ChargeNOW
Location sharing
Share location with other users
myTaxi
Traffic information
Provide information on the current traffic situation
Intrix Traffic
Parking information
Provide information on parking lots
Parknav
Matching
Match demand and supply
BlaBlaCar
An analysis of which service modules are included in which digital mobility service is shown in Fig. 43.1. Some service modules are integrated in most of the services. The map view, for example, is the most basic module and therefore integrated in almost all mobility services. Another important module is the routing module, which is integrated in navigation services and trip planners.
Fig. 43.1Service modules of digital mobility services
Some service modules are not yet integrated in many services although they might offer an additional benefit. The module that enables location sharing, for example, is mostly used in smart logistics services and car and ride sharing services. However, also trip planners or parking services could benefit from location sharing as it might be useful for users to know when a public transport vehicle is arriving or when a parking spot is left by another user. The matching module, as another example, is specific to services that match supply and demand and is therefore mainly integrated in car and ride sharing services or smart logistics services that match free capacities with delivery requests.
Table 43.3 presents an overview of the data sources that we identified. Most services are based on more than one data source. Especially navigation services and trip planners integrate data from private and public sources and enhance the data via sensor and crowdsourced data. Data from public transportation providers and from public administration is not yet integrated throughout the categories of digital mobility services. An analysis of which service modules are included in which digital mobility service is shown in Fig. 43.2. Table 43.3Data Sources of Digital Mobility Services
Data source
Provided data
Google
Map, routing and traffic information
Device sensors
User location
Crowdsourced data
Data aggregated across users
Other private providers
Solution‐specific data
Public transportation providers
Time tables, information on delays and incidents
Public administration
E. g. traffic situation, usage of public parking decks
Fig. 43.2Data sources of digital mobility services
Our analysis provides an overview of existing mobility services showing that there is a large number of different services that need to be combined by the users in order to fulfill their individual needs. Users need to switch between apps and providers since most of the services are not integrated.
However, in this chapter we have shown that services can be structured based on their modules and data sources. We have also shown that a lot of distinct services use similar modules and data sources which suggests that there is a lot of potential for reusing certain components. This serves as further motivation and guidance for the development of an open platform for digital mobility services which facilitates the development of new services by providing reusable modules and services and pre‐structured data. In the next chapter, we will outline our architectural concept for such a platform.
43.3 Architectural Concept of an Open Platform for Digital Mobility Services
We will first further define the requirements for our platform based on the findings of our analysis in the preceding chapter. The platform should offer several modular mobility services with different levels of granularity. These services should access different data sources and refine their information. All services should be hosted in a secure and safe environment. As many of these mobility services are quite computation intensive, the platform needs to be able to handle sufficient parallel service calls. Additionally, each user should be identifiable by the platform. Furthermore, the platform should support developers that contribute services to the platform’s ecosystem by providing access to raw or analyzed data, analysis tools and specifications on how to develop the services according to the platforms standards. The resources on the platform should be standardized so that similar datasets from different sources can be presented and interpreted in a similar way. The platform should provide a web‐based interface which allows browsing through the different resources by providing user credentials. The proposed platform should furthermore support cooperation between the public and the private sector. They can create consortia or public‐private partnerships and define who will operate the platform.
Fig. 43.3 shows the concept for the architecture of an open platform for digital mobility services. It consists of the following elements and layers which we will now explain in further detail.
Fig. 43.3Concept for the architecture of an open platform for digital mobility services
Data Sources
The platform is based on several different data sets, for example floating car data or parking lot data. This data could be gathered through on board units within cars or through sensors in parking garages or on the streets. Additionally, data from public transportation providers and taxi corporations such as time tables or the positions of currently available cars could also be an important addition to the set of data sources.
Layers of Modular Services
Modular services represent the core of the platform. They can be structured into several layers where the level of granularity increases from the top to the bottom. Services at the bottom focus on analyzing and refining the data sources, whereas services on higher levels reuse the services from lower levels and integrate them using their results. Services that will be used by end users can be found on the highest level. Fig. 43.4 illustrates these different levels and shows several example services which we will now explain in further detail. Parking situation The parking situation service shows the current availability of parking spaces. It is based on data provided by the parking garages, sensors, or the crowd.
Prediction of parking situation This service predicts the parking situation for a certain point of time in the future. It is based on the parking situation service and the traffic information service. This service processes the provided data with machine learning algorithms. Additionally, it is possible that this service also accesses other information such as weather data.
Traffic situation The traffic information service collects the traffic data from different sources like floating car data, road sensors and road alerts. Then, it combines this data and estimates the current traffic situation.
Prediction of traffic situation This service predicts the traffic situation for a certain point of time in the future. It is based on the traffic situation service and on other data sources such as weather data. This service processes the data with machine learning algorithms.
Routing The routing service calculates the best route between two points. The user can specify whether the current traffic situation or the predicted traffic situation for a certain point of time in the future should be considered.
Public transportation information This service shows current and future time tables of trains, subways and buses. It also provides information about any failures or unforeseen situations.
Public transportation navigator The public transportation navigator service suggests the best public transportation route between two points for a certain point of time. It is based on the public transportation information service.
Multimodal navigator This service offers the optimal route within the city for car drivers. It considers the traffic situation for selecting the optimal route, but als
o checks where it is possible to find a parking space at the destination. Additionally, it checks whether it is better to park the car near a bus station and to use public transportation. This service is supposed to be used by end‐users and is based on the previously described modular services.
Fig. 43.4Layer of modular services with example services
Integration Layer
The integration layer creates a secure and safe environment. Services can only be accessed through the integration layer which buffers service calls and acts as a load balancer. User management and access control also reside in this layer. Since all service calls have to pass this layer, it can also be used for analyzing service calls.
Solutions
Developers who are using the platform can use the service to create new mobility solutions. These solutions could be solutions targeted to end‐users or they could be integrated into services outside of the platform. An example for a possible solution is a scheduling and routing service for small and medium‐sized businesses with multiple appointments within one or several cities. By considering the routes between the appointments and the predicted traffic situation at that point in time, appointment scheduling can be optimized. For example, a nursing service could optimize its daily schedule using this solution and save driving time that could be dedicated to the patient care instead.
43.4 Discussion
Our architectural concept for an open platform for digital mobility services can be used to make data of smart cities available, such as data on public transportation, parking spaces and traffic situation. Such a platform creates a mobility ecosystem and fosters the development of innovative mobility solutions based on the provided modular services. Without it, each developer has to gather data on his own, which is difficult if at all possible.
In this context, another challenge arises: Due to the highly dynamic nature of the platform, caused by the different stakeholders and participants, extensive control, also known as platform governance is required as a precondition for further success of the platform [14]. For example, the data that is aggregated from different sources and then made public by our platform could be used by other developers to strengthen their own competitive position vis‐à‐vis the platform owner [15]. The platform’s standards and interfaces should be carefully examined in order to control the data flow and to avoid misuse. Although effective governance is crucial for the success of a platform, many operators still struggle with designing and implementing a suitable governance concept. The work of Hein et al. [16] and Manner et al. [17] analyses different governance mechanisms and proposes core principles for the governance of mobile platforms. Their findings can give guidance for the design and implementation of a governance concept for our proposed platform.
The example services in the previous section demonstrate and clarify different layers of services. Each service can be offered to the end‐user individually, but it is also possible for external developers to combine them to offer new services.
Data related to mobility is of a highly sensitive nature and requires special mechanism for preserving privacy [18]. Methods for preserving privacy while storing and managing mobility‐related data are presented as an alternative to a trusted authority by Sucasas et al. [19]. Based on these findings, we suggest to give users as much control as possible by providing standardized processes for setting privacy requirements in order to ensure privacy and transparency in the provided services. For example, tracking data is anonymized and assigned to a regularly changing identifier. Data set owners can then see and track the use of their data.
Our proposed concept is subject to a few limitations. As of now, the architecture of the service platform has not been evaluated. Additionally, only a few exemplary services have been presented. For mobility solution providers, a comprehensive list of services would be more useful. In future research, the remaining steps of the methodology framework by Dörbecker and Böhmann [9], such as implementation and validation, could be applied to our findings. The architectural concept and a concrete implementation could be evaluated by using qualitative and quantitative approaches such as expert interviews and surveys.
Our findings contribute to both theory and practice. As for theoretical implications, our results give guidance on potential future research on service platforms, especially in the context of mobility‐related applications. Additionally, they show how the framework of Dörbecker and Böhmann [9] can be applied for the modularization of service systems as presented in our analysis on existing mobility services.
As for practical implications, our concept presents a way of making already existing mobility‐related data available for mobility solution developers by fulfilling several requirements related to safety, privacy and governance mechanisms. The proposed platform can be used for the creation of integrated and innovative services and identifying further potential among data source providers for collaboration and synergies. Furthermore, existing systems for urban transportation can benefit from the platform by using offered services to enhance their own solutions and in turn provide new data to the platform, thus further fostering co‐creation and innovation.
43.5 Conclusion
Individual mobility is heavily impacted by digital mobility services. Therefore, research on digital mobility services can contribute to the efforts of companies and policy makers to make transportation more sustainable. We analyzed existing mobility services with regard to their modules and data sources. We showed that some modules and data sources are integrated throughout almost all categories while others are only available in highly specialized solutions. Our analysis shows that there is a large number of different services that need to be combined by the users in order to fulfill their individual needs.
In order to ease development of new, integrated mobility solutions, we designed an architectural concept for an open and modular digital mobility services platform. The platform supports the development of solutions by providing mobility data and services through open and standardized interfaces. A broad variety of services at different levels of complexity is offered by the platform which encourages reuse of existing service. Developers can find and pick the services that best fit their needs and goals.
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