׉?ׁB!בCט+u׉׉ 7cassandra://58b3lBaPIIpIUU1EL8olCeqtuOqnwnhlw06mJZMXSHY`׉ 7cassandra://8vXlFJPdy87DDlTM2AXWGWgWbzGFI9rVn-Jb1Qg9tQk}e`h׉ 7cassandra://kTstaYmRNewCgfmTVA4mEdlVgobmlmUxWY4r81Ao7-I*a`hn**L:a/_)aנhn**L:a/_)`!o\9׉H"https://www.technolution.com/move/Gׁ ׁ r׈Ehn**L:a/_)׉EKMOVE ON 2025 Livable and accessible Digital solutions for today’s cities ׉ 7cassandra://kTstaYmRNewCgfmTVA4mEdlVgobmlmUxWY4r81Ao7-I*a`hn**L:a/_)hn**L:a/_)+בCט+u׉׉ 7cassandra://KeFKQ1HqZKpPT5UB2LtcqaDVp-9pjW4UUvJB5vuifac2!`׉ 7cassandra://Q8EFmXvw7DWFugmQd8ibbTt9ERGyf8xSxeJDveXW_v80y`h׉ 7cassandra://fBBuj7Ix0poENJAIGDrB-0czRfqaJf-ULFkvjEKIwfE`hn**L:a/_)rט+u׉׉ 7cassandra://qrAH9Fmdg9YuUWhqzJBVZi3tPQyWYC5LhHct2Bl8k-8`׉ 7cassandra://f1N2WyF0TkMISLnsnTMo8O4tDQ83QYnWqneQxtDqkx4S}`h׉ 7cassandra://REITILXJ1wOBEpLH0DC46ZOP5FN_OywH1nJsFthM5D8 `hn*+L:a/_)sנhn**L:a/_)dL_9׉S G ׁ ׁ rנhn**L:a/_)g̞̬9׉H%https://www.technolution.com/move/nl/Gׁ ׁ rנhn**L:a/_)h$yg9׉H%https://www.technolution.com/move/nl/Gׁ ׁ rנhn**L:a/_)im̨j9׉SG ׁ ׁ rנhn**L:a/_)j|j9׉SG ׁ ׁ rנhn**L:a/_)km}^ 9׉S G ׁ ׁ rנhn**L:a/_)lo9׉S G ׁ ׁ rנhn**L:a/_)m9сhn**L:a/_)=+בCט+u׉׉ 7cassandra://P5AFG7vWoZRF9nnq7u0EaLdkR_VO3FMrL6aRMc4I99g`׉ 7cassandra://gvYTLu6yVkV--_mMLsOd460b6kPriL5-oFLLIKYJW0ge^`h׉ 7cassandra://we-kQVY_bIuLzKyBuaSQhEt8vwTPtOWQ8xLXTYubYNQt`hn*1L:a/_)ט+u׉׉ 7cassandra://-mCYlJQjt1VPDuuwoeC-DYaqWd6WBmRyPquVBgH_oyU?`׉ 7cassandra://CGaGUJJ0kujRDXEOiN8WWDIXcJA3XClbdMWOkY-cJKkZ`h׉ 7cassandra://70ody-qxC--8QoOrZyEfhudY4NuAV27ygqoTeN7HU2M!`hn*1L:a/_)נhn*1L:a/_)̞̬9׉H%https://www.technolution.com/move/nl/Gׁ ׁ rנhn*1L:a/_)&!9׉SG ׁ ׁ rנhn*1L:a/_)$yg9׉H%https://www.technolution.com/move/nl/Gׁ ׁ r׉E EThe good thing is that an AI model can learn the distinguishing features that really matter to control an intersection. FlowCube: capturing cyclists and pedestrians The FlowCube traffic sensor is used primarily for traffic at intersections. Traffic flows are captured using Vision AI. The great strength of the FlowCube is its flexibility. It can learn to recognize cyclists, pedestrians, and any other type of road user. By placing FlowCubes at multiple locations, the routes of individual road users can be determined – without identifying them or storing any data. In addition, we use the FlowCube to record near misses at busy intersections. The information we collect in this way can be a valuable contribution to monitoring the handling of traffic. In the Netherlands, the FlowCube has proven ideal for obtaining a better view of cyclists and pedestrians (motorized traffic can be ‘seen’ with induction loops). In the US, where intersections rarely or never have any detection infrastructure, cities are using the FlowCube to provide traffic control information about all modes of traffic – including public transport. AI and the smart TLC It can be more of a challenge to apply Vision AI in the Netherlands. There are many iTLCs in this country: smart traffic light controllers. iTLCs receive information about the traffic situation from traditional detection loops and vehicle GPS information. Using queuing models and optimization techniques, the traffic controller then determines the optimal sequence for green for each direction on the intersection. Vision AI applications such as the FlowCube can currently 22 only present their information to an iTLC if they have removed all contextual information concerning vehicles (distance to the stop line, length of the vehicle, lane), whereupon the traffic controller reconstructs the information that is relevant to its task. This means potentially useful information is being discarded, so that the power of Vision AI is not used optimally. Do more with less data So what can we expect AI and traffic management to do? What Large Language Models have proven is that the total corpus of information on the internet can be summarized in a relatively limited set of weights of a neural network. In technical language: the entropy of the data and the knowledge that is collected and stored is high, and AI models can make do with much less data. This is possibly true also for specific applications such as controlling traffic at intersections. AI is openminded, some would even say naïve. The good thing about this is that an AI model can learn the distinguishing features that really matter to control an intersection. People think that a model will have to be able to count individual vehicles in a queue, but maybe that isn’t necessary at all for good traffic control scenarios, for example if the model can see other useful patterns, such as the length of the queue, or the risk of a tailback. The next question is whether we humans are able to make sense of it and – crucially! – whether we have the confidence to allow a model like this to control the traffic. In any case, any model will have to be tested at length and thoroughly before we allow it anywhere near the real world. We don’t know yet what they will look like, but we do know one thing: we are going to see new AI applications in traffic management soon. ׉ 7cassandra://we-kQVY_bIuLzKyBuaSQhEt8vwTPtOWQ8xLXTYubYNQt`hn**L:a/_)B׉EnFlowCube: AI-based traffic sensor Technolution’s FlowCube is a flexible, AI-based, multi-modal traffic sensor that, counts cyclists and pedestrians, calculates routes and travel times, and provides traffic density insights, among other things. The FlowCube does not store privacysensitive data, is compact and easy to deploy for traffic management in any city. 23 ׉ 7cassandra://70ody-qxC--8QoOrZyEfhudY4NuAV27ygqoTeN7HU2M!`hn**L:a/_)Chn**L:a/_)B+בCט+u׉׉ 7cassandra://HM4tITYN7pBGvGPp-jtIDAjTTiidbFs2Wr4ddwj6JWM`׉ 7cassandra://P1v9QvUfapHYicqwYWK-wmTZmetBCeVoV0rdcNiPlC8kB`h׉ 7cassandra://CeGZIsCKeJA938jAptr8C8P6aHmMyDLb4p66Tyz5nnEW`hn*1L:a/_)ט+u׉׉ 7cassandra://RQyeaY8XQuSWNLglSrAczQ4YiOZuqD_8gzguzKwvkuIGo`׉ 7cassandra://-JA2hy-E5Zy4wF_80Bc7Q2IfuJWDS_b2oVLmzw-19Igw`h׉ 7cassandra://ec9H79SlYB7UQOfxQ2dTt4_uEOneYL8MjV2D-0dJ6jw#`hn*1L:a/_)נhn*1L:a/_)̞̬9׉H%https://www.technolution.com/move/nl/Gׁ ׁ rנhn*1L:a/_)&!9׉SG ׁ ׁ rנhn*1L:a/_)&!9׉SG ׁ ׁ rנhn*1L:a/_)$yg9׉H%https://www.technolution.com/move/nl/Gׁ ׁ r׉EfInstruments for a livable city Smart Urban Traffic Zones 7.13 a.m. Olle Lundqvist sets off from the bakery depot toward downtown Gothenburg to deliver freshly baked fika pastries to Espresso House on Kyrkogatan. This used to be a frustrating ride: a narrow street where offloading goods is difficult. But now Olle uses an app that tells him which loading bays are available. “Saves me endless searching again,” he thinks with satisfaction. With more than 600,000 inhabitants, Gothenburg is a big city. A huge number of deliveries are made in the historic center on a daily basis. In the context of its Smarta Urbana Trafikzoner (Smart Urban Traffic Zones) project, the city has equipped dozens of delivery vans with a GPS tracker to gain real-time insight into how Gothenburg’s more than 400 loading bays are used. Technolution provided the services to make this possible. Services for smooth loading and unloading Gothenburg is using these Technolution Move services to provide parcel delivery companies current and historical information about available loading bays in the city. Determine what loading bays are occupied This service aggregates GPS tracker data every minute, strips it of privacy-sensitive information, and determines what loading bays are currently occupied. Real-time insight for drivers The aggregated data is sent to an app that gives drivers real-time overview of the loading bays in the city. Historical analysis The data is fed to a tool for historical analysis. Delivery companies use the historical data to plan their delivery routes. Camera support The GPS data only shows vans that participate in the project, but another vehicle or a waste disposal vehicle could also be using a loading bay. This is why some places are equipped with camera-based sensors. Technolution merges this sensor data with the GPS data to give delivery drivers a reliable image. 24 ׉ 7cassandra://CeGZIsCKeJA938jAptr8C8P6aHmMyDLb4p66Tyz5nnEW`hn**L:a/_)H׉E4Overview of the occupancy of loading bays is part of curb management. Free sidewalks and curbs are becoming scarce due to the rise of delivery services, shared mobility, and charging stations. But sensors and other sources of data can tell us how curbs are being used. This data forms the basis for digital control, but can also be connected to law enforcement agencies for targeted law enforcement. Curb management and other applications of Smart Urban Traffic Zones are likely to play a greater role in the future. Smart application and connection of sensors, vehicle information, GPS data, DRIPs, and TLCs will allow cities to establish ever more effective control over the way the road and the public space are used. Smart measures for livability and accessibility The technology of Smart Urban Traffic Zones (or smart access) can be used for a variety of purposes, allowing cities to take targeted measures to improve livability and accessibility. To give a few examples: Environmental zones and emissions control Smart zones can identify high-emission vehicles and limit their access or impose charges. Geofencing for security and mobility management Cities can close off zones to heavy traffic. Only trucks that have temporary permits are allowed in. The permitted route is communicated digitally. Freight traffic on bus lanes Bus lanes can be automatically made accessible to freight traffic whenever they are not in use by buses. Priority for electric vehicles EVs are given automatic access to specific lanes or parking places in emission-free zones. The further development of our traffic management platform MobiMaestro will support curb management and other forms of smart access. As the example from Gothenburg shows, even having greater insight is a step forward that can make life easier for delivery drivers such as Olle. A next step could be to give the city greater control, for example by reserving loading bays or implementing dynamic use of them. These and other forms of Smart Urban Traffic Zones are giving cities a handle on the configuration and use of the public space. 25 ׉ 7cassandra://ec9H79SlYB7UQOfxQ2dTt4_uEOneYL8MjV2D-0dJ6jw#`hn**L:a/_)Ihn**L:a/_)H+בCט+u׉׉ 7cassandra://-MCCDfs4qDQtaHc34vhZlN29_fw6gAu3BBZ97HSPpgEb`׉ 7cassandra://PBguuFW5dofAMhnBLxfeiITnEMzgC2BRVL7poJ09XzgR`h׉ 7cassandra://WPMXuWqQKyzRXr57x5OQSzGkR1JNWMDfRxCmRxS0zmA>`hn*2L:a/_)ט+u׉׉ 7cassandra://Jx6gn-xKtc6lcpsSEPUdltb2fuQi4PwnHLtW4uXoy0c4`׉ 7cassandra://PW1MmH3cMKoriA8lj4b8E5cUoU84OpDvWFcO5mUvFEwc`h׉ 7cassandra://1f0z7efwMJiuy1h73BdXtJ3TbXiaBcPaMmCl-W-T4zw!`hn*2L:a/_)נhn*1L:a/_)r?ށ9׉Hhttps://www.technolution.com/Gׁ ׁ rנhn*1L:a/_)zE9׉H"https://www.technolution.com/move/Gׁ ׁ rנhn*1L:a/_)LE9׉H$https://www.technolution.com/performGׁ ׁ rנhn*1L:a/_)z8E9׉H"https://www.technolution.com/primeGׁ ׁ rנhn*1L:a/_)L8E9׉H"https://www.technolution.com/sparkGׁ ׁ rנhn*1L:a/_)zE9׉H$https://www.technolution.com/advanceGׁ ׁ rנhn*1L:a/_)Á̉y&9׉H$https://www.technolution.com/move/nlGׁ ׁ rנhn*1L:a/_)ā̉Gy&9׉H%https://www.technolution.com/prime/nlGׁ ׁ rנhn*1L:a/_)ŁYGy&9׉H%https://www.technolution.com/spark/nlGׁ ׁ rנhn*1L:a/_)Ɓ̉y&9׉H'https://www.technolution.com/advance/nlGׁ ׁ rנhn*1L:a/_)ǁYy&9׉H'https://www.technolution.com/perform/nlGׁ ׁ rנhn*1L:a/_)ȁpD9׉Hhttps://studiopiraat.nl/Gׁ ׁ rנhn*1L:a/_)Ɂ}9׉H'mailto:move%40technolution.com?subject=Gׁ ׁ rנhn*1L:a/_)ʁ{9׉H%https://www.technolution.com/move/nl/Gׁ ׁ rנhn*1L:a/_)ˁ{̢9׉H3https://www.linkedin.com/showcase/technolution-moveGׁ ׁ rנhn*1L:a/_)́&!9׉SG ׁ ׁ rנhn*2L:a/_)Ӂ̤ 9ׁHhttp://technolution.com/moveׁ ׁ Јנhn*2L:a/_)ҁ̩9ׁHmailto:move@technolution.comׁ ׁ Ј׉EgFounded 1987 Technology company Multi-disciplinary – software, electronics and programmable logic Solutions that matter Reliable technology Thinking differently € NL 300 Motivated employees 8,4 Employee satisfaction 8,2 Customer satisfaction 75 mln. Revenue 10-15% Of revenue R&D 28th In Dutch Top 30 R&D Locations Technolution - Gouda Technolution Deventer - Deventer Phase to Phase - Arnhem Technolution Nordics - Stockholm (Sweden) TNL USA Inc. & TNL Nanotech Inc. - Wilmington Sub-brands Certifications ISO 9001 Quality ISO 27001 Information security ISO 14001 Environment CO2 Performance Ladder level 5 26 ׉ 7cassandra://WPMXuWqQKyzRXr57x5OQSzGkR1JNWMDfRxCmRxS0zmA>`hn**L:a/_)Z׉ETechnolution Burgemeester Jamessingel 1 2803 WV Gouda Nederland colofon © Technolution 2025 photography Masja Stolk, Gouda design, layout and realization Studio Piraat, The Hague +31 (0)182 59 40 00 move@technolution.com technolution.com/move Technolution­move ׉ 7cassandra://1f0z7efwMJiuy1h73BdXtJ3TbXiaBcPaMmCl-W-T4zw!`hn**L:a/_)[hn**L:a/_)Z+בCט+u׉׉ 7cassandra://BVnmLOdBXoPlPXvUchOjZYIkH3Watz8R3Q7WnAUqo08`׉ 7cassandra://Nme1CwDF1tt2MNqHmC4ZDC71jEHLyL1m3FlTkZfthUwU`h׉ 7cassandra://6GcH2TTOWqgouFBgA3c42rFv8ZiwMl41mYeDv-Chm7E`hn*2L:a/_)Ԓנhn*2L:a/_)Ё ̤9׉H!https://www.technolution.com/moveGׁ ׁ rנhn*2L:a/_)с;9׉H3https://www.linkedin.com/showcase/technolution-moveGׁ ׁ r׉E(Follow us on LinkedIn technolution-move ׉ 7cassandra://6GcH2TTOWqgouFBgA3c42rFv8ZiwMl41mYeDv-Chm7E`hn**L:a/_)^׈Ehn**L:a/_)_hn**L:a/_)^+)ׁ2ׁ>m}ׁ3ҋ+Technolution Move - MoveOn magazine 2025 ENhn*)8Q,$UR