EV Adoption Grows, But Infrastructure And Consumer Confidence Lag
The automotive world continues its steady march toward electrification, but the pace is slower than many projected. Analysts still forecast that EVs could make up half of all new car sales by the end of the decade, driven by global competition and improving battery technology. But while sales rose 11% year over year in Q1 2025, the growth rate is beginning to moderate.
Contributing factors include consumer concerns over range, charging access and higher upfront costs—all of which point to a systemic issue: the infrastructure meant to support EV adoption isn't keeping pace.
Even as more EV chargers are added nationwide, the current approach to infrastructure development risks falling short. The challenge isn't about how many chargers we build. It's about building infrastructure that fits real-world patterns of movement—how people commute, where goods travel and when vehicles pause.
Without more targeted planning, we risk creating a charging network that is underused, inefficient or inaccessible to those who need it most.
At A Crossroads For Electrification
EV sales are projected to continue rising over the next decade, but today's electrification efforts remain at a critical crossroads. While adoption increases, charging availability remains uneven. Some areas have a surplus of chargers with limited use, while others—especially rural regions, underserved communities and high-demand freight corridors—remain charging deserts.
If left unaddressed, these imbalances will create friction in the user experience, slow adoption and perpetuate inequities in transportation access.
The disconnect stems from a traditional planning mindset—one that emphasizes population density, available land or political boundaries. While those factors matter, they overlook a central reality: mobility is behavioral.
Mobility Data Enables Smarter Infrastructure Decisions
To optimize the EV ecosystem, we need to shift from broad static indicators to dynamic, actionable insights. This is where real-world mobility data becomes essential. By analyzing how, when and where people and goods actually travel, planners can make more effective, adaptive decisions.
The following examples illustrate how EV infrastructure planning can align with real-world mobility behavior:
• Serving drivers at retail centers with long dwell times by colocating chargers with shopping and dining destinations.
• Supporting fleet needs at logistics hubs and truck stops where vehicles return on predictable schedules.
• Avoiding unreliable charging at routes with high congestion or frequent incidents that limit accessibility.
These insights empower city planners, utilities and transportation agencies to invest where demand exists—or will soon emerge—based on actual usage rather than outdated assumptions.
EV Usage Patterns Matter As Much As Location
Strategic charger placement is foundational, but understanding how different types of EVs are used is equally important. Travel behavior affects energy consumption, charging frequency and grid load.
Here are some examples of how usage patterns shape charging needs:
• Enabling consistent daily charging at homes and workplaces to support commuter routines.
• Aligning depot and overnight charging with the operational models of fleet vehicles like delivery vans and ride-share cars.
• Matching charger speed and type to driving conditions like stop-and-go traffic or long-distance highway travel.
Mobility data provides the historical and real-time context needed to anticipate these variations. The result is an infrastructure network that's not just reactive, but resilient—designed to accommodate diverse user needs and reduce grid strain during peak demand.
Technology Unlocks Smarter EV Planning
As EV adoption grows, transportation leaders need more than estimations to guide infrastructure decisions. Technologies that harness real mobility data can show exactly where charging capacity is needed, and why.
By analyzing traffic flows, parking durations, route patterns and congestion points, data-driven planning can improve EV charging infrastructure in these key ways:
• Anticipate charging demand based on actual travel behavior—not just residential distribution.
• Align charger placement with traffic volume, vehicle dwell times and congestion levels to ensure chargers are actively used.
• Project future growth by layering historical trends with real-time conditions.
• Improve network reliability by steering investment away from unreliable or disruption-prone areas, such as congested corridors or roads with frequent closures.
• Serve commercial and fleet needs more effectively by analyzing repeat routes and rest periods.
This approach makes infrastructure planning more strategic, inclusive and durable—grounded in how transportation functions on the streets, not just on paper.
The Road Ahead: Data-Informed, Equity-Centered Growth
As EVs edge into the mainstream, business and policy leaders must focus on the questions that matter most:
• Are infrastructure investments aligned with real transportation patterns?
• Are charging networks designed to include underserved regions and essential commercial routes?
• Are we anticipating where demand is going—not just reacting to where it is today?
The answers lie in targeted, behavioral data that reveals real-world movement patterns. The future of transportation is electric—but only if the infrastructure evolves to support it. That means abandoning legacy planning frameworks in favor of smarter, adaptive and equity-driven strategies.
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