| Abstract |
Smart mobility has been introduced as an enabler on achieving lower accident rates, decreasing the urban footprint for parking, reducing gridlocks, improving air quality, and as well becoming a tool on achieving the development of sustainable cities. It can enable several transport modes such as shared transportation services, including public transportation and electric and hybrid electric vehicles, autonomous driving, safe and convenient multimodal travel, and efficient and optimized use of resources and roads. Another development related to smart mobility is increased complexity of vehicles, whose goals are improving control, comfort, and efficiency of driving. To achieve that purpose, vehicle monitors and manages its overall state and states of individual components. Each component is therefore data source, and acts as a sensor. And they could be combined with data coming from other sources, for example from surrounding vehicles and environment in order to enlarge the electronic horizon of vehicles, and thus to increase vehicle’s automated and autonomous driving features. An important feature used in vehicle autonomous driving is the “world model” that creates and maintains an observed model of the (external) reality, as perceived by the vehicle. Vehicle is using this world model as the base for making own decisions on actions that it will take. Gathering or exchanging data between number of data sources, each potentially providing data in different formats, using different communications technologies, would create very large and complex communication problem, effectively hampering data exchanges, and thereby limiting accuracy and reliability of world model. IoT platform(s) can help bridge this gap, and support the cooperative awareness concept, since data collected from different vehicle sensors and environment can be published on an IoT platform, and then data collected on IoT platform can then be distributed and shared to any vehicle or elements of infrastructure that needs to use it. This approach, with effectively hub-and-spoke architecture simplifies problem of many-to-many communication. Using the smart infrastructure and its integration with IoT platforms allows access to a much larger amount of data that extends the vehicle’s horizon. The data is associated with, e.g., traffic lights, hazard warnings, navigation, and pedestrians. This chapter presents IoT developments and architectures, data models and communications which can be used to improve and further enable ITS and autonomous driving. The chapter also presents number of ITS use cases like autonomous driving, platooning, automated valet parking (AVP), car rebalancing, etc., which are enabled by federation of IoT platforms. The chapter also covers legal issues related to privacy and security of data, and current legal aspects of it. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. |
