| | APRIL 20268IN MY OPINIONThe Green Revolution on WheelsEver wondered how the delivery truck that brings your packages, the bus you take to work or the refuse truck that collects your waste could become key players in our journey to make the world more sustainable? The intersection of artificial intelligence, data analytics, and commercial transportation is creating unprecedented opportunities to reimagine sustainability in an industry traditionally known for its carbon footprint. According to the U.S. Environmental Protection Agency, despite representing less than 8 percent of total vehicles, trucks and buses are responsible for over 35 percent of direct CO2 emissions from road transport, hence the stakes couldn’t be higher or the opportunities more interesting.Intelligent Route Optimization: Beyond Point A to Point BThe journey toward sustainable commercial transportation starts with smarter routing. AI algorithms now ingest millions of real-time data points to optimize fleet operations beyond human capability. More than just data, this space needs actionable insights and that’s where analytics and AI shine.For refuse trucks, AI-powered route optimization can cut fuel consumption by up to 25percent by analyzing collection patterns, traffic and waste volume forecasts. The U.S. Department of Energy reports around 136,000 refuse vehicles operate daily in the U.S., each averaging 800–1,000 stops and a fuel consumption of 2.8 miles per gallon. This adds up to over 1.2 billion gallons of fuel used annually while discounting real-time variables like traffic, weather, and ad hoc requests create inefficiencies, fuel waste and missed pickups. According to Eric Hansen, CIO of Waste Connections, intelligent routing can reduce planning and admin time by 25 to 75percent and CO₂ emissions by up to 25percent. These savings matter, given the industry’s fuel spend. A waste management company spent more than $500 million on fuel in 2023 or ~3.6percent of revenue. Extrapolating that ratio across the $140 billion industry suggests total fuel costs near $5 billion.For delivery vehicles, machine learning now can factor in weather, real-time traffic, historical data and consumer behavior to find not just the shortest but the most energy-DRIVING TOMORROW WITH AI AND DATA ANALYTICS IN SUSTAINABLE TRANSPORTBy Brendan Chan, Sr. Chief Engineer - Autonomy and Active Safety, Oshkosh CorporationAI ALGORITHMS ANALYZE REAL-TIME AND HISTORICAL DATA FROM VEHICLE SENSORS AND DIAGNOSTIC SYSTEMS TO PREDICT POTENTIAL EQUIPMENT FAILURES BEFORE THEY OCCUR.Brendan Chan, is a collaborative technology executive and industry thought leader with 15+ years of experience in automation, AI, and intelligent product development. Known for cross-functional leadership and innovation, he holds multiple patents, industry awards, and been invited to speak at industry events like NVIDIA GTC and SAE COMVEC.Brendan Chan
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