A city-wide trial in Melbourne shows how road use charges can reduce traffic jams

Traffic in Melbourne. Image: Getty.

Road congestion in large Australian cities is estimated to cost more than A$16bn a year. Economists have long argued the best way to improve traffic flow is to charge drivers for their contribution to road congestion. We have now analysed data collected from 1,400 drivers across Melbourne to see whether road user charging can change their behaviour in ways that ease congestion.

And the answer is yes.

Because the obstacle to adopting this approach has been concern about its fairness, we also looked at driver incomes. Would congestion-based charges price the poor off the road for the benefit of those who can pay? We calculated how different systems of road use charges affected households on different incomes, and how driving patterns changed under different prices.

The evidence does not support other common policy responses to traffic congestion. Building new roads does little to relieve congestion. Placing tolls on roads can push traffic onto others.

However, even small reductions in congestion can produce large benefits. On congested roads, reducing traffic by 5 per cent can increase traffic speeds by up to 50 per cent.

The question is: what would the optimal charges be? Drivers often plan their travel ahead of time, so Uber-like surge pricing is not necessarily the best way to go. Could simpler fixed charges, based perhaps on time of day or location, be effective?

In 2015-16, Transurban Group implemented the Melbourne Road Usage Study (MRUS) to answer these questions. More than 1,400 drivers across greater Melbourne installed GPS devices in their vehicles for eight to ten months. After a period to establish baseline use, a randomly selected subset faced a series of road use charges via a system of virtual accounts. Every month participants accumulated real money from reduced charges as a result of their decisions about driving.

Well-targeted charges ease congestion

The Melbourne Road Usage Study tested three simple charges:

  • a flat distance-based charge of 10 cents per kilometre
  • a time-of-day charge of 15 cents per kilometre at peak times and 8 cents at other times
  • a distance-plus-cordon charge where drivers were charged 8 cents per kilometre at all times plus A$8 if they entered the inner city.

Our working paper, Can Road Charges Alleviate Congestion?, evaluates the raw data.

Charges that vary by time of day were most effective at reducing driving at congested times. Drivers subjected to a higher cost of driving in the weekday peak hours of 7am to 9am and 3pm to 6pm reduced travel by 10 per cent during these periods.

While a simple 10 cent charge on distance travelled did reduce driving, this was mainly outside the congested inner city and at off-peak times – mostly in the middle of the day and on weekday evenings. Most freeway congestion occurs around morning and late afternoon commutes.

London and Singapore have charges to enter the congested city centre. Further research is needed to assess the effects on inner-city traffic in Australian cities.

The evidence points towards most drivers who enter the central business district (CBD) being willing to pay higher weekday charges. But few drivers entered the cordon zone during the study. Less than 5 per cent of the drivers made over half of the trips into the area.

Access to reliable public transport matters

Public transit has a key role in getting cars off the road. Our data showed households located far from the CBD and from public transport drive more. Living 500m closer to a tram or train station has the same effect on kilometres driven each day as living 5km closer to the CBD.

Households within a 10-minute walk from public transport drive least. The largest reductions in driving from time-of-day and cordon charges come from households living 10 to 20 minutes’ walk away.

Road use charges could be fairer

Congestion-based charges can be a more progressive way to fund roads than the existing system of registration fees and fuel taxes.

The fuel excise makes up almost half of the average annual road bill in Australia. It’s essentially a distance-based fee, but more fuel-efficient vehicles pay less per kilometre travelled. Hybrid vehicle drivers, for example, contribute much less to fuel tax revenue.

Yet, although hybrids contribute less to air pollution, they increase congestion just as much as their petrol-guzzling counterparts. And congestion is a much greater shared economic cost than vehicle air pollution.

Annual vehicle registration fees make up most of the remaining road bill. These provide no incentive to reduce congestion.

Fuel taxes and registration fees put a disproportionate burden on low-income households in the outer suburbs. Our research shows these households would be better off if roads were funded more by congestion charges.


Field experiments help get the settings right

So what is the optimal congestion charge? Economic theory (Pigou 1920) tells us to price at the cost that each extra user imposes on the system.

With road use, though, the calculation is difficult. To fix rates in advance, we would need to know exactly how much longer everyone’s trip is when each extra driver joins each system. And we’d need to cost that slowdown for each individual on the road at that time (i.e. value their time and, potentially, the cost to them of being late). New research has been using clever experimental designs to identify these values.

That said, maybe it is not too important to get the price just right. For electricity, we are starting to see that households respond to there being a price, not its specific level.

Before widespread road use charges are implemented, we would like to see more field experiments like the MRUS to find answers to other questions. Would it be better to combine a time-of-day charge with targeted locations? How effective would it be to charge more for using highly congested arterial roads at peak times? Would this simply push congestion onto nearby local roads? How large a gap between peak and off-peak prices is needed to produce a strong response?

Another interesting option is the i10 model outside Los Angeles. Two lanes are for traffic willing to pay more to get to their destination faster.

Dynamic pricing ensures traffic in these lanes flows freely – if too many use these lanes and traffic slows, the price increases. Drivers can decide every few kilometres if they want to pay more to stay in the express lanes. Those who must get somewhere on time are able to, and the fee revenue can be used to reduce road costs for others.

The Melbourne Road Usage Study (MRUS) shows field experiments can help us design better road use charges. By all appearances, households took it seriously and were positive about their involvement.

The ConversationThe MRUS provides evidence that well-designed road use charges could help reduce congestion by encouraging people to drive at different times, take other routes or use other transport. This could lead to better use of existing infrastructure, thereby reducing costs, while generating revenue for infrastructure investments. Under such a system, drivers who contribute little to congestion could see substantial gains.

Leslie A. Martin, Lecturer (Assistant Professor) in economics and Sam Thornton, Master of Economics candidate, University of Melbourne.

This article was originally published on The Conversation. Read the original article.

 
 
 
 

Urgently needed: Timely, more detailed standardized data on US evictions

Graffiti asking for rent forgiveness is seen on a wall on La Brea Ave amid the Covid-19 pandemic in Los Angeles, California. (Valerie Macon/AFP via Getty Images)

Last week the Eviction Lab, a team of eviction and housing policy researchers at Princeton University, released a new dashboard that provides timely, city-level US eviction data for use in monitoring eviction spikes and other trends as Covid restrictions ease. 

In 2018, Eviction Lab released the first national database of evictions in the US. The nationwide data are granular, going down to the level of a few city blocks in some places, but lagged by several years, so their use is more geared toward understanding the scope of the problem across the US, rather than making timely decisions to help city residents now. 

Eviction Lab’s new Eviction Tracking System, however, provides weekly updates on evictions by city and compares them to baseline data from past years. The researchers hope that the timeliness of this new data will allow for quicker action in the event that the US begins to see a wave of evictions once Covid eviction moratoriums are phased out.

But, due to a lack of standardization in eviction filings across the US, the Eviction Tracking System is currently available for only 11 cities, leaving many more places facing a high risk of eviction spikes out of the loop.

Each city included in the Eviction Tracking System shows rolling weekly and monthly eviction filing counts. A percent change is calculated by comparing current eviction filings to baseline eviction filings for a quick look at whether a city might be experiencing an uptick.

Timely US eviction data for a handful of cities is now available from the Eviction Lab. (Courtesy Eviction Lab)

The tracking system also provides a more detailed report on each city’s Covid eviction moratorium efforts and more granular geographic and demographic information on the city’s evictions.

Click to the above image to see a city-level eviction map, in this case for Pittsburgh. (Courtesy Eviction Lab)

As part of their Covid Resource, the Eviction Lab together with Columbia Law School professor Emily Benfer also compiled a scorecard for each US state that ranks Covid-related tenant protection measures. A total of 15 of the 50 US states plus Washington DC received a score of zero because those states provided little if any protections.

CityMetric talked with Peter Hepburn, an assistant professor at Rutgers who just finished a two-year postdoc at the Eviction Lab, and Jeff Reichman, principal at the data science research firm January Advisors, about the struggles involved in collecting and analysing eviction data across the US.

Perhaps the most notable hurdle both researchers addressed is that there’s no standardized reporting of evictions across jurisdictions. Most evictions are reported to county-level governments, however what “reporting” means differs among and even within each county. 

In Texas, evictions go through the Justice of the Peace Courts. In Virginia they’re processed by General District Courts. Judges in Milwaukee are sealing more eviction case documents that come through their courtroom. In Austin, Pittsburgh and Richmond, eviction addresses aren’t available online but ZIP codes are. In Denver you have to pay about $7 to access a single eviction filing. In Alabama*, it’s $10 per eviction filing. 

Once the filings are acquired, the next barrier is normalizing them. While some jurisdictions share reporting systems, many have different fields and formats. Some are digital, but many are images of text or handwritten documents that require optical character recognition programs and natural language processors in order to translate them into data. That, or the filings would have to be processed by hand. 

“There's not enough interns in the world to do that work,” says Hepburn.


Aggregating data from all of these sources and normalizing them requires knowledge of the nuances in each jurisdiction. “It would be nice if, for every region, we were looking for the exact same things,” says Reichman. “Instead, depending on the vendor that they use, and depending on how the data is made available, it's a puzzle for each one.”

In December of 2019, US Senators Michael Bennet of Colorado and Rob Portman of Ohio introduced a bill that would set up state and local grants aimed at reducing low-income evictions. Included in the bill is a measure to enhance data collection. Hepburn is hopeful that the bill could one day mean an easier job for those trying to analyse eviction data.

That said, Hepburn and Reichman caution against the public release of granular eviction data. 

“In a lot of cases, what this gets used for is for tenant screening services,” says Hepburn. “There are companies that go and collect these data and make them available to landlords to try to check and see if their potential tenants have been previously evicted, or even just filed against for eviction, without any sort of judgement.”

According to research by Eviction Lab principal Matthew Desmond and Tracey Shollenberger, who is now vice president of science at Harvard’s Center for Policing Equity, residents who have been evicted or even just filed against for eviction often have a much harder time finding equal-quality housing in the future. That coupled with evidence that evictions affect minority populations at disproportionate rates can lead to widening racial and economic gaps in neighborhoods.

While opening up raw data on evictions to the public would not be the best option, making timely, granular data available to researchers and government officials can improve the system’s ability to respond to potential eviction crises.

Data on current and historical evictions can help city officials spot trends in who is getting evicted and who is doing the evicting. It can help inform new housing policy and reform old housing policies that may put more vulnerable citizens at undue risk.

Hepburn says that the Eviction Lab is currently working, in part with the ACLU, on research that shows the extent to which Black renters are disproportionately affected by the eviction crisis.

More broadly, says Hepburn, better data can help provide some oversight for a system which is largely unregulated.

“It's the Wild West, right? There's no right to representation. Defendants have no right to counsel. They're on their own here,” says Hepburn. “I mean, this is people losing their homes, and they're being processed in bulk very quickly by the system that has very little oversight, and that we know very little about.”

A 2018 report by the Philadelphia Mayor’s Taskforce on Eviction Prevention and Response found that of Philadelphia’s 22,500 eviction cases in 2016, tenants had legal representation in only 9% of them.

Included in Hepburn’s eviction data wishlist is an additional ask, something that is rarely included in any of the filings that the Eviction Lab and January Advisors have been poring over for years. He wants to know the relationship between money owed and monthly rent.

“At the individual level, if you were found to owe $1,500, was that on an apartment that's $1,500 a month? Or was it an apartment that's $500 a month? Because that makes a big difference in the story you're telling about the nature of the crisis, right? If you're letting somebody get three months behind that's different than evicting them immediately once they fall behind,” Hepburn says.

Now that the Eviction Tracking System has been out for a week, Hepburn says one of the next steps is to start reaching out to state and local governments to see if they can garner interest in the project. While he’s not ready to name any names just yet, he says that they’re already involved in talks with some interested parties.

*Correction: This story initially misidentified a jurisdiction that charges $10 to access an eviction filing. It is the state of Alabama, not the city of Atlanta. Also, at the time of publication, Peter Hepburn was an assistant professor at Rutgers, not an associate professor.

Alexandra Kanik is a data reporter at CityMetric.