At GoodVision, we collaborate remotely with municipalities, transportation agencies, traffic surveyors, and engineers worldwide daily. But occasionally, we like to meet our partners in person—after all, nothing matches face-to-face interactions, especially when solving complex transportation challenges.
Our Open Day events, organised regularly in our Prague office, are the perfect opportunity for live networking with GoodVision clients, fellow industry experts, and everyone passionate about smart mobility. This June, we held its third edition, featuring Eng. Zdeněk Lokaj from Prague Transportation University ČVUT, Richard Bureš, council of the Prague 1 municipal district, and Jiří Kolář, Chairman of the Board of Directors from our partners, KH Servis, as panel speakers.
The main subject of this year’s event was AI traffic management and planning. However, instead of discussing the technology in the void, we set our panels in the context of the smart mobility solutions recently deployed in Prague to inspire urban areas globally to follow in the footsteps of the Czech capital.
Here are five key insights from the event, showing how all major cities can leverage data, video analytics, and AI traffic solutions to overcome transportation woes and improve the quality of life for their citizens.
In most major cities, parking spaces are already stretched thin. Even though parking lots take up to 70% of space in non-residential areas, we spend 17 hours a year on average looking for an available parking spot.
In Prague, excessive parking occupancy is particularly harmful to the city centre. Our guest from the city council estimated that every 24 hours, over 80,000 supply trucks enter the historical centre district, serving courier deliveries and the robust tourist infrastructure: bars, restaurants, cafes, and hotels.
More than 80,000 supply trucks in Prague enter the historical centre district every 24 hours.
All this traffic puts a heavy burden on the parking capacity of the area, leading to parking congestion. And with that volume, parking time exceedance, claiming spots reserved for residents or people with disabilities, blocking driveways, parking without a ticket, and other violations are much more common. The city council suspected that improved law enforcement could help solve the issue, but the police were stretched too thin and couldn’t deal with all cases of parking abuse.
The implementation of GoodVision’s AI-powered traffic monitoring system confirmed this theory. “Immediately after the deployment, we saw a significant improvement”, the council representative revealed. The smart monitoring improved parking abuse and time exceedance detection. The tool also provides a full vehicle record for any administrative proceedings: licence plate, and status before, during, and after the violation.
The new smart mobility system helps police react faster and deal with more cases. Automated offence detection lets drivers know that improper parking won’t go unnoticed even if they don’t receive a fine immediately. This has quickly led to better compliance and more spots around the centre for those needing them.
As another of our guests, Professor Zdenek Lokaj put it, “Drivers will never behave predictably; they are stochastic systems that are often influenced by emotions”. Even though technology cannot eliminate the random factor of driver behaviour entirely, it can minimise its consequences.
The perfect example is applying AI traffic tools to predict, detect, and react more effectively to road events. According to Professor Lokaj, for some emergency service centres, up to 60% of calls are bogus. These unnecessary dispatches result in a loss of time and resources at best and a loss of life at worst when no ambulances are available to attend to the actual incidents. Intelligent traffic monitoring systems provide visual confirmation, helping dispatchers decide if the reported road event has really occurred.
For some emergency service centres, up to 60% of calls are false, leading to unnecessary (and costly) dispatches and impacting road traffic.
What about the unreported collisions? Smart, real-time traffic monitoring with automatic incident detection can instantly notify traffic operators and emergency services based on preset criteria. This way, they can react accordingly if, for any reason, witnesses and participants decide not to report the incident. AI and machine learning can help anticipate random incidents based on long-term data and act proactively.
Another advantage of smart mobility solutions is quick data processing. Using real-time traffic monitoring paired with AI, traffic operators can instantly access up-to-date information and share it with services and drivers, helping everyone stay informed about the situation on the road.
More often than not, the impact of real estate projects on the larger traffic isn’t the top concern for developers, who tend to downplay it in their preliminary forecasts. Smart mobility data helps municipalities double-check these studies and anticipate the real consequences of future development.
Letňany is a district of Prague that has seen intense development in the past few years. One of the recently proposed projects involved building more houses near a major exhibition centre, which wouldn’t affect the area's traffic according to the developer's study. The borough officials were sceptical about the results and asked our KH Servis partners to conduct a complementary traffic survey.
The results confirmed their doubts. The survey proved that the actual traffic volume was three to four times higher than shown in the initial study. Even on normal days, the daily traffic would reach thousands of vehicles. Such numbers drastically surpass the capacity of a two-lane road that is a primary connection between the venue, the new development, and the rest of the city. And on days when the exhibition centre houses huge events like concerts or conferences, the traffic volume could reach even 70 thousand vehicles daily for several days in a row.
Large-scale traffic surveys like these are much easier to run with smart mobility data platforms. Systems like GoodVision collect data automatically, reliably, and continuously. AI algorithms process records quickly, providing accurate, visual, and numerical input for traffic modelling. Combined, all these features give municipalities the facts they need for informed development policymaking.
Here are the key statistics mentioned by our expert guests during the Smart Mobility Day event.
Emergency dispatch centres need a way to improve detection and reduce response times:
Tourist activity and events can severely disrupt traffic throughout entire districts:
Urban parking challenges call for better enforcement and compliance through technology and policymaking:
Professor Lokaj noted that, at best, it takes 10 minutes to react to a detected event. According to our data, it may take the average operator as much as 42 minutes to respond. In incident response, every second matters, so reducing that time even by a small margin can make the difference between life and death.
In Prague, the response time to a detected road event is, at best, 10 minutes. However, in many cases, the response time reaches 42 minutes. In more crowded cities, these statistics may be even worse.
Here, AI's data processing speed is key. Using trained patterns and self-learning, artificial intelligence-based road traffic algorithms and models instantly classify collisions or other dangers. Paired with live traffic video, they help smart mobility tools monitor roads in real time. When an incident happens, the system alerts the right person to take action.
However, improving incident response isn’t the only possible use of real-time traffic monitoring tools. Live Traffic and similar platforms can be set up to anticipate traffic jams by recognising congestion-forming patterns. If the specified criteria, e.g., increased traffic volume, are met, traffic operators will receive a notification, allowing them to quickly apply countermeasures, e.g., opening additional lanes or rerouting. By minimising congestion, smart mobility solutions contribute to smoother traffic flow, lower operational costs, and reduced collision rates.
“If there’s no reason for drivers to follow the rules, they won’t do it”—Professor Lokaj's brutally honest claim strongly supports the importance of traffic law enforcement.
To prove his point, he used the example of a football stadium situated in the Prague 10 district. On match days, the area around the stadium becomes completely clogged, leaving people nowhere to park in a three-kilometre radius. Knowing that a fine or towing is unlikely, they park everywhere, including in the blue zones. Worst of all, improperly parked vehicles regularly block the way for ambulances coming in the direction of a nearby hospital.
“If there’s no reason for drivers to follow the rules, they won’t do it”
In Prague 1, only 54% of all parking fines are paid. Up until recently, one reason for that was low, non-cumulative fines. While such measures can be effective, drivers despise them. As such, they need solid backing to implement them. Data, analytics, and modelling can support such policies, helping officials get public approval for unpopular decisions.
Smart mobility solutions also allow municipalities to target offenders instead of introducing general measures affecting all citizens or the city’s economy. For instance, rather than closing entire zones for car traffic, police can use analytics and recorded vehicle data to apply fines. Digitised, automated ticketing is another part of the solution, but again, it must be backed by a reliable data collection and analytics system.
Studying traffic data may also hint at the direction policymakers should take in the long term. Trends in car usage, preferred mobility modes, traffic volumes across the city, the effectiveness of applied solutions, and other factors should be considered when planning urban strategies for years to come. AI traffic analytics can help municipalities look into the future by quickly processing large volumes of historical data.
The five points we covered in this article merely scratched the surface of AI and data in traffic issues we discussed during our Smart Mobility Day event. Between implementing new traffic policies, using technologies in urban planning, and the role of traffic information in smart city projects, there’s a lot we can learn from data to make traffic smoother, faster, and safer.
We regularly search for new data approaches and insights when meeting with traffic specialists and enthusiasts and connecting digitally via our webinars.
Check with us regularly to join us in these endeavours, or sign up for our newsletter at the bottom of the page to get updates about upcoming online and offline events.