The speed at which new technology changes our daily lives has reached breakneck levels. From our homes, to our places of work, to our public spaces, technology is driving major shifts in the way we tackle problems of all types. One specific area in which exciting advances are being made is how we manage our roadways. At the end of 2016, there were an estimated 1.32 billion cars on the road worldwide, and that number is only going to increase. It’s clear that effectively, efficiently, and – most importantly – safely managing areas like road infrastructure and traffic flow is of the utmost importance.
Using technology to help us in these tasks is nothing new, but thanks to major improvements in areas like 4G data availability and cloud storage, some exciting new applications have arisen. One such application is Vaisala RoadAI system. RoadAI is a computer vision powered data collection platform that is aligned with C-ITS thinking and architecture. The main value for the user comes through their everyday maintenance and seasonal asset management data needs – resulting in better use of resources, lower costs, and safer conditions for drivers.
The primary goal of RoadAI is to make it possible to safely and continuously generate visual data that can be used by agencies and stakeholders to make better decisions affecting transportation safety and resource use. At its core, the system allows vehicles and human operators to make notifications and to upload real-time visual information taken from onboard cameras that can then be accessed, analyzed, and shared by the people and systems that need it.
The level of connectivity allowed by current wireless technology means that entire fleets of vehicles can be connected to the system, turning each one into a data collection platform capable of producing a constant stream of still image and video information. That can be done either automatically through automated uploads, or manually using RoadAI’s hands-on-wheel technology.
The hands-on-wheel aspect of the RoadAI system is designed to enable a vehicle’s driver to manually create and transmit a note while on the road without diverting their attention from the task of driving. By integrating an easily accessible button onto a vehicle’s steering wheel, RoadAI allows the driver to capture “speak notes” and transmit visual data they deem important with a simple push of the button and voice commands.
On the automated side, advancements in computer vision mean that RoadAI has the capability to independently determine points of importance in the video imagery that it generates. That allows the system to recognize certain objects, like road signs, on its own. As a result, RoadAI can transmit important data regarding things like changes in signage, on-road hazards, and even weather conditions without the need for human input.
All of the visual data generated by RoadAI connected vehicles can be transmitted to, stored, and processed on the cloud, making both the raw data and the resulting analysis easily available to connected agencies and stakeholders.
Access to this kind of data collection and analysis represents a huge improvement in the tools that cities have at their disposal to manage road infrastructure, traffic, and public transportation. There are countless examples of how planners, engineers, and managers can put the data provided by RoadAI to use, and even other system-connected vehicles can benefit from the real-time visual information collected.
One of the most powerful features of RoadAI is the ability to share collected data with a wide variety of stakeholders. Access to real-time data on things like road changes, temporary hazards, and weather conditions are beneficial to a wide variety of agencies and companies, and the ability to coordinate and share such data outside of C-ITS systems is currently a major weak point. RoadAI allows visual data and analysis to be shared via a map-based user interface that can be accessed from the web, making it easy for any number of stakeholders to benefit from the system.
RoadAI enables easy management of the data collected by both human inspectors and automated image and video information, which then facilitates better resource allocation. For instance, computer vision algorithms can effectively identify and analyze road hazards like snow and ice. Managers can use system integrated reports and task lists to allocate resources with just one click. Only having notes easily in order, supported by images and videos saves plenty of time and helps to ensure safer roads and less wasted resources.
Computer vision algorithms are now so good that they can match, and even outperform, human ability in some detection and classification tasks. As a result, cities utilizing C-ITS technologies like RoadAI can reduce the number of personnel needed to both collect and analyze data. For instance, potholes could be mapped using video data collected automatically from city fleet vehicles already on the road, reducing the number of human surveyors required.
Vehicles that travel consistent routes on a daily basis, like city buses, provide an enormous opportunity for data collection and synergies between maintenance and public transportation. By connecting public transportation vehicles to a RoadAI enabled network, cities can collect constant, consistent data from trips that would’ve run anyway, reducing data acquisition costs. From a management perspective, the data from a bus on a given route can be shared automatically with other system-connected buses in order to provide drivers with immediate feedback on changing route conditions.
Self-driving vehicles are already being tested on roads in a number of countries around the world. Whether for personal use or public transportation, autonomous vehicles depend on reliable data to operate safely. The ability to tie in a network of autonomous vehicles to RoadAI’s real-time road and weather data would help ensure that drivers, navigation services and future self-driving cars can operate on a predictive, rather than reactive, basis.
From online shopping to major infrastructure projects, data is at the center of the modern world. While data-hunger isn’t always a positive thing, there are countless areas in which new technological advancements are opening up opportunities for positive change. Cooperative intelligent transportation systems are one such example, putting advancements in areas like wireless connectivity and cloud computing to work to help cities and agencies solve real-life problems.
Vaisala’s new RoadAI system is already helping bring about such positive changes on roads in multiple cities throughout Finland, allowing those municipalities to better manage their resources, provide better infrastructure, and make roads safer for their citizens and employees alike. Hopefully, in time, more and more cities adapt AI powered systems for their everyday use, and around the world drivers will embrace the benefits of C-ITS, allowing RoadAI and other systems like it to expand the positive effect they’re currently having here at home.
Markus is responsible for commercialization of Vaisala´s computer vision based services for roads and rails. Markus holds a Masters degree in technological entrepreneurship from Lappeenranta University of Technology. He is a former officer of Finnish Defence Forces and has been the head for Digitalization Program and multiple ICT projects in the Finnish Transportation Agency (FTA). Markus was also a co-founder and CEO of Vionice (acquired by Vaisala in 2017).