Driving: We’re Doing It Wrong


(Credit: Artesia Wells / Shutterstock)

If you use a car to get around, every time you get behind the wheel you’re confronted with a choice: how will you navigate to your destination? Whether it’s a trip you take every day, such as from home to work, or to someplace you haven’t been before, you need to decide on a route.

Transportation research has traditionally assumed that drivers are very rational and choose the optimal route that minimizes travel time. Traffic prediction models are based on this seemingly reasonable assumption. Planners use these models in their efforts to keep traffic flowing freely – when they evaluate a change to a road network, for instance, or the impact of a new carpool lane. In order for traffic models to be reliable, they must do a good job reproducing user behavior. But there’s little empirical support for the assumption at their core – that drivers will pick the optimal route.

For that reason, we decided to investigate how people make these choices in their real lives. Understanding how drivers build a route to reach their destination will help us gain insights into human movement behavior. Better knowledge of individual routing can help improve urban infrastructure and GPS directions systems – not just for one driver, but for everyone. Beating congestion is a big goal: one estimate put the cost of traffic in 2014 at US$160 billion in the U.S., with 42 extra hours of travel time and $960 worth of extra fuel for every commuter.

How Do People Really Go?

Using GPS data collected for several months for hundreds of drivers in four European cities, we studied individuals’ routing behavior, looking for interesting patterns in their choices.

We discovered that people use only a few routes when moving between their relevant places, even when those trips are repeated again and again over extended periods. Most people have a single favorite route for trips they perform routinely and a few alternatives routes they take less frequently to the same destinations.

So did people in fact usually choose the optimal route?

In short, no. It turned out roughly half of the favorite routes are not the optimal routes suggested by navigation devices, such as those offered by some popular mapping apps for smartphones. If we also consider drivers’ alternative choices, even fewer routes are optimal – only a third overall minimize travel time.

Our data provide empirical proof that drivers are not taking the optimal route, directly contradicting the shortest travel-time assumption.

Why Would Drivers Take a Nonoptimal Route?

What’s behind this result? A unique answer that is valid for every driver won’t be easy to find.

Prior small-scale studies found that many factors, some seemingly minor, might influence route preference. For example, people tend to choose routes going south rather than routes of equal lengths that go north. People favor routes that are straight at the beginning, instead of shorter ones that aren’t straight. Landmarks also influence route choice, by attracting more trips than travel-time minimization would expect. A novel app for iPhones builds on that very concept and allows people to find the most “interesting” route between two points.

People might not be able to determine which route is optimal, among all possible choices, because of limited information and limited ability to process big amounts of information. Or, even if they can, people might deliberately make different choices, according to personal preference. Many factors can influence preference, including fuel consumption, route reliability, simplicity and pleasure.

Drivers’ apparent flexibility on route choices may provide an opportunity to alleviate overall congestion. For instance, smartphone apps could offer points and vouchers to drivers who are willing to take longer routes that avoid congested areas. Navigation app Waze has already changed drivers’ habits in some cities, so it’s not so far-fetched to imagine a gamification system that reduces congestion.

How Far From the Best Route Are We?

For our next study, rather than trying to understand what drives individual route choices, we aimed to quantify how far those choices are from optimal.

A sample of the transformed trajectories reveals the shape of human routes. Regardless of the real start and destination points, every transformed trajectory begins at the circle on the left and ends at the circle on the right. (Credit: A. Lima et al. J. R. Soc. Int. DOI: 10.1098/rsif.2016.0021)

It’s hard to directly compare all the different trips undertaken in a city, because they involve many locations and are different in length. To make this task easier, we transformed trajectories so that they all look alike, regardless of their actual source, destination and length. We rotated, translated and scaled each route so that all trajectories would start and finish at the same two points in a new reference system. After this transformation, all the routes look as if they spanned the same two points; they all look similar in length, but their shape is preserved. What we found by plotting a sample of the transformed routes was the intrinsic variability in human routes.

Intriguingly, our abstraction of all the trips sort of looks like a magnet’s force lines, with the routes’ origins and destinations in place of the magnet’s north and south poles. By analyzing a density plot of the transformed trajectories, we found the vast majority are fully contained within an ellipse that has the same shape independent of the scale, with the start and endpoints as foci. This ellipse effectively makes up the boundary of human routes.

The density plot shows how likely you are to be at any position between the start (on the left) and the destination (on the right). Colors indicate, in logarithmic scale, from dark to bright, the spots more likely to be occupied by drivers on that trip. (Credit: Antonio Lima)

The ellipse also helps us measure how direct a route is. The ellipse’s eccentricity tells us how elongated it is. An eccentricity close to 1 means the ellipse is similar to a line (high width and low height), while an eccentricity close to 0 means it is similar to a circle (width and height roughly similar).

Generally, a straight route is not a viable option because of physical obstacles, such as buildings. Drivers deviate from that idealized shortest path according to the street network and personal preferences. While these two phenomena are hard to model, we found that they are bounded by a ellipse of a particular shape, having a high eccentricity equal to 0.8.

To our surprise, the observed shape of the ellipse did not change with distance between the endpoints. It looks like in an urban setting, drivers are willing to take detours that are roughly proportional to the distance between their starting point and destination. Routes that involve bigger detours are simply not taken, or split into two separate trips.

Our study uncovered basic rules of a realistic routing model that captures individual behavior in a urban environment. These findings can be used as building blocks for new routing models that better predict traffic. And now that we know drivers have some quantifiable flexibility in their routes, we can use this information to design incentive mechanisms to alleviate congestion on busier roads, or carpooling plans based on individuals’ preferred routes.


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

CATEGORIZED UNDER: Technology, Top Posts
MORE ABOUT: transportation
  • OWilson

    The short route I take to the office, will depend on the weather, the time of day, the day of the week, whether school is in or out for the week, and whether or not I am early, or late.

    (Then there is that beauty who walks her dog a couple blocks over :)

    Hard to feed personal preferences into a dumb computer :)

  • Barry Marshall

    The route I take to work has the least amount of traffic lights.

  • http://www.mazepath.com/uncleal/qz4.htm Uncle Al

    Traffic rules are configured to maximize local revenue harvests via traffic court, sales tax, regulation (e.g., emissions), Enviro-whiner faux fuels (ethanol, compressed methane, transesterified adipocere); local levies for road repair (never done) and alternative transportation (only exant as studies and eminent domain).

    The I-405 El Toro Y in Orange County is 26 lanes wide. A brisk walk moves faster. “Commuter lanes” and traffic “enforcement” accomplish that. Bypass toll roads with constantly changing traffic-contingent fees are also speed traps. Pookie pookie – more studies are needed.

    • Doug Huffman

      Why reside in OC?

      WAZE permits efficient routing.

      • http://www.mazepath.com/uncleal/qz4.htm Uncle Al

        One solution is to drive like a maniac, allocating one eye for cops. By observation, the lights are timed ~10 mph over the limit. They have their rules and I functionally embrace them.

  • Ted

    Very interesting points. I would argue that commuters in large cities “usually go with the flow”. I would also challenge anyone to find an alternative route to work, that more than a few people can use. The painful truth in most large European cities I’ve visited/lived, is that you always favour the high-streets due to the fact that smaller roads are slower, have countless junctions, intersections & traffic lights, huge pot-holes and they of course lack the all important right-of-way…

    • OWilson

      I’m a bit of a scientist, and I’ve always been fascinated by traffic gridlock, and the relatively few (and cheap) algorthymic solutions available to keep the traffic moving.

      I drive only 2 km to work, but am confronted with some 17 stop signs or lights on my way to work.

      Flashback to 10 years ago living in the U.K.

      I lived on the East Coast, and often had to drive some 100 km to the Airport.(Humberside).

      Most times I could get there in 50 minutes, without even 1 stop, even though I had to pass through some 12 villages or towns.

      Turns out the few traffic lights in the towns were at default green, unless somebody actually pushed the button to cross. The other signs were basically yield to the Major Road Ahead.

      Their goal was to keep traffic moving, whereas the goal in my neighborhood, is to keep traffic stopped.

      We have “Traffic Calming Areas” replete with speed bumps, and every corner is a 4 way stop.

      They don’t like cars in my town, so they have no incentive or (as a city traffic engineer once admitted) no budget to keep traffic moving. They love cutting down 4 lane roads to 2 with “bike paths” even though most of the year our Canadian winter doesn’t encourage bicycling.

  • Alfredo Louro

    I don’t understand why we are “doing it wrong”. Why would you assume distance is the only variable, and it must be minimized?


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