Abstract: The mobility landscape is undergoing significant changes. More and more mobility providers compete for customers with their own mobility services. Traditional public transport, demand responsive transport, taxis, car sharing, ride pooling, bike sharing, e-scooters, … the available modes of transport in cities are becoming increasingly heterogeneous and confusing. At the same time, significant changes to the landscape are induced by the effects of the global pandemic. They may lead to even more drastic changes in the mobility demand.

How to tame the complexity of this landscape and fight the climate change without neglecting mobility as a fundamental human need is an open - albeit essential - question.

In this talk, we will examine the changes in the mobility landscape and look at the role of two important players in this discussion: open simulators and artificial intelligence. What do they bring to the table in order to tackle the rising complexity? How can they be applied to improve the transportation system in a city? The Eclipse SUMO project is used as an example to illustrate how to build digital twins of smart cities. Moreover, results from recent research projects are used to discuss the effectiveness and efficiency of applying artificial intelligence to optimize transportation systems.

Authors: Junhyung Ki, Sebastian Schildt, Andreas Hastall, Sven Erik Jeroschewski and Robert Höttger

Abstract: Modern internal combustion engines have several advanced exhaust treatment systems to meet emission standards and legislation. In case of Selective Catalytic Reduction (SCR) for diesel engines, a catalyst (“AdBlue®”) is used as consumable. This incurs costs for the operator of diesel vehicles and provides an incentive to unlawfully circumvent and shut down those systems. This case study presents how the Eclipse KUKSA stack has been used to realize an anti-tampering system for commercial heavy-duty trucks exhaust systems. We show how the in-vehicle KUKSA.val software and the KUKSA.cloud components can be used to collect relevant data from a real heavy-duty truck and send them to the cloud for further analysis.

Authors: Harri Hirvonsalo and Pertti Seppänen

Abstract: In this study, we explored how the Eclipse Kuksa framework could be used as a technology basis for building an intelligent moving test platform to support research of autonomous vehicles and vehicle related research in general. Based on the gained experience, we state that Kuksa framework is a feasible basis for development of open, intelligent automotive data systems, though with a considerable learning needs. We present the experience gained during this study and demonstrate some of the functionality provided by a minimum-viable system we implemented in the study.

Authors: Mikael Saarinen and Niina Lundén

Abstract: Hono™ service stack deployment to Azure was a student project by the SMADYASP (Smart Autonomous Driving Yet Another Student Project) group, in which the goal was to create cloud infrastructure architecture for mobility applications. Microsoft Azure was used as the cloud platform, and deployment was done using Terraform, Helm, and Kubernetes. With the results of the project, it is now much easier to deploy Hono™ and monitor and trace the whole service stack. In the future, this project's results are used in setting up a test environment for real automotive scenarios concerning in-vehicle and 5G connectivity mobility applications.
Source: https://github.com/smaddis/smad-deploy-azure
Demo video: https://youtu.be/SF46X0i_hJU

Demo: Conference handout - not for distribution

Authors: Muralikrishna Thulasi Raman, Andreas Graf, Benedikt Niehues and Marco Aiello

Abstract: A major problem with vehicles used in densely populated areas is parking. Part of the problem is the scarcity of the resource in busy areas and the non optimal utilization of private spots. We propose the 'Smart Shared Private Parking' model that aims at including in the parking pool also private parking spots. In an urban area with both commercial and residential buildings, frequently household owners do not utilize their own parking lots during office hours, long duration of shopping and vacations. At the same time, such owners want to be able to park in their lots when needed. Therefore, to engage the residents and allow them to provide their parking spaces when unused one needs a real-time, distributed infrastructure that supports dynamic allocation of spaces. We propose a conceptual deployment of edge hardware and communication mechanisms to enable shared private parking sharing. We illustrate an infrastructure setup required to analyse various aspects of the model and show its effectiveness in parking allocation in terms of vehicular emission, utilisation rate, and revenue as metrics considering all the stakeholders. A simulation based on a district of Dublin provides quantitative instances for these metrics.

Authors: Philipp Heisig and Christoph Flick

Abstract: Future vehicles can be considered as ”IoT devices on wheels” as they exhibit high-performance computation resources, various sensing devices, and a data-driven software architecture. While the availability of automotive big data provides the basis for innovative and disruptive mobility services, processing vehicle data within the cloud poses also several challenges. A major challenge in this context is the validation of cloud-native mobility services regarding their proper functionality and the fulfillment of non-functional requirements. Due to the cost-efficient nature of simulations, traffic simulation in combination with network simulation is more and more used for a virtual proof-ofconcept of mobility services and their software architectures. Nevertheless, the creation of adequate simulation environments specific to connected vehicle scenarios is time-consuming and requires explicit domain knowledge. We present a prototypical domain-specific language tailored to the formal description of connected vehicle scenarios and the according generation of simulation environments. Therefore, we make use of the traffic simulator Eclipse SUMO as well as the co-simulation environment Eclipse MOSAIC and demonstrate the usage of our DSL via the use case of a restricted traffic zone. Although the DSL so far only support the setup of minimal traffic scenarios, it already helps to abstract complexity and ease the set-up of simulation environments for connected vehicle scenarios.

Authors: Alessandra Bagnato, Etienne Brosse and Kaïs Chaabouni

Abstract: The Morphemic H2020 project (The most advanced multicloud platform with proactive features) covers several features from modelling cross-cloud applications, continuous and autonomous optimization and deployment and providing access to several cloud capabilities. This demo paper describes the MORPHEMIC CAMEL Designer tool responsible for the Cloud Application Modelling and Execution Language (CAMEL) design for the modelling Environment Modelio. CAMEL Designer is an open source module for graphically creating, editing and exporting CAMEL Models in XMI format.