Lida Joly explains how data-driven traffic analytics will help us reach zero emissions and zero fatalities
The European Commission has set the ambitious goal to reduce emissions and serious accidents by 50% by 2030 with its Smart and Sustainable Mobility Strategy. Furthermore, by 2050, the commission, as well as the United States Department of Transportation, plan to realize Vision Zero where the target is to achieve zero road fatalities and emissions. But how to reach these ambitious goals? A promising trend is to leverage big data and data-driven analytics to help governments and local authorities accelerate towards Vision Zero.
According to the World Health Organization, every year approximately 1.3 million people die because of road traffic accidents. That is two fatalities every minute. Non-fatal traffic incidents aren’t included in this number. However, these have a significant impact as well not only on the involved individuals and their family, but also on the economy. The WHO estimates road traffic crashes cost most countries around 3% of their gross domestic product.
The second major pillar of Vision Zero are traffic emissions. According to the International Energy Agency, road transport was responsible for approximately 25% of all CO2 emissions in 2021. Besides its effect on global warming, traffic emissions also cause a harmful effect on public health. A report from the European Environment Agency indicates air pollution as the single largest environmental health risk for the European population with exposure triggering diseases, such as lung cancer and asthma, and causing a reduced life expectancy.
A promising trend is to leveraging big data and data-driven analytics to help governments and local authorities accelerate Vision Zero. Using such technologies not only offer new ways to measure and monitor traffic for better safety and efficiency, it also enables us to combine data sets and contextualize analysis, for example traffic data with pollution data.
We are living in an increasingly connected world with Internet-of-Things technology integrating in every industry and innovative applications generating huge amounts of data. Connected vehicles are one example. They generate data that inform us where, when, and how fast a car is driving. Satellites are capturing weather, pollution, and other atmospheric data, and so on. Everything is being measured enabling us to understand what mobility is, how traffic is evolving, and the impact it has on the world.
To achieve the goals of the Road Safety program, the European Commission has outlined different key performance indicators with ‘infrastructure safety’ (dangerous situations) and ‘safe road use’ (speeding) among the most important ones.
Previously, road authorities and governments would record and analyze locations of frequent crashes and safety incidents, before being able to take measures. Now, data-driven traffic analytics enables road authorities to transition from a reactive to a proactive approach. Connected vehicle data can be fed into artificial intelligence models together with other types of data, e.g. weather data, to make predictions based on historic unsafe driving behavior and other parameters to identify where accidents are most likely to happen, even before one occurred. Such simulations and analysis can also be performed also when re-designing or starting a new road construction program. Being pro-active is a must when aiming for zero road incidents.
Similarly, data analytics is used to drive the transition to greenification and electrification of vehicle fleets.
Inefficient traffic situations, such as congestion, contribute to an increase in emissions and air pollution. Data-driven traffic analytics is used to measure such inefficient patterns and determine where traffic is coming from and going to, how it’s flowing through dense urban areas, and which measurements can be installed for a smoother process, for example to optimize traffic light performance.
On the other hand, the electrification of vehicles offers a promising reduction in traffic emissions but requires the necessary support. Trucking companies are now analyzing movement patterns of their trucking lines and optimizing replacement of traditional trucks based on the driving journey, waiting times, and existing EV-charging infrastructure. The EV-charging operators are now looking to optimize the location for the installation of new truck charging stations, knowing that a single installation easily costs 10 million EUR of investment.
Connected but fragmented
The traffic and big data industry is at an interesting phase right now. Due to IoT technology, many mobility companies and traffic authorities are generating mountains of data. However, most don’t know what to do with it or fail to maximize value extraction out of the data.
The seemingly complexity of traffic data analytics often acts as a roadblock for companies to start learning from their traffic data. This highlights the industry’s need for simple solutions that not only facilitate the analytical process, but also enable companies to leverage multiple data sources at once.
We live in a connected world, but the industry is still fragmented. New innovations and data sources are emerging on the market, such as multi-modality, the availability of public transport (GTFS) and electric bike data (GBFS), and so forth.
However, most tools are closed-box solutions that only handle one type of data set. Standardization and open-box solutions are becoming increasingly important as we move forward, as well as collaborations between market leaders and other participants bringing new innovations to the market.
Collaborations are already taking place, such as between INRIX and General Motors, who jointly released a new road safety platform, or between Wejo and NIRA Dynamics with the release of a new road health and safety platform or between xyzt.ai and Bridgestone to provide municipalities a fast and easy solution to monitor road safety and efficiency.
Data-driven analytics is helping the world become a safer and greener place. To reach the ambitious goals of 2030 and 2050, we need more accessibility to big data, the necessary tools to visualize and analyze the big picture, and more and stronger collaborations between old and new industry players.
See also article in GeoConnexion International winter / 2023
Credits Bart Adams