Responsive Traffic Management - Artificial Intelligence in Action
Updated: Jul 10
AI has the potential to transform mobility
In this world nothing is said to be certain except for death and taxes - and traffic jams. Every day, millions of commuters around the world see their precious time frittered away in backed-up traffic - 54 hours a year for the average American commuter. This is not only detrimental to human welfare but even more so to the environment.
Acknowledging this growing issue, many companies and governments are now looking to novel technological solutions to traffic management. Below we highlight examples of some AI-assisted approaches that are leading the way.
Helsinki diving headfirst into smart mobility
Helsinki is one city making strides in this regard. In 2017 the city council committed to reaching a 60% reduction of 1990 greenhouse gas emissions levels by 2030 and to become carbon neutral by 2035. The success of this ambitious commitment hinges largely on changes in the transportation sector where 55% of the projected reductions are targeted. Many interesting projects have arisen in this context and the west harbor neighborhood of Jätkäsaari has developed into a fertile testing-ground for innovations in smart mobility.
Formerly a central hub of international shipping container traffic, the Länsisatama harbor now serves as a bustling passenger connection between Helsinki and the cities of Tallinn and St. Petersburg. While home to only a few thousand permanent residents, millions of international travelers pass through the small Jätkäsaari neighborhood on the way to their destinations each year. With limited detour options and high traffic volumes, even small bottlenecks can have a large impact on whether they get to their destinations on time
The Jätkäsaari Smart Junction project was designed to address this issue through the development of sophisticated traffic simulation models adapted to the local context. Since implementation began in Q3 2019, radar devices and cameras have been set up at key intersections, collecting data on lane-specific vehicle counts, travel times and stops in the area. The resulting datasets are uploaded to the Jätkäsaari Open Data Catalog where they provide the basis for analysis into the improvement of intersection light timing and the optimization of vehicle flow.
As part of a wider traffic optimization system, data collected through the Smart Junction sensor network is supplemented with information on ferry arrivals, vehicle loads, road work projects and current weather conditions. This rich supply of data allows AI-assisted analysis to create accurate real-time projections on traffic movements and expected individual time requirements.
The city leverages this data to coordinate the “just-in-time” arrival of heavy goods vehicles to the ferry port. Through the implementation of the FinEst Mobility app, truck drivers are provided with accurate updates and projections that allow them to better account for changing conditions and reduce their wait times at the port gates. In this way unnecessary congestion, as well as noise and air pollution, are significantly reduced.
Comprehensive data collection also allows for the better coordinations of local deliveries. As Jätkäsaari Mobility Lab Project Manager Juho Kostiainen explained to us: “One project collected detailed entrance data in the city and developed a proof-of-concept solution for routing delivery companies to the right entrances. These are now utilized in a new pilot that tests the perceived value and further development needs for last-meter routing with professional drivers and logistics companies“
This approach to mobility is further bolstered by the Helsinki Region Infoshare website. Functioning as a centralized databank, the platform compiles a wide range of regional information. In addition to the traffic data outlined here, this also includes data on zoning, air and water quality, energy consumption, planned development projects, as well as 3D maps and survey results – over 600 discrete datasets in total.
More than just a resource for traffic engineers and city planners, the platform is publicly accessible and free of charge. By making the catalogue available to Helsinki citizens and third-party developers, local authorities hope to foster an inclusive process and increase input from outside the transport authority.
Right on time - smart traffic lights in Pittsburgh
On the other side of the Atlantic, the application of artificial intelligence in traffic optimization is also taking off. Developed at the Robotics Institute of Carnegie Mellon University, the US city of Pittsburgh began in 2012 to implement a system of intelligent traffic management.
Similar to Jätkäsaari Smart Junction, data on vehicle and pedestrian movements through 50 key intersections is analyzed with the assistance of AI-powered software. As algorithms process the data in real time, the timing of traffic lights is automatically adjusted, coordinating and optimizing movement throughout the city.
The results are impressive. Rapid Flow Technology – the private sector implementing partner – suggests that this technology has reduced wait-times by up to 40%. With less automobiles sitting idle, journey times fell by an estimated 25% and vehicle emissions by 20%. A similar system piloted in Maricopa County, Arizona, reduced wait times by a whopping 50%.
And this is just the beginning. As the increase in wireless technology allows more data to be exchanged – both between vehicles and from vehicles to responsive traffic systems – these gains are only likely to increase.
“Better understanding of the traffic situational picture and using that data and information to optimize traffic flows based on preferred priorities and contextual parameters is one of the key cases for AI.”
Juho Kostiainen, Jätkäsaari Mobility Lab Project Manager
AI drives improvements in mobility services
But optimizing the flow of commuter traffic is only one side of the coin. And a lot of efficiency gains can also be achieved through bundling – reducing the total number of vehicles needed to fulfill our transit needs. The rise of vehicle sharing platforms and on-demand public transport solutions in recent years would have a significant impact on reducing congestion. Yet, many services struggle to become profitable due to low utilization rates.
AI-driven services like Ubiq’s act as a valuable supplement to smart municipal traffic management systems by providing mobility services with reliable fleet optimization. By facilitating an optimal fleet distribution, Ubiq ensures that vehicles are in the right place, at the right time to meet demand. This means not only improved vehicle availability for the user, but less unnecessary driving and a reduction in associated emissions. It also means that operators are able to increase fleet utilization and save on operating costs.
In facing the unprecedented dual challenge of global climate change and urbanization, a wide range of tools and solutions will be needed. In addition to smart traffic systems and a transition to renewable energy resources, AI-driven forecasting services like Ubiq’s have a vital role to play. By making the most of developments in data science and artificial intelligence, traffic jams no longer need to be one of life’s certainties. Solutions to death and taxes have a bit further to go.
Ubiq enables operators to effectively position fleets to serve strategic goals. For more information, contact firstname.lastname@example.org