Geofencing technology and transportation

You are driving your electric scooter to work. The device’s map indicates your position and the time to your destination. Suddenly, you hear a sound; you should slow down because you are approaching the downtown area where the speed limit is 20 km/h. You keep moving accordingly. Once out of the city center, you stop at the next light. You see a delivery robot crossing the street. A person is coming directly toward it, looking at her phone. But when they are about 75 cm apart, the robot moves slightly to the right and dodges the person; the pedestrian raises her head and looks impressed. You keep moving forward toward your destination. Now you are at a residential area where lawnmowers are cutting the grass. They move silently, precisely mapping the garden without bumping into objects or living beings. This distracts your attention from the road, wondering how they do it. With the neighborhood behind you, now the train station is in sight. The map on your scooter directs you toward the parking area, where you find a spot among a vast field of scooters, all perfectly aligned. Is this already happening? Not yet, but thanks to geofencing technology, it soon will be.

Global Navigation Satellite Systems (GNSS) and other localization technologies enable locating objects and people with extreme precision and in close to real-time. By leveraging this possibility, industries have integrated geolocalization modules and chips in their products and technologies, giving rise to many applications. As a result, what sounded like science fiction decades ago is a reality today: accurately obtaining positions down to the centimeter.

Today, determining position accurately and flawlessly is essential for automotive, agricultural, mining, and asset tracking, among other industries. However, for sectors such as mobile robotics and unmanned aerial vehicles, knowing the location of an object or a person is not enough. In these cases, mapping the surrounding space is essential; devices must recognize objects or living beings, either static or in motion, around themselves to decide the trajectory they should follow.

What is geofencing technology?

Geofencing means precisely knowing the spatial limits of a specific area and the distance to physical obstacles nearby that region. Generating an accurate virtual geofence is paramount for applications that, relying on high-precision GNSS technology, seek to determine their precise position to the cm level.

Geofencing in transportation applications depends on two technologies: Real-Time Kinematic (RTK) positioning and dead reckoning (DR). RTK corrects common errors in current satellite navigation (GNSS) systems through surveying. DR calculates the current position of a moving object by determining an already fixed position and then incorporating estimates of speed and heading direction over time.

Geofencing devices: lawnmowers and delivery robots

Lawnmowers and delivery robots are leading developments in the field of geofencing. They are the most tangible examples describing current location/GNSS technologies' capabilities when mapping a confined ground.

The first robotic lawnmower area mapping was done in 2011. It was done based on various sensors (hall effect, lidar, radar, and other proximity sensors). Since then, technological developments have focused on 1) establishing a geofence, determining the shape of an area, and 2) enabling device navigation in an established perimeter while excluding trees and obstacles within that area.

Looking through the lens of technological innovation, we can recognize three phases in the development of robotic lawnmowers (RLM). In the initial phase, hall effect sensors supported RLM devices, requiring the installation of a perimeter wire in the garden—a geofencing zone.

A few years later, RTK technology enabled virtual perimeters. RTK-based lawnmowers, through a local base station providing GNSS error corrections, increased accuracy down to the centimeter. The development eliminated the skills and time needed to install a boundary wire. This first step brought efficiency and less operational costs, resulting in a better user experience. Professionals could use these geofencing devices more efficiently and in different mowing areas.

The next step involved removing the local base station and relying only on error corrections provided by a network of base stations already deployed in the field. Trends and choices from manufacturers indicate an ongoing migration toward this technology. This will bring further ease of use and platform portability benefits.

Assuming “simpler is better,” the future should bring new geofencing systems (RLM) without a local RTK base. This innovative technology reduces the time needed for installation and calibration to zero, evolving towards a “plug & play” user experience.

Delivery robots are also considered geofencing devices. Although in this case, the story is slightly more complicated because they should recognize, in seconds, what surrounds their space. Detecting moving objects to avoid crashes is a variable adding complexity to the geofencing equation. Lidar and radar technologies currently achieve this. In the coming years, though, Vision-RTK promises even better results. Geofencing companies are eager to improve accuracy because cities, logistic centers, and other industrial sites demand it.

Geofencing applications: accurate geofencing enables micromobility compliance with new road regulations

Geofencing can aid in organizing urban areas as it provides the means to move safely and efficiently on roads and streets. Shared e-bikes and scooters may seem unrelated to mapping the space. Why even care about accurately geolocalizing them if they can move randomly without considering other objects? Since the advent of micromobility, these vehicles move through cities subject to mild or no traffic regulations. But “The times they are a-changin’ ” and now its industry faces increasing limitations imposed by municipalities and road regulation authorities; challenges, not evident at first sight, are now revealing themselves.

Some new yet-to-be-solved issues concern where these vehicles can circulate, where people can park them, and speed limits according to location. A solution, however, might be right in front of our eyes. RTK-based high-precision positioning brings answers to these new challenges.

For example, an accurate-enough standard GNSS receiver would enable users to localize vehicles for their next ride. RTK-based systems can enable cm-level geofencing, which is helpful in use cases such as no-riding zones in pedestrian areas, banned sidewalks and bicycle lanes, or authorized parking areas and speed limits (also supported by geofencing).

More geofencing applications or the creation of ad hoc policies

Integrating new micromobility vehicles into the city's space will require government efforts. They may not need to build dedicated lanes (as with bicycles in the Netherlands forty years ago) because these vehicles can travel on standard roads. But certainly, implementing new policies for micromobility operators is a must. These policies should address three main aspects: safety, operational costs, and profitability maximizations.

Safety includes speed limits, sidewalk detection, and forbidden riding zones. The focus on operational costs includes keeping costs low and potential economic penalties for parking in unauthorized areas. Finally, profitability maximization consists in offering users devices closest to their current location, reducing maintenance and operational costs for the deployed fleets, and increasing the service area and the monetary return per ride while limiting the number of parking fines.

Gone are the days when governments launched regulations for one or two types of vehicles. Nowadays, cars, buses, bikes, motorbikes, mopeds, scooters, and e-bikes, all travel at different speeds and in different directions. Ordering cities according to the needs of these vehicles is essential. For that aim, precise geolocation technology is a valuable resource. If you are still in doubt, look at large urban areas where regulations still need to be put in place. The result: chaotic streets, increasing complaints against improper parking that creates clutter, and the safety of pedestrians and multiple drivers at stake.

And so, what should we expect?

The scenario for the coming years is already in place. On the one hand, mobile robotics will scale up in the market (volumes and size alike), increasing the number of players adopting high-precision GNSS architectures. By 2023, we can expect professional, prosumer, and consumer platforms to launch new models in different geographies. For instance, in Japan, remote delivery robots should deploy in April 2023 after the revision of the Road Traffic Act. On the other hand, micromobility operators will keep developing proof of concept technologies (PoCs), moving forward with an increasing number of deployments scheduled for springtime 2023.

Geofencing devices such as mobile robotics can be precisely located thanks to a positioning revolution based on digital and already-in-place infrastructures. This combination comprises GNSS solutions, an extensive network of base station antennas, online data services, and error correction services adopting standardized protocols such as SPARTN. Used smartly, these building blocks should bring operators and users more efficiency and lower service costs.

Mapping the surrounding space is an enterprise that took humanity centuries to develop. What first commenced as an activity to know geographical confines has now translated into accurately defining the position of each object in space, including its surroundings. For sure, Carl Friedrich Gauss and Alexander von Humboldt, whose ideas and trips ignited the possibility of mapping the world, would marvel at the steps taken so far in localizing objects‒with centimeter precision. Geofencing technology is at an early development stage. But when the vehicles we travel on integrate the latest geofencing technologies along with urban regulations data, transportation geofencing will take us all to a higher mapping level.