Helsinki's testbed for smart mobility.

The three-month case study pilot was carried out in collaboration between Drover AI, Voi Technology, Vianova, VTT and Mobility Lab Helsinki. Drover’s PathPilot solution was installed on 25 of Voi’s e-scooters. In the first phase, it collected data about the infrastructure the e-scooters ride on. The second phase of the pilot introduced audio signals related to rider behaviour (such as alerts when riding on pedestrian streets, parking).

The case study produced a white paper analyzing the observed rider behaviour. The results were promising. For example, riding e-scooters on sidewalks was reduced during the test period. Continuation of testing with an expanded time and scope might be considered. Read more about the results.

“From the images collected by the scooters, we obtained accurate information about, among other things, potholes on sidewalks, which can be a safety risk for road users. Additionally, several situations were observed where, for example, a parked car blocked access to the bicycle lane,” says Juho Kostiainen, Project Manager of Mobility Lab Helsinki.

The pilot with Marjetas Academy is one of the agile pilots selected in Oct 2022 (read more in Finnish) which aim to support the development of Helsinki’s cityinfra platform.

The pilot with Normiopaste is one of the agile pilots selected in Oct 2022 (read more in Finnish) which aim to support the development of Helsinki’s cityinfra platform.

In the pilot, xyzt.ai’s visual analytics platform is used for studying traffic flows and quality of data sets provided by GeoMobility. The objective is to better understand the quality and coverage of different data sets in the Helsinki area, and how they serve different needs and how they can be analyzed (e.g. routes, speeds and delays of traffic). For the companies, it provides a chance to build knowledge on regional data sources, challenges and needs.

The public summary report is available here as pdf.

The URBANE project is aimed at developing a replication and scale-up model for successfully replicating smart green last-mile delivery solutions. It will use a PI-inspired innovation framework and digital twins with real life pilots in different cities around Europe. The activities in Helsinki are focused on developing and testing sustainable and viable last mile delivery solutions, and particularly autonomous systems. The Helsinki pilot partners include LMAD (Last Mile Autonomous Delivery, operating an autonomous system), DB Schenker (as the logistics operator) and Soben/TwinswHeel (as a provider of the autonomous platform) with Forum Virium Helsinki managing the pilot with the support of Helsinki/Mobility Lab.

The project’s objective is to create an operating model for companies to convey last mile delivery information and details to drivers as open data. It will promote the operating conditions and improve cost efficiency of logistics operations, improve the service levels for the customers and reduce the environmental effects through optimization (e.g. reduced time spent looking for parking spots).

The data is stored and available in OpenStreetMap and for demonstration purposes an example application app.gatesolve.com was created. It visualises entrances and routes of last 50 meters to them. In addition to the navigation application, another (open source) application, Open Logistics Map (OLMAP), is available for collecting such data. 

A final report for the project can be found from Tieke’s web site here.