Distance-Based Road Pricing: Making Personal Car Taxes More Fair

Evgeny Klochikhin
Predict
Published in
5 min readOct 24, 2019

They say that death and taxes are the only two inevitable things in life, and that’s certainly true for drivers. Owning a personal vehicle costs vary across the United States, with some counties imposing a personal property tax, states deploying tolls, and cities thinking about launching congestion pricing schemes.

Road-usage pricing has been long exercised by various governments but a fairer taxation system needs to be implemented now.

The basic concept seems reasonable enough. Maintaining the roads requires public expenditures. More cars also contribute to overall congestion and environmental effects, so it makes sense to incentivize limiting road usage.

It seems fair: you use the road and you pay the fees. However, the way we tax road usage currently is not really that fair. It’s time we move to a better system.

Why we don’t tax road usage fairly

Currently, we tax road usage entirely through tolls and model/year of the vehicle. Yet this does not accurately capture the whole picture of road utilization nor differentiates enough on how different people use their personal vehicles.

Take the example of two drivers, Bob and Joe. Both live in the same metropolitan area. There is a toll that charges drivers going in and out of the main city.

Bob lives just outside of the city. He commutes to work in his car several days a week, paying the toll to cross the bridge into the city. However, he works right by the bridge, so he doesn’t actually drive around much in the city itself. Aside from his commute, Bob does not drive around the roads much at all.

Joe lives and works in the city. So, he rarely has to pay the toll, even though he drives around quite frequently. The city is large, so he ends up driving more miles than Bob on a weekly basis.

With a standard toll system in place, Bob is forced to pay a far greater tax than Joe — even though Bob uses the roads less often. That’s unfair and runs against the purpose of implementing a toll in the first place.

How to implement distance-based road pricing

So, how could we implement a fairer system for taxing road usage? It’s a little complicated, but well within the capabilities of our current technology.

To tax road usage fairly, we would need to track exactly how frequently individual drivers are using the roads. We would want to know which roads every driver used so we could set rates appropriately.

To implement such a system, we would need a tracking device in every vehicle. It would also be helpful to have devices to collect GPS and GNSS data on all of the roads.

About ten years ago, the ruling party of the Netherlands actually proposed such a system. However, it proved to be politically unpopular and hard to implement on the scale of the entire country at once. When another party won the next election, the proposal fell by the wayside.

The Netherlands’ proposal is a utopian vision for distance-based road pricing. There are other alternatives that are also worth considering and can ensure more gradual transition.

A good example to consider is usage-based insurance: the more you drive the more risk you pose for insurance companies and hence pay higher premium. Also, the better you drive the less risk — hence, smaller premium. Usage-based insurance is almost entirely voluntary because it helps better drivers save money when they sign up for the system. In return, insurance companies have better data about how people drive that helps them implement more efficient risk models.

The Parkofon approach and the future of road pricing

The Dutch proposal proved to be politically and socially difficult. It also required a great deal of investment in infrastructure. Every road would need to be equipped with new sensors.

Fortunately, there are ways to implement distance-based road pricing without fully adapting that model. The simplest way to achieve this is to place an accurate and secure GPS device in the vehicle itself.

If we were to embed a geopositioning system within the vehicle itself, it would be difficult to tamper with. We could equip all new vehicles to include such a system, like the Russian government mandated ERA-GLONASS to be installed on all cars. And state and municipal governments would not have to invest in a lot of new infrastructure. Cameras to capture license plate numbers could be sufficient as a supplement to data collected with the in-vehicle device. Meanwhile, drivers will get much more convenience knowing where the next available parking spot is, paying automatically at gas stations and restaurants, and having real-time traffic information.

The devices would track how much every vehicle used the roads and which roads were utilized. Then, every car owner would receive a tax based on standardized rates. This is fairer to drivers and can also offer greater convenience. No longer would people have to take inefficient routes to their destinations just to avoid paying a toll.

As an added plus, this solution is infrastructure-light. An accurate and secure in-vehicle navigation system, such as Parkofon’s technology, could do the job just fine.

License plate recognition cameras for enforcement are perhaps the only infrastructure element that is required to enable satellite-based road-pricing schemes.

Naturally, there would be a transition period. Not everyone would drive a car with such navigation abilities right away. But as more and more people buy newer cars, it would become feasible to implement this technology as a standardized taxation system. It’s similar to changes that are already occurring with regards to toll payment. For example, San Francisco is phasing out cash payments for tolls. In future years, people in the Bay area will be required to use the electronic FasTrak system to pay for tolls.

There’s a need for a fairer taxation system, and we have the technology to make it happen. This is where transportation is headed.

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Evgeny Klochikhin
Predict

Evgeny Klochikhin, PhD is the CEO of Parkofon, a smart mobility company building a fully connected #MaaS platform. Innovation scholar, data scientist, engineer.