Next-Gen Maps aim to Re-Balance Detail and Simplicity
Every sat-nav user is familiar with the chagrin of missing their turn because the map’s lines and circles don’t resemble the real world.
Yandex is blaming maps, not users, for these errors. At its annual conference in December, the company presented its re-designed maps boasting natural-looking 3D objects such as trees, bus stops, colored buildings, road markings and more. “We know that many users are bad at translating physical reality into a system of symbols,” Ilya Vlasyuk, head of map production of Yandex, said in the company’s video release. “Therefore, improving readability of maps is our job. One of the ways to achieve it is to increase the level of detail in the maps.”
However, many other popular navigation apps also offer similar enhancements. For example, Sygic and TomTom’s apps have embedded 3D views of buildings. Both, as well as Google Maps and Petal Maps, also accurately reproduce the design of motorway lanes and markings at busy locations. Yet, none of them offer the full range of native-looking objects embedded in Yandex’s next generation of maps.
Native images are a compromise
That said, adding more native-looking objects to sat-nav apps can be a double-edged sword, believes Andrey Vorobyev, deputy head of ITS competence center of the Moscow Road Institute (MADI). First, the more detail in the map, the more time it takes the commuter to sort out unimportant elements. Also, large 3D objects such as tall buildings or trees can block the view of smaller ones behind them.
However, a bigger issue is that any map, good or bad, distracts the driver from the road, he said. While improving readability can reduce distraction time, it cannot eliminate it totally because looking at the map involves taking one’s eyes off the road and re-focusing them. This inherent disadvantage can only be overcome by getting rid of maps altogether.
An alternative is provided by voice and haptic assistants, which do not distract the user from the road. However, their instructions are not precise enough, leading to navigation mistakes on complex road junctions.
AR-based navigation is the final goal
Vorobyov suggested that the ultimately solution to these issues will be the development of navigation tools based on holographic head-up displays for cars and augmented-reality wearables for cyclists, scooter riders and walkers.
Some of sat-nav app developers are now experimenting with AR-based navigation. In two cases, Google Maps and Huawei’s Petal Maps offer augmented reality navigation for walkers. Sygic’s app can project navigation tips in form of arrows, symbols and short messages onto the head-up display. In 2021, TomTom teamed up with AR specialist Phiar for the same reason.
In five years, we will see the first examples of mass-produced holographic devices for travelers. However, these systems will have to undergo substantial development and testing before they become truly convenient and reliable. In the meantime, enhancing maps can be seen as an intermediate step in this direction, he added.
For example, an app could inform users when they need to look at the map. Sygic’s current focus is on app visuality and elements that enable more predictive driving, said Lukas Dermek, Sygic GPS Navigation product manager: “For example, we would like to implement crossroads with traffic lights and crosswalks into the map visual. No details are clear at the moment but it is rather about safety alerts to be more careful when driving through crossroads and crosswalks. Also, we continue the development of new modern map skins that include all relevant information for a driver in a readable style.”
Producing and maintaining visually rich maps is a costly task, so that even the mighty Google uses them only in high traffic areas. Yandex’s Vlasyuk said: “The difficulty turned out to be that… we have about a hundred [new] entities to be digitized in a way that is fast, accurate and doesn’t come with many mistakes along the way. This requires a new approach to data processing. For example, satellite imagery, the main raw source for maps, does not have a satisfactory resolution for new maps. Therefore, we have to use multiple sources of data, from taking panoramic photographs to crowdsourcing images. Our mapmakers then process the collected data using a neural network and a set of newly developed tools.” Even so, it will take several years to create maps for all roads and cities in Russia and other countries where Yandex operates.
