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Cognitive Models for Equitable EV Charging Decisions

A recent study published in Transportation Research Part D: Transport and Environment by Xinwu Qian, an Assistant Professor of Civil and Environmental Engineering at Rice University, is rethinking the design and placement of charging stations. The focus is not only on accessibility but also on ensuring they align with people’s daily routines and activities.

Electric car plugged in with charging station to recharge battery with electricity by EV charger cable in eco green park and greenery foliage.

Image Credit: Owlie Productions/Shutterstock.com

As electric vehicles (EVs) become more popular in the fight against climate change, the debate over public charging infrastructure is growing more complex.

Charging an electric vehicle is not just about plugging it in and waiting; it takes 30 minutes to an hour, even with the fastest charger. Therefore, it is an activity layered with social, economic, and practical implications. While we have made great strides in EV adoption, the invisible barriers to public charging access remain a significant challenge.

Xinwu Qian, Assistant Professor, Rice University

Qian’s work highlights the hidden inequities in the current public charging infrastructure. His research shows that low-income households, which are less likely to have home charging access or afford it, often find public charging stations near their homes.

However, these stations are usually inconvenient, as they are far from the households' regular activities. In contrast, while public charging stations may be farther from wealthier suburban areas, they tend to fit better with people’s daily routines. This creates an opportunity gap for low-income communities, where public charging access exists in theory but is less practical in reality.

Disparities arising from distance measures are only part of the equation; a deeper issue emerges when we consider the actual time people can spend at different locations. For lower-income households, the issue is often about time. If you are juggling multiple jobs or family obligations, spending 30 minutes to an hour at a charging station might not be feasible, especially if it is located far from your daily activities.

Xinwu Qian, Assistant Professor, Rice University

In a 2024 study led by Qian, data from over 28,000 public charging stations and 5.5 million points of interest across 20 U.S. cities were analyzed. The findings were striking: income, rather than proximity, was the key factor in determining who benefits most from public EV infrastructure.

Wealthier individuals had the flexibility to charge their cars while spending time at locations they frequently visited, where charging stations were more likely to be found. In contrast, lower-income communities faced challenges in incorporating public charging into their routines due to shorter dwell times and less alignment with their daily activities.

Qian said, “Charging decisions are deeply personal. People rely on intuition and habit when choosing a station, often without realizing the broader social and economic implications of their choices.”

Qian draws a troubling comparison between the interstate highway system built decades ago and today’s charging infrastructure.

The interstate highways were designed to connect cities, but there are many studies and evidence suggesting that they also ended up dividing communities and depriving certain neighborhoods of opportunities. We are seeing a similar pattern emerge with EV charging stations, where deployment strategies favor certain lifestyles and leave others behind. This builds upon the issues created by the interstate highways and could also exacerbate them.

Xinwu Qian, Assistant Professor, Rice University

His research also highlights a concerning feedback loop: companies that install charging stations often target higher-income clients, perpetuating the cycle of inequality.

Qian said, “It is a sad reality. If we do not address these systemic issues now, we risk deepening the divide between those who can afford EVs and those who cannot.”

The National Science Foundation recently awarded a grant to Qian’s research team, which is developing cognitive models to explore how people decide where to charge their cars. These models aim to break the “echo chamber” of intuitive decision-making by offering users strategic recommendations that align with long-term societal benefits.

Qian’s research also offers practical recommendations for businesses and policymakers. One key suggestion is to reconsider how charging station subsidies are distributed.

Qian advocates for targeted incentives that focus on underserved communities, encouraging businesses in these areas to install charging infrastructure, rather than providing uniform funding.

Qian said, “We cannot just rely on market forces to fix this problem. Public and private sectors must work together to create an equitable charging network that benefits everyone, not just those who can afford it.”

Qian also emphasized how crucial it is to combine community resilience tactics with charging infrastructure.

Qian said, “Resilience is not just about preparing for disasters. It is about addressing chronic challenges, like ensuring that everyone, regardless of income, can participate in the transition to sustainable energy.”

The United States aims to have 500,000 EV charging stations by 2030, and Qian’s research provides a crucial roadmap for equitable deployment. By combining insights from behavioral psychology, sociology, and engineering, he is working to ensure that the benefits of EV adoption are shared fairly across all communities.

Electric vehicles are more than just a way to save money or reduce emissions; they are an opportunity to rethink how we design our cities and serve our communities. But to seize that opportunity, we need to address the inequities in our infrastructure now,” Qian said.

Journal Reference:

Gazmeh, H., (2024) Understanding the opportunity-centric accessibility for public charging infrastructure. Transportation Research Part D Transport and Environment. doi.org/10.1016/j.trd.2024.104222.

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