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TraffiQure Technologies

TraffiQure Technologies, a CMU technology spinoff firm, uses Artificial Intelligence and Machine Learning technologies to provide services or software products that help clients make effective decisions in the transportation domain based on massive data. The ultimate goal is to improve the efficiency, reliability and equity of transportation system planning and operation.


TraffiQure works with governmental agencies, non-profit organizations and private transportation firms who operate transportation systems. Examples include federal, state and local department of transportation, public transit agencies, parking agencies, emergency response agencies, mobility service providers.

Services an Products

Services and Products

TraffiQure provides consulting services for clients to understand their data resources for better decision making of transportation systems and provides software programs that are customized for each specific client to improve their day-to-day operation, or long-term system planning. There is no one-size-fit-all AI and ML tool that works for all clients. It is very critical to develop specific strategies for each client to meet its unique managerial goals.

Predictive Analytics for Real-Time Traffic Management

Sensorless Parking Management Systems

First and Last Mile Mobility Services

Public Transportation Systems

Why Traffiqure?

There is a great need to leverage large-scale multi-jurisdictional multi-source data to improve transportation system management. Most public agencies and non-profit organizations do not have the staffing to analyze large-scale data. However, scientists and engineers who are specializing in AI or ML do not understand transportation systems. Simply applying AI and ML technologies without having domain expertise is unlikely to work for transportation systems. TraffiQure has extensive expertise and experience in both AI/ML and transportation engineering.

Why Traffiqure?
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Leveraging Data

  • Waze

  • Twitter

  • OEM telematics

  • Connected vehicles

  • Probe vehicle travel speeds (INRIX, HERE, TomTom, etc.)

  • Speed detectors (Wavetronix or RTMS fixed location sensors)

  • Incident data (crash, events, road closures, etc.)

  • Police stops data

  • Traffic counts (by vehicle classifications)

  • Weather (QCLCD, NWS, RWIS, Nexrad radar, etc.)

  • Automatic passenger counts and vehicle locations data

  • Parking occupancies and transactions data

  • Cellular tower and GPS data

  • Mobility services data (transportation network companies, volunteer services, freight delivery, etc.)

  • U.S. Census socio-demographic data

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