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US Department of Transportation (USDOT) Intelligent Transportation Systems (ITS) Joint Program Office (JPO) Operational Data Environemnt (ODE)
The ITS ODE is a real-time virtual data router that ingests and processes operational data from various connected devices - including vehicles, infrastructure, and traffic management centers - and distributes it to other devices and subscribing transportation management applications. Using the ITS ODE within intelligent transportation deployments increases data fluidity and interoperability while meeting operational needs and protecting user privacy. The software’s microservices architecture makes it easy to add new capabilities to meet local needs. Check the ITS factsheet for more information: https://www.its.dot.gov/factsheets/pdf/ITSJPO_ODE.pdf.
Figure 1: ODE Dataflows
Documentation:
All stakeholders are invited to provide input to these documents. To provide feedback, we recommend that you create an "issue" in this repository (https://github.com/usdot-jpo-ode/jpo-ode/issues). You will need a GitHub account to create an issue. If you don’t have an account, a dialog will be presented to you to create one at no cost.
Once the ODE is deployed and running locally, you may access the ODE's demonstration console by opening your browser and navigating to http://localhost:8080
.
Connect
button to connect to the ODE WebSocket service.Select File
button to select an OBU log file containing BSMs and/or TIM messages as specified by the WYDOT CV Pilot project. See below documents for details:
Upload
button to upload the file to ODE.Upload records within the files must be embedding BSM and/or TIM messages wrapped in J2735 MessageFrame and ASN.1 UPER encoded, wrapped in IEEE 1609.2 envelope and ASN.1 COER encoded binary format. Please review the files in the data folder for samples of each supported type. By uploading a valid data file, you will be able to observe the decoded messages contained within the file appear in the web UI page while connected to the WebSocket interface.
Another way data can be uploaded to the ODE is through copying the file to the location specified by the ode.uploadLocationRoot/ode.uploadLocationObuLog
property. If not specified, Default locations would be uploads/bsmlog
sub-directory off of the location where ODE is launched.
The result of uploading and decoding of messages will be displayed on the UI screen.
Figure 2: ODE UI demonstrating message subscription
Notice that the empty fields in the J2735 message are represented by a null
value. Also note that ODE output strips the MessageFrame header and returns a pure BSM or TIM in the subscription topic.
With the PPM module running, all filtered BSMs that are uploaded through the web interface will be captured and processed. You will see an output of both submitted BSM and processed data unless the entire record was filtered out.
The ODE software can run on most standard Window, Mac, or Linux based computers with Pentium core processors. Performance of the software will be based on the computing power and available RAM in the system. Larger data flows can require much larger space requirements depending on the amount of data being processed by the software. The ODE software application was developed using the open source programming language Java. If running the ODE outside of Docker, the application requires the Java 8 runtime environment.
The ODE is bundled as a series of submodules running in Docker containers and managed by Docker-Compose. All other required dependencies will automatically be downloaded and installed as part of the Docker build process.
Read the following guides to familiarize yourself with ODE's Docker and Kafka modules.
Installation and Deployment:
git
commands may fail for similar reasons, you can fix this by running export GIT_SSL_NO_VERIFY=1
.Configuration:
If you wish to change the application properties, such as change the location of the upload service via ode.uploadLocation.*
properties or set the ode.kafkaBrokers
to something other than the $DOCKER_HOST_IP:9092
, or wish to change the log file upload folder, etc. instead of setting the environment variables, modify jpo-ode-svcs\src\main\resources\application.properties
file as desired.
ODE configuration can be customized for every deployment environment using environment variables. These variables can either be set locally or using the sample.env file. Instructions for how to use this file can be found here.
Important!
You must rename sample.env
to .env
for Docker to automatically read the file. This file will contain AWS access keys and other private information. Do not push this file to source control.
The following instructions describe the minimal procedure to fetch, build, and run the main ODE application. If you want to use the privacy protection module and/or S3 depositors, see the User Guide for more detailed information. Additionally, different build processes are covered at the bottom of this section.
If running on Windows, please make sure that your global git config is set up to not convert end-of-line characters during checkout.
Disable git core.autocrlf
(One Time Only)
git config --global core.autocrlf false
The ODE software system consists of the following modules hosted in separate Github repositories:
Name | Visibility | Description |
---|---|---|
jpo-ode | public | Contains the public components of the application code. |
jpo-cvdp | public | Privacy Protection Module |
jpo-s3-deposit | public | S3 depositor service. Optional, comment out of docker-compose.yml file if not used. |
asn1_codec | public | ASN.1 Encoder/Decoder module |
jpo-security-svcs | public | Provides cryptographic services. |
jpo-sdw-depositor | public | SDW depositor service. Optional, comment out of docker-compose.yml file if not used. |
You may download the stable, default branch for ALL of these dependencies by using the following recursive git clone command:
git clone --recurse-submodules https://github.com/usdot-jpo-ode/jpo-ode.git
Once you have these repositories obtained, you are ready to build and deploy the application.
The above steps to pull the code from GitHub repository pulls it from the default branch which is the stable branch. If you wish to pull the source code from a branch that is still under development or beta testing, you will need to specify the branch to pull from. The following commands aid you in that action.
**Note**: These commands can also be performed using the provided script `update_branch`.
```bash
# Backup user provided source or configuration files used by submodules
cp asn1_codec/asn1c_combined/J2735_201603DA.ASN .
# Run the following commands to reset existing branch
git reset --hard
git submodule foreach --recursive git reset --hard
# Pull from the non-default branch
git checkout
Notes:
sample.env
to .env
. This file will contain private keys, do not put add it to version control.Copy the following files from jpo-ode
directory into your DOCKER_SHARED_VOLUME directory.
config.properties
file in a text editor and update the metadata.broker.list=your.docker.host.ip:9092
line with your system's DOCKER_HOST_IP in place of the dummy your.docker.host.ip
string.Navigate to the root directory of the jpo-ode project and run the following command:
docker-compose up --build -d
docker-compose ps
To bring down the services and remove the running containers run the following command:
docker-compose down
For a fresh restart, run:
docker-compose down
docker-compose up --build -d
docker-compose ps
To completely rebuild from scratch, run:
docker-compose down
docker-compose rm -fvs
docker-compose up --build -d
docker-compose ps
Check the deployment by running docker-compose ps
. You can start and stop containers using docker-compose start
and docker-compose stop
commands.
If using the multi-broker docker-compose file, you can change the scaling by running docker-compose scale <container>=n
where container is the container you would like to scale and n is the number of instances. For example, docker-compose scale kafka=3
.
ODE requires the deployment of asn1_codec module. ODE's docker-compose.yml
file is set up to build and deploy the module in a Docker container. If you wish to run asn1_codec
module outside Docker (i.e. directly on the host machine), please refer to the documentation of asn1_codec
module.
The only requirement for deploying asn1_codec
module on Docker is the setup of two environment variables DOCKER_HOST_IP
and DOCKER_SHARED_VOLUME
.
To run the ODE with PPM module, you must install and start the PPM service. PPM service communicates with other services through Kafka Topics. PPM will read from the specified "Raw BSM" topic and publish the result to the specified "Filtered Bsm" topic. These topic names are specified by the following ODE and PPM properties:
Follow the instructions here to install and build the PPM service.
During the build process, edit the sample config file located in config/example.properties
and point the property metadata.broker.list
towards the host of your docker machine or wherever the kafka brokers are hosted. You may use the command docker-machine ls
to find the kafka service.
After a successful build, use the following commands to configure and run the PPM
cd $BASE_PPM_DIR/jpo-cvdp/build
$ ./bsmjson_privacy -c ../config/ppm.properties
This section outlines the software technology stacks of the ODE.
Install the IDE of your choice:
Contact the developers of the ODE application by submitting a Github issue.
Contact the ODE management representative using the information in the Code.gov Registration Info section.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either expressed or implied. See the License for the specific language governing permissions and limitations under the License.
Please read our contributing guide to learn about our development process, how to propose pull requests and improvements, and how to build and test your changes to this project.
https://usdotjpoode.atlassian.net/secure/RapidBoard.jspa?projectKey=ODE
https://usdotjpoode.atlassian.net/wiki/
https://travis-ci.org/usdot-jpo-ode/jpo-ode
https://sonarcloud.io/organizations/usdot-jpo-ode/projects
Code quality assurance is reported through the usdot-jpo-ode SonarCloud organization. Code quality reports are generated by the JaCoCo plugin for Maven during the ODE's webhook-triggered TravisCI build. After a successful build, the SonarQube scanner plugin for Maven creates and uploads a code quality report to SonarCloud.
For regression and user acceptance testing, ODE provides an automated test harness. The test harness is pprovided in the qa/test-harness directory under jpo-ode root folder. The test harness uses the ODE Validator Library repository as a submodule.
For more information, please see: https://github.com/usdot-jpo-ode/jpo-ode/wiki/Using-the-ODE-test-harness
Date: 07/2017
In its current state, the ODE has been developed to accomplish the goals of data transfer, security, and modularity working with the J2735 and 1609.2 security. The system has been designed to support multiple services orchestrated through the Apache Kafka streaming data pipelines, services built and supported as separate applications and described with each service's repository. As a modular system, each component has been built for functionality first, and additional performance testing is needed to understand the limits of the system with large volumes of data.
Please read our Wiki for more information, or check the User Guide.
Application Support for the ODE currently managed via GitHub's native issue tracker: https://github.com/usdot-jpo-ode/jpo-ode/issues.
Agency: DOT
Short Description: The ITS ODE is a real-time virtual data router that ingests and processes operational data from various connected devices – including vehicles, infrastructure, and traffic management centers – and distributes it to other devices and subscribing transportation management applications. Using the ITS ODE within intelligent transportation deployments increases data fluidity and interoperability while meeting operational needs and protecting user privacy. The software’s microservices architecture makes it easy to add new capabilities to meet local needs.
Status: Beta
Tags: transportation, connected vehicles, intelligent transportation systems, java
Labor hours: 200
Contact Name: James Lieu
Contact Phone: (202) 366-3000
The ODE can be run in a k8s environment. See this document for more details about this.