Project activity by topic
Decide how to do traffic and vehicle simulations

TrafficSimulators_GettingStartedWithDifferrentSimulators_GettingStartedWithCARLA: Launch page to get started with CARLA

TrafficSimulators_GettingStartedWithDifferrentSimulators_GettingStartedWithSUMO: Launch page to get started with SUMO

TrafficSimulators_GettingStartedWithDifferrentSimulators_GettingStartedWithCARLA-SUMOCosimulation: Launch page to get started with CARLA-SUMO cosimulation (IVSG - PSU internal)

Mapping
About the Mapping Van
Mapping_MappingVan_About: General information about the Penn State Mapping Van. Mapping van is shown below.

Choice of Coordinate Systems for Wide Areas
Mapping_CoordinateSystems_WideAreas: Discussion of coordinate systems and the errors each can introduce when mapping large areas (cloned from IVSG on 2023 04 03).The coordinate system conversions through simulation work are as below.

Hardware installation
Hardware_MappingVanHardware_CADdrawings: The mapping van measurements used for the GPS antenna calibration. Sample CAD drawings are below.


Power System
Hardware_MappingVanHardware_PowerSystem: Setup of power system (IVSG - PSU internal)
Time Synchonization
FieldDataCollection_TypicalHardwareSetups_TriggerCameraUsingExternalSignal:Methods to externally trigger FLIR cameras to external trigger signals. (IVSG - PSU internal)
FieldDataCollection_TypicalHardwareSetups_TimeSync_ArduinoUsingGPSPPS: Producing tight time-trigger pulses (less than 20 microseconds jitter) via Arduinos. (IVSG - PSU internal)
FieldDataCollection_TypicalHardwareSetups_TimeSyncTriggerBox: CAD models for trigger box. (IVSG - PSU internal)
Sensors - Cameras
Hardware_MappingVanHardware_Camera: Remounting the cameras to improve regidity, water intrusion, and hardware faults. (IVSG - PSU internal)
Camera Calibration : Methods used to calibrate the camera system. (IVSG - PSU internal)
Sensors - LIDAR
Hardware_MappingVanHardware_LiDAR: Documents of LiDAR specs. (IVSG - PSU internal)
FieldDataCollection_TypicalHardwareSetups_LIDARs_CeptonX90Install: Procedure of installing CeptonX90 LiDAR. (IVSG - PSU internal)
FieldDataCollection_TypicalHardwareSetups_LIDARs_VelodyneVLP16Install: Procedure of installing VelodyneVLP16 LiDAR. (IVSG - PSU internal)
Sensors - Wheel Encoders
Hardware_MappingVanHardware_Encoder: Setup of encoders. (IVSG - PSU internal)
Sensors - Radar
Hardware_MappingVanHardware_Radar: Setup of Radar. (IVSG - PSU internal)
Sensors - GPS
Hardware_MappingVanHardware_GPS: Setup of GPS. (IVSG - PSU internal)
Sensors - IMU
Hardware_MappingVanHardware_IMU: Setup of IMU. (IVSG - PSU internal)
Sensors - Steering System
Hardware_MappingVanHardware_SteeringSystem: Setup of steering system. (IVSG - PSU internal)
Data Parsing
FieldDataCollection_DataCollectionProcedures_ParseRawDataToDatabase: Parse raw data (.bag) to raw data database. (IVSG - PSU internal)
FieldDataCollection_DataCollectionProcedures_DataTransferWithDMS:Transfer data to PennDOT DMS. (IVSG - PSU internal)
FieldDataCollection_DataCollectionProcedures_AutomatingDataTransferToDMSUsingCommandLine: Transfer data to PennDOT DMS using command line tools. (IVSG - PSU internal)
FieldDataCollection_DataCollectionProcedures_StitchingImagesToVideo:Stitching parsed images into a video. (IVSG - PSU internal)
The data flow of the simulation is below

For zoomed-in view, please see: https://github.com/PAWorkzoneAutomation/PAWorkzoneAutomation.github.io/blob/main/Images/PennDOT_Simulation_Workflow_V2.drawio.png
Simulating construction scenarios
Simulating a traffic flow on Penn State test track: The work in this area involves information to guide how to simulate a traffic flow on Penn State test track. (IVSG - PSU internal)

The following tables show the three roadway situations for the simulation: urban, artirial and highway, including the location we picked in State College and the corresponding data link.
Situations |
Urban |
---|---|
City |
PA, State College |
Location Description |
|
Site Number |
1134 |
Data Time |
Nov 16, 2016 |
Peak Time |
8AM |
Peak Volume (Vehicles/h) |
696 |
Off-peak Time |
1PM |
Off-peak Volume (Vehicles/h) |
368 |
Link to Real Traffic Data |
Situations |
Arterial |
---|---|
City |
PA, State College |
Location Description |
|
Site Number |
1136 |
Data Time |
Nov 16, 2016 |
Peak Time |
5PM |
Peak Volume (Vehicles/h) |
2374 |
Off-peak Time |
9AM |
Off-peak Volume (Vehicles/h) |
1212 |
Link to Real Traffic Data |
Situations |
Highway |
---|---|
City |
PA, State College |
Location Description |
|
Site Number |
1180 |
Data Time |
Dec 05, 2017 |
Peak Time |
4PM |
Peak Volume (Vehicles/h) |
4046 |
Off-peak Time |
9AM |
Off-peak Volume (Vehicles/h) |
2321 |
Link to Real Traffic Data |
The following table shows the summary about whether the considered three roadway situations could be applied to each of the proposed 20 scenarios.
Scenario |
Scenario Summary |
Urban |
Arterial |
Highway |
Uploaded to DMS |
---|---|---|---|---|---|
0 |
ANALYSIS OF VARIANCE |
Y |
Y |
Y |
Urban peak volume Urban off-peak volume Arterial peak volume Arterial off-peak volume |
1.1 |
|
Y |
Y |
Y |
Urban peak volume |
1.2 |
|
Y |
Y |
Y |
|
1.3 |
|
N |
N |
Y |
|
1.4 |
|
N |
N |
Y |
|
1.5 |
|
Y |
Y |
N |
|
1.6 |
|
N |
N |
Y |
|
2.1 |
|
Y |
Y |
Y |
|
2.2 |
|
Y |
Y |
Y |
|
2.3 |
LANE SHIFT TO TEMPORARY ROADWAY |
Y |
Y |
Y |
|
2.4 |
|
Y |
Y |
Y |
|
3.1 |
|
Y |
Y |
Y |
|
4.1a |
|
Y |
Y |
Y |
|
4.1b |
|
N |
N |
Y |
|
4.2 |
|
N |
N |
Y |
|
4.3 |
|
N |
N |
Y |
|
5.1a |
|
Y |
Y |
Y |
|
5.1b |
|
N |
N |
Y |
|
5.2 |
|
Y |
Y |
Y |
|
6.1 |
|
Y |
Y |
Y |
Simulation post processing
FeatureExtraction_Association_PointToPointAssociation: Functions are provided to determine matches between data sets of (X,Y) points, store and compare groups of associated points (patch objects), and determine intersections between patch objects and circular arcs (useful for collision detection).

FeatureExtraction_SafetyMetrics_SafetyMetricsClass: MATLAB code implementation of functions that perform safety metric calculations given a set of objects and a path through them.

Time to collision

Demo of vehicle doing a lane change
GPS and CORS Calibration
FieldDataCollection_GPSRelatedCodes_RTKCorrectionService: Setting up and using of Real-time kinematic (RTK) via Networked Transport of RTCM via Internet Protocol (NTRIP).(IVSG - PSU internal).

Data Processing
Processing GPS Data
DataProcessing_GPS_GPSConversionMethods: A repo sharing the algorithms used for GPS conversions, e.g. LLA to ENU (cloned from IVSG on 2023 04 03).
Maps and scenarios
FieldDataCollection_VisualizingFieldData_PlotWorkZone: A repo displaying the scenarios and their descriptions. (IVSG - PSU internal)

Data collection for on-track tests

Data Management System (DMS)

The data tags definition is below:
Stage - either “Simulation”,”TestTrack”,”OnRoad”
ScenarioNumber - the ID number for the Scenario
ScenarioShortName - the “short” name for the Scenario
Treatments - These are 3 subfields, for HD maps, Comms, Coatings - each for “with” and “without”
DataSource - either “AV” or “MappingVan” or “Roadside”
Per-treatment data - “MergedMap” or “ProcessedMetrics” or “CARLAScenario” or “Codes”
Aggregated mapping data - “Precalibration”, “Prerun”, “Postrun”, “Postcalibration”
Individual run data - the run number, e.g. pass number 1 of the AV
To be added:
About the DMS
Accessing the DMS from the public
Accessing the DMS from the team
Process for data upload/download
Automonous Vehicle testing
To be added:
About the AV
the AV equipment
the AV setup
the AV testing
the AV sample data
the AV results
Coatings
To be added:
About coatings
Coating details used in the project
Calibration of the coatings
Coating tests
Coating results
CV2X
To be added:
About CV2X
CV2X equipment
CV2X setup
CV2X testing
CV2X sample data
CV2X results
Work Zone Instrumentation
About Work Zone Instrumentation
Work Zone Instrumentation equipment
Work Zone Instrumentation setup
Work Zone Instrumentation testing
Work Zone Instrumentation sample data
Work Zone Instrumentation results