Using Pledger to enable safe micromobility scenarios for smart cities


August Betzler, i2CAT

Estrela Carmona Cejudo, i2CAT

There are important challenges to face when implementing a sustainable and efficient micromobility in modern cities. Micromobility generally refers to personally driven, small vehicles operating at moderate speeds of 25 km/h or less. These vehicles, like bicycles or scooters, are nowadays often electric, which adds to the comfort of the driving experience and is a sustainable method of transportation (compared to cars). But it also increases the average velocity of such vehicles, no longer being allowed to circulate on pedestrian areas. When accidents happen, the increase in velocity plays an important role, given micromobility users are considered vulnerable road users (VRUs), i.e. users that in the event of a crash or accident may be seriously injured. Given the growing numbers of micromobility users, this type of transportation has become a key factor to be considered in infrastructure layout planning, but also in the rule- and lawmaking: Dedicated lanes on roads, prohibition to traverse pedestrian areas, speed limits, and compulsory helmet wearing are just some examples of adaptations made to enable a safe and sustainable use of micromobility in cities.

However, despite these adaptations, often the layout of streets and the traffic situation in specific locations of the city leave VRUs still exposed to dangers. For such cases, Information and Communication Technologies (ICT) can be the means to enable services that can add to the safety of VRUs. In Pledger’s Use Case 2, an ICT infrastructure is used, on top of which Pledger is deployed to host a risk detection and notification service. This service is capable of detecting risks for a specific scenario, where micromobility users and pedestrians are exposed to the risk of accidents, as pedestrians have to forcefully cross a bike lane whenever they need to enter or leave a public transport (tram). With the help of IEEE 802.11p-based on-board units and road side units, the VRUs and tram can be tracked by the service managed by Pledger, warning users to reduce their speed and be on alert whenever both micromobility and public transport users coincide at a tram station.


To assure that this service is always fully operational, given it is a safety application, different features provided by the Pledger platform are used. First of all, before deploying the use case, a dedicated network slice including computational and radio capacities, as well as the required network connection, would be reserved via Pledger from the available infrastructure that spreads across the city. To cover different parts of the city, one would select radio and computation resources in the areas that are to be covered to grant connectivity and edge compute capacity. Second, Pledger’s orchestrator does the lifecycle management of the virtualized risk detection and notification service. Crucial decisions, such as scaling or offloading of the service to assure its operability are taken based on the feedback provided by the decision support system: Based on the monitoring of application and infrastructure metrics, as agreed in a dedicated SLA for the risk detection and notification service, it can be tracked whether the service is performing as expected or not. If at any point an SLA is not met, e.g. when the number of users increases and the service starves on computation resources, actions are requested to the orchestrator to either increase resources allocated to the service, or to move the service to another compute node where enough resources are available. All of this is done, while considering preferred deployment locations for the application services, like being deployed at the edge. For this use case, the key factor is first that the service is always operational and second, that the delays between detecting a risk and notifying it are always as small as possible. Thanks to the aforementioned metrics monitoring and the dynamic decision making, both key objectives can be achieved. Figure 1 represents the average maximum delay achieved for the risk detection and notification system, for an increasing number of users, with and without using Pledger.

Beyond these optimizations, necessary to assure the best service quality and quality of experience for the VRUs, Pledger also offers the use of distributed ledger technologies (DLTs). During the execution of the use case, logs are generated storing information about events observed (e.g., risk situations detected) and also the traces of the VRUs connected to the use case application, always in an anonymized fashion. This information should only be accessible by trusted entities, which include the service provider itself, but also possible third parties. In this use case, the public transport services or agencies related to the implementation of micromobility in cities could be interested in the data for statistical purposes. Thanks to the DLT, access to the logs can be controlled securely and efficiently.

Overall, the different features provided by the Pledger platform are key to enhance the performance and the quality of service for this micromobility-oriented use case. The use case already has been validated in lab conditions and is to be evaluated on-street with real users and traffic conditions.


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