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TRAFFIC


Vision algorithms


take control of traffic


Greg Blackman explores the vision and AI technology transforming our roads, as the transport sector gathers for the Intertraffic Amsterdam trade fair


A


msterdam is building its smart credentials. Te city’s government is working with businesses in the


Zuidas commercial district to create a mobility-as-a-service app due to be released later this year. Te idea is to encourage commuters to leave their cars behind and use alternative modes of transport, made easier by the app. Te ultimate goal is that, by 2025, all of Amsterdam will have reliable, affordable and accessible modes of shared transport. Mobility-as-a-service (MaaS) is one of


the big trends at the Intertraffic Amsterdam show, from 21 to 24 April. Te model is a shift from people relying on their own vehicles to one where transport is provided as a service. It relies on data, another trend topic at Intertraffic, and real-time data is something vision systems can provide. As part of the Intertraffic conference programme, under the theme of big data,


representatives from Swisstraffic, Viscando, and Flir will give presentations about controlling traffic with vision and AI. Speaking to Imaging and Machine


Vision Europe, Viscando’s CEO, Amritpal Singh, said it wants to use the potential of computer vision and AI to bring objective and quantitative information to cities. Singh will be speaking on 22 April at Intertraffic’s theatre two at 4pm. Viscando’s stereovision technology is used for monitoring traffic, but also to control traffic. Te firm’s vision system can track traffic moving through a road intersection, or any open area, such as a shared space or the cargo bay of a logistics company. Te system is able to detect and track


all kinds of motorised vehicle, along with bicycles and pedestrians, simultaneously. It can do this at 20Hz. ‘We get plenty of detailed data on how road users move through an intersection,’


16 IMAGING AND MACHINE VISION EUROPE FEBRUARY/MARCH 2020


Singh explained. ‘We can analyse the trajectories of road users and look at how people behave, at traffic signals for instance, or analyse conflict risk and measure the gaps people leave between vehicles.’ Te camera generates a lot of detail about


behaviour and interactions between road users, and its impact on traffic safety. Te longer-term goal, according to Singh, is to use machine learning to predict the traffic needs of road intersections and connect intersections with each other. Viscando has two ongoing pilot projects in Sweden investigating this, and started a pilot in Norway this month (February). ‘Tere are a lot of possibilities to have a complete picture of how the intersection is working and providing data for optimising it,’ Singh said. Te pilot project in Stockholm, called


the Multisensor project, is using the system to control the traffic. Tis is a live trial conducted together with the city. Te


@imveurope | www.imveurope.com


Protasov AN/Shutterstock.com


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