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TrafficGenius uses AI to optimize traffic light timing, reducing congestion, emissions, and costs. Join us in the future of smart transportation.
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Solving cities traffic problem through Ai driven traffic light timing. Seed Round Scott Murdoch, PhD C: 616-283-0059 E: smurdoch@trafficgenius.co
Traffic Congestion cost time, money, and emissions • The United States loses approximately $87 billion a year in lost productivity to traffic congestion. • Boston, MA; District of Columbia; Chicago, IL make up the three most congested cities in the U.S. Roughly $2,000 per driver in lost wages annually. • 30 million tons of CO2 are emitted yearly just from idling non-commercial vehicles.
What TrafficGenius does… • TrafficGenius uses Machine Learning to adjust the timing of traffic signals in a consecutive order along the path of greatest congestion. • Use Case: How many of us have sat at the end of a long line through multiple light cycles with no traffic on the perpendicular intersection. Why does this need to be the case? It’s underutilized public good.
The Time is Now • Advancement in technology using Machine Learning has been wide-spread in the private sector. • Smart Cities initiatives are increasing as cities focus on greater efficiencies of their resource to reduce emissions and compete for the business of large corporations. • International Data Corporation ‘global spending on smart cities initiatives will reach $189.5 billion in 2023’
Team • Scott Murdoch, PhD - Founder • Data Scientist with over 10+ years of experience. • Ph.D. in Economics, dissertation on forecasting; using machine learning. • Ridiculously ambitious, work on TrafficGenius as much as I can even with 2 young kids, and a full-time job. • Frederick Schwartz - Advisor • 40 years experience in transportation engineering • BSCE Purdue, MBA University of Miami • Professional career in firm management and leadership • Principal in Rush Street Consulting
Market • Intelligent Transport System market is estimated at 21 billion for 2018 • Forecast to 29 billion by the end of 2024
Players • Surtrac by Rapid Flow – Spun out of Carnegie Mellon, looks at real-time traffic data from sensors and optimized in local grids, or neighborhoods. • In|Sync by Rhythm Engineering - Collects data in real-time, processes locally at the intersection, not at the center controller. One of the larger traffic engineering • Split Cycle Offset Optimization Technique (SCOOT) – Less advanced version of Surtrac, based in United Kingdom market.
Our Advantage - How we differ • Focus on city-wide, global, approach rather than a localized approach – neighborhood or corridor. • Data driven, machine learning, approach that uses historical patterns as well as real-time to forecast near future patterns, reducing forecast backups before they occur.
Product • Two product streams: • Municipalities: implementation and maintenance of algorithm at the central controller. • Automakers: TrafficGenius will be the sole holder of the algorithm that controls traffic light timing. Meaning we will have the quickest route to your destination. We plan to sell the timing to automakers for there onboard GPS.
Progress • TrafficGenius is in the pre-revenue seed stage. • Completed a very large undertaking of researching open source Traffic data with detailed daily history. • Determined the City of Chicago was the most complete. • City of Chicago data is detailed, yet not complete. Additional data was collect manually, which was time intensive. • Data Complete -> Data Transformation -> MVP currently in development; expected to be complete in October (2019).
Revenue Opportunity • Revenue Model follows our two product offerings: • Municipalities: Pay for initial implementation of our algorithm. Annual subscription fee for maintenance. The first couple of cities will get a significantly reduced implementation. • Automakers: Two possible options; One, yearly subscription per new vehicle. Second, a bidding of automakers per city to have the fastest route supplied to only there vehicles. ;)
The Deal / Use of Funds • $1.2 million convertible note to get through the next 18 months • Use of Funds: • Hiring (Sales, Experienced Traffic Engineer, python developer) • Legal Needs – Patent filing, government contracting. • Capital / Rent - (Computer for hires, cloud computing for algorithm, WeWork membership.) • Marketing.