param name="outputformat" value="txt,html,kml" />

   optional:
	<param name="countsScaleFactor" value="Double > 0 "
	<param name="distanceFilter" value="Double >= 0" />
	<param name="distanceFilterCenterNode" value="String" />
	<param name="outputCountsFile" value="String" />
</module>

inputCountsFile:  [String]

Path to the file containing the real-world traffic counts.

outputformat: [String]

The output format specifies in which format the comparison results are written to disk. It can be any combination of txt, html and kml. Multiple formats can be specified separated by commas. txt writes simple text-tables containing the values to a file. It is most useful to create custom graphs, e.g. in Excel. html creates a directory containing several html files, allowing to browse the results interactively. kml creates a file to be displayed in Google Earth. This last option only works if the correct coordinate system is set.

countsScaleFactor: [Double > 0]; default: 1.0

If you only simulate a sample of your population, the simulated traffic volumes are likely lower than the real-world traffic counts. In order to allow useful comparison, one can specify a factor by which the simulated traffic volumes are multiplied. For example, if you simulate a 25% sample of your full population, specify a countsScaleFactor  of 4.

distanceFilter: [Double] and distanceFilterCenterNode: [String]

If the traffic counts cover a larger area than the area being simulated, the traffic counts outside your area will result in a bad comparison. Instead of removing the traffic counts from the counts.xml, you can specify a filter to only include some traffic counts from the file in the comparison. To activate the filter, specify the id of a node that acts as the center of a circle. The circle has the radius specified in "distanceFilter", the unit being the same unit as the length of links (i.e. usually meters).

outputCountsFile: [String]

1.4. Post Creation 

Take ...

playground.anhorni.kti.CountsAnalyser or
playground.dgrether.analysis.CountsAnalyser

... as an example (will be implemented in the core soon)

Produces kml, txt or html output from the linkstats file (+network file)

 

2. Validation Issues 

2.1.Further Validation Measures: Examples 

Trip length and duration distribution

compare with Swiss Micro Census (PUS) german

Modal split (Example.: Westumfahrung ZH, 2009)

compare with Swiss Micro Census (PUS) german

 

 

Route Switchers

Example.: Westumfahrung ZH, 2009

 

Spideranalysis

Example.: Westumfahrung ZH, 2009

 

 

Volumes

Example.: Westumfahrung ZH, 2009

 

 

2.2. Problem and Future Work

• Lack of Validation Data and System Specification
  • Level of analysis and modeling (e.g. count data vs. avg. trip length, route switcher analysis etc.)
  • Ensemble runs ?  confidence intervals etc. (computational costs!)

 

• Future Measures
  • Travel speeds (e.g., based on GPS data)
  • Facility loads (e.g., based on license plate data or retailer consumer card data)

 

=> A lot of interesting future work!

 

3. Visualizers  

                                                        

OTFVis user guide

OTFVis presentation 2009

 

Exercises: 

1. OTFVis

Building the bypass (WU) has made worse a promiment bottleneck in the region of Zurich. Try to locate it by using the OTFVis. It is best visible between ~ 7:15 and 9:00. It is not visible very clearily in our results, but ... local car drivers say it is there ;)

Hints:

• Compare 2 Westumfahrung runs simultaneously with OTFVis. Use wuIST.mvi (base case) and wuWU.mvi (with bypass).
• Run OTFVis as follows:

 

 

2. Google Earth 

a) Using Google Earth with 100.countscompare.kmz look at the count stations in the south of Switzerland (Tessin, e.g., Lugano, Mendrisio).
b) Look at the count stations in the center of Zurich (e.g., Rosengartenstrasse, Nordring etc.)
c) What is the difference? What is the problem in (a)

 

3. Counts Configuration & OTFVis

Configure a ZH simulation based on zurich-switzerland.xml such that counts are plotted only within a restricted area: center = Bellevue and radius = 10 km.
I.e.; inspect network by OTFVis and define distanceFilterCenterNode in the count section of the configuration file (see Section Parameters)

 

ValidationVisualizationSlides.ppt 5.1 MB