Transportation Engineer/Modeler - Cooperative Driving Automation (CDA) and Digital Twin

Join a forward-thinking team committed to innovating the transportation sector! At Leidos, we support the Federal Highway Administration’s (FHWA) Saxton Transportation Operations Laboratory (STOL), focusing on enhancing transportation operations, safety, mobility, and reducing environmental impacts. STOL champions the integration of emerging technologies such as cooperative driving automation (CDA) and Vehicle-to-Everything (V2X) to revolutionize transportation.

 

Learn more about STOL here! 

 

Role Overview:

We are seeking a dedicated Transportation Engineer/Modeler for Cooperative Driving Automation (CDA) and Digital Twin to join our McLean, Virginia group. You will engage in dynamic projects involving Operations, Safety, Freight, and Access Management and in the growing and rapidly advancing fields of Intelligent Transportation Systems (ITS), CDA, Digital Twin, V2X, and Connected Vehicle (CV) technologies.

 

Key Responsibilities, but are not limited to:

• Conduct research on a variety of transportation engineering projects, which encompass traffic simulation, CDA, Digital Twin, V2X, CV, safety, and Intelligent Transportation Systems (ITS).
• Execute traffic simulation projects across multiple scales, ranging from microscopic to macroscopic levels.
• Develop, refine, and maintain simulation networks, manage comprehensive data analysis, and implement cutting-edge algorithms in an open-source environment.
• Perform cross-disciplinary CDA and Vehicle-to-Everything (V2X) simulations, including automated driving simulation, vehicle dynamics simulation, V2X communication simulation, and sensor simulation.
• Participate in the creation of digital twins and high-definition (HD) maps
• Utilize data mining techniques and algorithms to analyze Connected and Automated Vehicle (CAV) and V2X testing data.
• Create guidance, training, and outreach materials aimed at technical audiences, practitioners, and various stakeholders, focusing on diverse aspects of transportation.
• Develop documentation, reports, manuals, and presentations to effectively communicate project results to intended audiences, ensuring clarity and practical applicability in both oral and written forms.
• Contribute to the development, support, and review of technical proposals.
• Author white papers, proposals, and briefings that demonstrate technical and thought leadership, catering to the needs of Leidos leadership or clients.

Required Qualifications:

• Advanced degree (Master’s or higher) in Transportation Engineering, Systems Engineering, Computer Science, or related fields.
• 2+ years of hands-on experience in professional or academic setting with at least one of microscopic traffic simulation tools (e.g., SUMO, Vissim, Aimsun, Transmolder, or similar).
• 1+ years of hands-on experience in professional or academic setting with cooperative autonomous driving and sensor simulation tools, (e.g., CARLA, LGSVL, CARMAKER, or similar).
• Ability to obtain and maintain a Public Trust clearance (which includes three years of immediate residency in the US).
• Experience in developing digital twin or 3D simulation networks (e.g., CARLA)
• Proficiency in programming for implementing developed algorithms into simulation tools (C++, Java, Python, or Matlab).
• Demonstrated ability to author technical research papers and reports.
• Expertise in advanced data analytics for transportation using Python, or Matlab.
• Knowledge of CAV, Intelligent Transportation Systems, and traffic operation and management.
• Clear communication skills, both verbal and written.

Preferred Experience:

• Experience with using professional tools (e.g., Roadrunner) to develop digital twin and 3D simulation scenes for autonomous driving and sensor simulation tools by.
• Experience with creating high-definition (HD) maps.
• Solid understanding of Vehicle-to-Everything (V2X) communication protocols and experience with communication simulation tools such as NS-3 and OMNET++.
• Experience with vehicle dynamics simulators (e.g., CARSIM and TruckSIM).
• Hands-on experience or familiarity with CARMA ecosystem (e.g., CARMA platform, CARMA streets, CARMA messenger, and CARMA Cloud)
• Experience with implementing artificial intelligence (AI) and machine learning in transportation
• Familiar with augmented reality (AR) and virtual reality (VR) technologies.
• Demonstrated project management skills, with a track record of successfully overseeing projects from inception to completion.
• Capable of developing Requests for Information (RFI), Requests for Proposal (RFP), and managing subcontractor agreements.
• Proven experience in managing subcontractors, ensuring adherence to project specifications and timelines.
• Experience with leading or assisting in the development of technical proposals, showcasing the ability to convey complex ideas effectively.
• Competent in developing cost models, basis of estimates (BOEs), and Bill of Materials (BOM) for diverse projects.
• Agile methodology proficiency, with experience in applying agile practices in development environments.

Team Dynamics:

• Strong team collaboration and ability to engage in constructive feedback.
• Clear communication skills, both verbal and written.
• Adherence to schedules with a focused work ethic.
• Receptive to professional growth and learning.
• High quality standards and work pride.
• Enthusiasm for the field of transportation simulation and technology.

 

Anticipated pay range for this position: $80,000-$110,000

Original Posting Date:

2024-07-09

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $65,000.00 - $117,500.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.