Project activity by year

Year 1

Decide how to do traffic and vehicle simulations

TrafficSimulators_GettingStartedWithDifferrentSimulators_GettingStartedWithCARLA: Launch page to get started with CARLA (cloned from IVSG on 2023 06 05)

TrafficSimulators_GettingStartedWithDifferrentSimulators_GettingStartedWithSUMO: Launch page to get started with SUMO (cloned from IVSG on 2023 06 05)

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)

Year 2

The data flow of the simulation is below

_images/PennDOT_Simulation_Workflow_V2.drawio.png

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.

Situation 1 Summary
Situations	Urban
City	PA, State College
Location Description	BEAVER AV Between Sparks St and Gill St
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	https://gis.penndot.gov/tire/tms-sites/1134/report

Situation 2 Summary
Situations	Arterial
City	PA, State College
Location Description	COLLEGE AV 0.65 MILE NORTHEAST OF SR-3022
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	https://gis.penndot.gov/tire/tms-sites/1136/report

Situation 3 Summary
Situations	Highway
City	PA, State College
Location Description	I-99 1.35 Mile North of Exit 71
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	https://gis.penndot.gov/tire/tms-sites/1180/report

The following table shows the summary about whether the considered three roadway situations could be applied to each of the proposed 20 scenarios.

20 Scenarios - 3 Situations Sumamry
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	WORK ON OR BEYOND SHOULDER SINGLE LANE APPROACH SHOULDER WORK	Y	Y	Y	Urban peak volume
1.2	ROAD CLOSURE WITH DETOUR STANDARD ORANGE DETOUR SIGN	Y	Y	Y
1.3	WORK ON SINGLE LANE APPROACH SELF-REGULATING LANE SHIFT INTO OPPOSING LANE	N	N	Y
1.4	WORK ON SINGLE LANE APPROACH SELF-REGULATING LANE SHIFT INTO CENTER LEFT-TURN LANE	N	N	Y
1.5	WORK ON A SINGLE-LANE APPROACH WORK IN CENTER LEFT-TURN LANE	Y	Y	N
1.6	WORK ON MULTI-LANE APPROACH WORK IN RIGHT LANE UNDIVIDED HIGHWAY	N	N	Y
2.1	ROAD CLOSURE WITH DETOUR DETOUR OF A NUMBERED TRAFFIC ROUTE	Y	Y	Y
2.2	WORK ON A SINGLE-LANE APPROACH SELF-REGULATING STOP-CONTROL	Y	Y	Y
2.3	LANE SHIFT TO TEMPORARY ROADWAY	Y	Y	Y
2.4	WORK ON SINGLE-LANE APPROACH TRAILOR-MOUNTED SIGNALS	Y	Y	Y
3.1	WORK ON SINGLE-LANE APPROACH MOVING LANE CLOSURE	Y	Y	Y
4.1a	WORK ON 2-LANE APPROACH WORK IN RIGHT LANE	Y	Y	Y
4.1b	WORK ON 2-LANE APPROACH WORK IN RIGHT LANE	N	N	Y
4.2	WORK NEAR INTERCHANGE RAMPS WORK IN RIGHT LANE NEAR EXIT RAMP	N	N	Y
4.3	WORK NEAR INTERCHANGE RAMPS WORK IN ENTRANCE RAMP, STOP CONTROL	N	N	Y
5.1a	WORK ON 2-LANE APPROACH WORK IN RIGHT LANE (MOBILE)	Y	Y	Y
5.1b	WORK ON 2-LANE APPROACH WORK IN RIGHT LANE (MOBILE) (TURNPIKE)	N	N	Y
5.2	WORK ON 3-LANE APPROACH WORK IN LEFT LANE (MOBILE)	Y	Y	Y
6.1	WORK ON 2-LANE APPROACH LONG TERM SHOULDER USE	Y	Y	Y

Variance analysis of simulation results

The daily volume trends of urban, arterial and highway are summarized below:

We did an analysis of variance to check whether simulated flow is the same as the set flow and to find the minimum simulation time.

The flow is estimated every 1 min. The data used below is right from the peak start time or off-peak start time, from the detector on the test track for two lanes.

The results are shown as below.

_images/urbanResults.png — Results for urban

_images/arterialResults.png — Results for arterial

Analysis for highway is ongoing.

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).

_images/fcn_Points_fillPointSampleSets_Ex3.jpg

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

_images/TTCexample.png — Example of TTC calculation

_images/PETexample.png — Example of PET calculation

_images/lanechange.gif — Demo of vehicle doing a lane change

Automatic generation of work zone simulation scenarios

The automatic generation of scenarios for simulation that follow the workflow as below:

_images/AutomaticGenerationOfScenarios.drawio.png

The source file of this workflow diagram can be found here: https://drive.google.com/file/d/18G0Bb3WNbk9Mf6DgM548p8j4xtOKnf1m/view?usp=sharing

Scenarios defined in KMZ format are loaded into GIS software, such as Google Earth.

_images/googleEarth.png — This contains all data for the CAD definition, but most of this is not needed within final road definition as per ASAM OpenDRIVE.

The KMZ files can be found here: https://github.com/ivsg-psu/FieldDataCollection_VisualizingFieldData_PlotWorkZone/tree/main (IVSG internal)

The KMZ definition is then parsed to KML, where coordinates are readable.

The KML files can be found here: https://github.com/ivsg-psu/FieldDataCollection_VisualizingFieldData_PlotWorkZone/tree/main (IVSG internal)

The KML definition is parsed in MATLAB. It illustrates driving lanes and traffic objects in LLA coordinate system.

Using the KML data, we can plot all the scenarios with each other to identify common lane markers and road segments.

_images/All_lane_markers_plotted_together.png

The driving lanes in LLA coordinates are then transformed into ENU coordinates. This uses the Cartesian coordinates to ease the creation of XODR definitions.

Non-smooth data points contain large gaps, and this causes problems when the road is created.

_images/TestTrack_nonSmooth.png — Example of test track created with non-smooth data points

_images/TestTrack_RRSmoothError.png — Problem of misalignment caused by the non-smooth data points

The ENU coordinates are then resampled for geometric smoothness to avoid the large gaps

_images/testTrackENU_raw.png — Raw ENU data of test track

_images/testTrackENU_resampled.png — resampled ENU data of test track

The resampled ENU coordinates are then converted to XODR definition.

The xodr file can be found as testTrack.xodr with this link: https://github.com/PAWorkzoneAutomation/PAWorkzoneAutomation.github.io/tree/main/Data/MapImports/XODR

The XODR file is then editable to apply to different scenarios, for example, changing the lane width. Below shows an example of increasing the right driving lane width.

_images/laneWidth_original.png — Original

_images/laneWidth_increased.png — Lane width increased

Below shows another example of increasing the right driving lane width at 500 meters from the start line.

The xodr file can be found as testTrack_increasedLaneWidth.xodr with this link: https://github.com/PAWorkzoneAutomation/PAWorkzoneAutomation.github.io/tree/main/Data/MapImports/XODR

XODR can be imported into RoadRunner.

_images/testTrack_xodrviewer.png — Road imported into XODR viewer (open-source)

_images/testTrack_RR.png — Road imported into RoadRunner (commercial)

The xodr file can be found as testTrack.xodr with this link: https://github.com/PAWorkzoneAutomation/PAWorkzoneAutomation.github.io/tree/main/Data/MapImports/XODR

RoadRunner exports into CARLA and SUMO.

_images/testTrack_CARLA.png — Test track imported into CARLA

_images/testTrack_SUMO.png — Test track imported into SUMO

The files needed for map imports can be found with this link: https://github.com/PAWorkzoneAutomation/PAWorkzoneAutomation.github.io/tree/main/Data/MapImports

Year 3

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).

Name	Server ID	Base Station LLA Coordinates	Datumn	Installation Date	Last Calibration Date	Note
LTI Test Track Base Station	PSU_TestTrack	TBD	WGS 84	TBD	TBD	Installed and maintained by IVSG.
Reber 320 Base Station	PSU_Reber320	40.79365087° -77.86460284° 334.719 m	WGS 84	11/28/2022	01/07/2023	Installed and maintained by IVSG, this base station is moveable so it cannot be used as a CORS station
Reber 339 Base Station	PSU_Reber339	40.79333290° -77.86441976° 334.733 m	WGS 84	11/28/2022	01/08/2023	Installed and maintained by IVSG, this base station is moveable so it cannot be used as a CORS station
Transportation Research Building Base Station	PSU1	40.8068919389° -77.8497968306° 337.665 m	WGS 84	TBD	TBD	Installed and maintained by PennDOT, its LLA coordinates may not be correct.