Develop Configurable Advanced Traffic Management Systems Software to Expand Applications, Lower Support Costs, and Enhance Travel Experience While Addressing Fast-Changing Conditions with Automation.
Overview of the Nationwide Advanced Transportation Systems Deployment Program Granting Projects to Transportation Agencies over Four-Year Fiscal Periods Produced Lessons Learned on Various Technologies.
Nationwide, United States
Cleveland, Ohio, United States
2022 Program Report Advanced Transportation and Congestion Management Technologies Deployment (ATCMTD) Program
Summary Information
The Fixing America’s Surface Transportation Act (FAST Act) established the Advanced Transportation and Congestion Management Technologies Deployment (ATCMTD) Program to allow for competitive grants for the deployment of advanced transportation technologies. This study provided an overview of fiscal years 2016–2020 ATCMTD projects (58 grants in total from all over USA) and described the findings from one completed project, a fiscal year 2017 grantee, namely the Greater Cleveland Regional Transit Authority (RTA), completing its project as of March 31, 2022. This study also highlighted performance measures used by grantees, grantee insights, as well as lessons learned regarding their technology deployments. Some of the key technologies considered in the granted projects included Connected Vehicles (CVs) and connected infrastructure, real-time traveler information, Integrated Corridor Management (ICM) and Decision Support Systems (DSS), infrastructure maintenance and monitoring technologies, adaptive traffic signal control, Artificial Intelligence (AI), Machine Learning (ML), and advanced analytics, Automated Vehicles (AVs), and green technology such as light-emitting diode (LED) lighting, electric vehicle shuttles.
- Develop configurable Advanced Traffic Management Systems software to expand applications, lower support costs, and enhance travel experiences. Use test zones inside the TMC for developers to access network and operation systems with safety protection and firewall regulations. Understand the weather-related challenges, such as extreme summer heat, for effective AV deployment.
- Bring together AI and human intelligence to create machine learning models. Combine advanced deep learning models with engineering judgement for AI applications of traffic operations and management which helps manage missing and corrupted data.
- Engage stakeholders and agencies early in the deployment process to ensure consistent coordination and project success. Early engagement is especially valuable when involving multiple agency partners or large geographic areas. Workshops and educational materials can help address challenges with a range of end users, such as the trucking community. Forming an advisory committee of regional agencies can provide leadership and support collaboration, and a detailed understanding of network connectivity and firewall protocols is essential when partnering with agency stakeholders.
- Collaborate with industry and vendors early in the process in a design-build fashion to save iterations and project costs. Telematics and third-party software companies should be engaged early in the process to help determine opportunities to integrate project data feed into existing infrastructure.
- Conduct detailed project scoping and site surveys before development to avoid delays. Ensure sufficient coverage of qualified technicians to achieve project goals, and consider existing mounting locations and line of sight, which may impact adaptive pedestrian safety systems and increase equipment needs. Account for testing, validation, and correction time in delivery schedules to allow for repeated testing phases.
