The Marketing team at Swim analyzed available United States Department of Transportation’s traffic project estimates to pinpoint the cost of alleviating traffic concerns in various US markets through the use of software. Swim wanted to identify the traffic optimization opportunities that would benefit from the use of Internet of Things (IOT) technologies, sensor data, and machine learning, which would also reduce traffic costs & expenditures while optimizing and alleviating traffic conditions.
Here are some of the opportunities we’ve analyzed in our Operations & Management (O&M) Cheat Sheet for Smart Cities, Intelligent Traffic Systems (ITS), and Traffic Managment Centers (TMC's) and how to optimize & alleviate traffic in your Smart City:
The USDOT has found that the average annual delay per US commuter rose from 37 hours in 2000 to 42 hours in 2014, a 13.5 percent increase, and the combined hours of delay experienced by all commuters across the Nation in 2014 reached 6.9 billion hours—about a third higher than the 2000 total. According to a survey by the Intelligent Transportation Society of America, 71% of US State ITS project were implemented in order to relieve congestion and traffic delays. The USDOT maintains a cost database, which makes available estimates for major public Intelligent Transportation System (ITS) projects around the country. These projects are critical to USDOT goals.
In 2016, the City of Miami Beach, Florida, targeted a retrofit of their existing Transportation Management Center (TMC) and related ITS systems. They estimated that a complete build-out of a stand-alone TMC could cost $1 Million to $2 Million, and that retrofitting existing equipment could cost $331,000. In addition to the $331,000, the city estimated that the cost of installing smart signals to support an adaptive signal control system would be $50,000 per intersection. The city also determined that Operations & Management (O&M) costs for the TMC would be 10% of construction costs annually, and that O&M for field devices would be 10% of capital costs, annually. Total costs for the project are broken down in the chart below:
Miami TMC retrofit Costs Breakdown (2016) Source: USDOT
In 2011, the State of Maryland undertook a similar project with the Maryland Regional Integrated Transportation Information System (RITIS). The objectives of the RITIS project were to incorporate data from several types of sources including transit Automatic Vehicle Locations (AVL), traffic cameras, crash data, emergency responder dispatch, and weather information. The data comes from several agencies and in unstandardized formats across multiple systems. RITIS standardizes the raw data from the various agencies and displays it through multiple visualization tools in order to allow participating agencies to improve incident response, as well as traveler information. According to the director of the CATT Laboratory at the University of Maryland, (who is managing the RITIS project), maintaining RITIS costs about $400,000 per year, but costs will increase as the number of participating agencies and amount of data continues to grow.
In 2010, the City of Portland, Oregon, determined that the capital cost to install a next generation transit signal priority system in the city was $500,000, with annual O&M costs of $850,000 per year. This project fit into Portland’s greater Transportation System Management and Operations (TSMO) vision, which aimed to provide public agency staff, transportation operations professionals, and private representatives of the traveling public with real-time data about the municipality’s traffic operations. The city estimated that O&M costs for the TSMO initiative at $3 Million annually.
According to Machina Research, public authorities and their technology partners could squander $341 billion by 2025 if they adopt a fragmented versus standardized approach to IOT solution deployment. Using IOT technologies to integrate systems from multiple agencies and data sources could have a major impact on lowering O&M costs, device maintenance costs, and reducing the amount of server infrastructure required to run these systems. These savings would be achieved by intelligently processing data at the edge, into a structure consumable by ITS systems. These structured streams could be aggregated on the edge or in the cloud, to perform predictive maintenance for field devices and deliver real-time alerts about traffic system performance.
By providing more relevant, enriched data streams to ITS systems, IOT technologies can significantly reduce the costs of retrofitting existing traffic systems. IOT technologies can transform currently deployed hardware into modern, intelligent traffic systems and greatly reduce the capital costs and recurring O&M expenses for new ITS deployments.
Learn how Swim ESP™ for Smart Cities can help optimize and alleviate traffic conditions in your Operations & Management (O&M) for Smart Cities. Swim ESP can help transform and manage your traffic sensor data using Machine Learning on your ITS and in your TMC's.
Sources: ITSA, City of Miami Beach (USDOT), Maryland Regional Integrated Transportation Information System (USDOT), Portland area (USDOT), Portland TripCheck Travel Information Portal (USDOT), Machina Research