As a commitment to bolstering Michigan’s startup economy, MichAuto has created the MichAuto Innovator Exchange, an immediate access point for startup companies to connect with well-established firms and other consumers of innovation. Learn more about participating company, LiveRoad Analytics, and its Co-Founder and Chief Ecosystem Officer Harriet Chen-Pyle below.
Meet Harriet Chen-Pyle, Chief Ecosystem Officer and Co-founder of LiveRoad Analytics
Harriet is Chief Ecosystem Officer and Co-founder at LiveRoad Analytics. She oversees partnerships and industry dynamics and how the company shapes its presence. This encompasses the exploration of new market opportunities, identifying current trends, key issues, and business strategy. She also directs the organization to maintain a competitive edge through long-term relationship development between customers, the company, and market verticals.
Harriet brings industry provenance in the Intelligent Transportation Systems (ITS) industry with experience spanning across automotive for Advanced Traveler Information Systems (ATIS), and Commercial Vehicle Operations (CVO) within the private and public sectors. This includes TomTom, Telenav, ComTech, and Teletrac Navman in the private sector, and The Transit Standards Consortium (TSC), Michigan Department of Transportation (MDOT), ITS AMERICA, and ITS Michigan in the public sector, to name a few.
She is a founding member of the Teleoperation Consortium, a member of CVTA (Connected Vehicle Trade Association), and a charter member of ITS AMERICA. Most recently, she has been recognized as a top female founder in Michigan by Purpose Jobs, along with LiveRoad’s accolades of being last year’s 15th GAMIC finalist and back-to-back inclusion in Renaissance Venture Capital’s Startup Hotlist for Spring and Fall 2023.
Harriet has a B.S. in Communications from Eastern Michigan University and a certificate of completion from Nan Hai (U.S.A.) Co., Inc. for intensive Mandarin Chinese language program.
What Harriet Has to Say About Her Company
How long have you been in business and how many employees do you currently have?
LiveRoad has been in business for 4.5 years with a team of 8 people.
Describe your ideal client and the problem you are trying to solve for them?
LiveRoad’s ideal clients include CVO (Commercial Vehicle Operations) comprising the three core segments of the trucking industry: TL (Truckload), LTL (Less-Than-Load), Package Express, and Automotive OEMs. Improved weather forecasting is critical under climate change. Weather events are more volatile, costing an estimated US$283M per day, and causing an average of 40 fatalities per day globally according to the World Meteorological Organization. LiveRoad Analytics is a meteorological technology company utilizing swarm intelligence from connected fleet and proprietary sensor data for improved safety and operational efficiency within the transportation and new mobility ecosystem.
For CVO, one out of four large truck accidents occur during bad weather. If there’s a fatality, the cost per accident is over $7 million. Because of this, fleet operators often decide to shut down their fleet during bad weather. However, an unexpected shutdown costs their company over $700 per day per truck. For U.S. fleets, this is over $8 billion a year. Thus, for CVO, when it comes to inclement weather, they face a costly dilemma: Either they shut down area-wide regions of their fleet, or they keep up and running while putting their drivers at risk. LiveRoad resolves this quandary through timely targeted notifications to drivers and dispatchers by giving them visibility into the actual conditions on the roads. With LiveRoad, they can see which roads have iced over, which roads are just wet, and which roads are about to become risky. With LiveRoad Analytics, fleet operators avoid unnecessary, costly shutdowns while keeping their drivers safe.
Automotive OEMs are undergoing tremendous changes and seeking to maximize their connected vehicle data through their digital transformation roadmaps for innovation and sustainability, as well as seeking innovative ways to monetize their connected vehicle data.
For innovation and sustainability, improved weather forecasting will have a positive impact on sustainability goals through reduced carbon emissions, inventory management, more resilient supply chain, and optimizing energy consumption. OEMs collect real-time data that is underutilized in mitigating weather risk, particularly between vehicles. Connected vehicle data capture a number of valuable weather variables and provide impact data points such as ABS or wiper status. LiveRoad delivers a robust technology solution leveraging the power of sensor data for improved weather forecasts, predictive data modeling, weather analytics, and road surface prediction. OEMs already consume weather data, but do not have access to data at this resolution and verification to be able to support proactive ADAS. OEM vehicle data and LiveRoad’s solution provides an unmatched level of real-time ground truth data available for integration into meteorological modeling. LiveRoad has developed a platform to combine streaming mobile sensor data with road and atmospheric modeling for an unparalleled level of both spatial and temporal resolution to enhance New Energy Vehicles, the Customer Experience, and Autonomy. For the Automotive OEM customer, this provides:
- Smarter vehicles – Improved safety and customer satisfaction via HMI & ADAS/AV
- Improved efficiency in mobility or fleet solutions
- Improved data for internal processes – EV range, parts failure analysis, supply chain
On data monetization, OEMs have interest in LiveRoad’s technology because they collect raw data from hundreds of millions of connected vehicles and they see LiveRoad as a way to convert their raw data into valuable information they can sell, capturing the interest of the $13 billion US Weather Industry. This derivative forecast product provides OEMs with an industry-leading weather product, opening up new revenue streams across major industries affected by weather.
Where do you see your company in the next 5 years?
LiveRoad foresees itself as a leader in weather AI using swarm intelligence, capable of accurate forecasting for metro microclimates globally, and able to support customer solutions across any industry impacted by weather or climate change. Socially, all road users benefit from improved safety.
Why did you choose to locate your firm in Michigan?
Michigan is the epicenter for all things automotive. Michigan also experiences a lot of microclimate conditions during all four seasons. Michigan offers a diverse and wealth of talent, pilot testbeds, and smartzone entities that cohesively support Michigan-based tech startups. Mobility is one of the core focus areas for Michigan being home to the automotive industry. LiveRoad Analytics’ solution can both complement and be the recipient of this dynamic supportive ecosystem that the state offers on multiple fronts.
What is your firm’s greatest competitive advantage?
Swarm Intelligence for improved microclimate forecasting and climate resilience. LiveRoad technology goes beyond the capabilities of meteorology alone for improved visibility into risk along the road network and at facility locations. LiveRoad has built a proprietary road weather model that analyzes the road network at unmatched levels of resolution in the industry. LiveRoad fuses a range of datasets including vehicle telematics data, proprietary road sensor data, and high-resolution meteorological modeling. The integration of this data creates a valuable feedback loop that dynamically verifies and updates the forecast. ML and AI are used to continuously improve the forecast models. This dramatically improves inclement weather forecasting.
LiveRoad’s patent pending technology is a proprietary road surface model that combines edge computing with advanced meteorological weather models and multiple data sources to provide risk analysis as a Safety System and Method for Motor Vehicles. This technology helps determine road surface conditions such as wet, mixed, and icing conditions, determines the average impact to vehicles on a specified route, and predicts the road conditions’ impact on a particular vehicle based on a deviation from the average – not necessarily an average of all vehicles, but a representative subset or sample for the purpose of more precisely determining whether the driven vehicle will be able to safely navigate the planned travel path.