International Transportation (67) 1 | 2015 37 Smart Traic PRODUCTS & SOLUTIONS Standards-based Smart Traic solution from Shared-E-Fleet How vehicle sensor data can be captured and made available-for improved traic analysis, environmental monitoring and urban planning. Traic analysis, environmental monitoring, intelligent traic solutions, urban planning Vehicles today are equipped with many diferent sensors that enable them to have a good awareness of their surroundings. Some sensors capture vehicle-speciic data, including acceleration, rounds per minute or fuel consumption. In addition to vehicle positioning, other modern sensors measure environmental data such as temperature, rain or light intensity. Typically, these sensors have a purpose related to vehicle operation, providing data for driver assistance systems, among others. The light sensor, for instance, controls headlight dipping and the rain sensor controls activation of the windshield wipers, while the acceleration sensors allow selective braking of individual wheels for enhanced vehicle stability. Authors: Andreas Ziller, Arne Bröring W ith Smart Traic as part of the Shared-E-Fleet project, we have developed an approach that goes beyond this local use of sensor data. Our vision is that in future vehicles will serve as mobile sensor platforms contributing data securely and anonymously to a global data pool where data can be made available to various applications. This approach goes beyond existing solutions such as BMW Connected Drive or Tomtom HD Traic, for example, by making data available to external applications too, using a standardized gateway. Vehicle sensor data can be queried via the vehicle bus, enabling this data to be read, uploaded and used for new applications. Smart Traic can make the data from vehicle sensors available not only to the driver of the vehicle on which the sensors are mounted, but also to all other road users. Large-scale collection and analysis of sensor data from a large number of vehicles can thus enable a whole array of new applications. These are not restricted to traic applications. The sensors can be used, for example, to capture the automobile’s local surroundings. The rain sensor tells us if it is raining; combined with the data from outside temperature sensor this information also indicates whether it may actually be snowing or if there is a risk of black ice. The acceleration sensors on the wheels provide information as to whether the road surface is in fact icy. The video cameras installed on the vehicle can be used in future to ascertain more complex interrelationships such as the condition of the road (snow, potholes). The many sensors in vehicles will open up far-ranging opportunities for intelligent systems that go well beyond the capabilities of today’s traic management and traic control systems. In current practice, both stationary and mobile devices are used to capture traic data. Stationary devices mounted above or alongside the roadway are not evenly distributed, nor do they provide a reliable picture of the traic situation. The advantage of a mobile distributed network of sensors compared to conventional dedicated sensor networks is that it does not require any ixed installations. Large numbers of vehicles and high road saturation levels create a very dense data network. Coverage is further increased by the element of mobility. On the vehicle side, this requires only a processing unit connected to the vehicle bus. Such components are already present in the vehicle for other purposes (entertainment, navigation etc.). Power supply, polling intervals and processing capacity present no problem for vehiclebased sensor systems, unlike ixed-installation sensor networks. Vehicles provide suficient capacity for this. And wireless connectivity solves the issue of accessibility and data transmission. Typical applications Potential applications for such sensor data captured by vehicles are many and varied. Here we briely outline some typical applications: Improved traic safety thanks to weatherdependent route planning If data captured by the sensors for outside temperature and rain or by the windshield wiper controllers already present in automobiles today is collected and then logically combined, the resulting aggregated data can help to determine the current weather situation. This makes it possible, among other things, to infer from the fact that it is both cold and raining that there is a risk of ice on certain stretches. Using information from a large number of vehicles provides a good overall picture. Vehicles on the road can be warned of ice or can in fact altogether avoid areas at risk. Environmental monitoring Data provided by vehicle sensors can be used in analyses to support environmental monitoring models, for example. One potential such application is regional emission monitoring (CO 2 and particulates), using the air quality sensor in the cars’ recirculation control unit for instance. International Transportation (67) 1 | 2015 38 PRODUCTS & SOLUTIONS Smart Traic Traic optimization For inner city traic management, using vehicles as additional data sources enables more precise monitoring and management of events in a city’s traic network. Motion analysis, for instance, allows the early detection of congestion. Monitoring of the parking situation A more ambitious target for future applications could be for vehicles to use video cameras to detect on-street parking spaces. The idea here is to use image processing to identify free parking spaces locally and only send information on the location of those free spaces to the control center. There the data will be processed and evaluated using a probability model and can then be made available to various applications. Of course, this procedure is not really precise as free parking spaces may quickly be occupied again. But if the purpose is simply to get a quick overview, potentially promising locations could be highlighted in a map view of the navigation system, allowing the driver to narrow down the search for a parking space. System design To enable the added-value services and applications described above, we have developed an innovative Smart Traic tool in the scope of the Shared-E-Fleet consortium project. The basic principle of the provision of Smart Traic Services for user apps is shown in igure 1. The Smart Traic On-Board Unit is an embedded Linux system that is used in the vehicle to read and then forward a range of sensor data to the Smart Traic System. The Smart Traic platform uses Webservices to collect the data and then make it available to other users. Smart Traic Services provide standardized interfaces and protocols to make the data available in an interoperable format. This facilitates interaction with other services. For example, the data provided is used by the route query system developed in Shared-E-Fleet to support route selection. This allows drivers to avoid routes with a high volume of traic or hazardous weather conditions such as ice on the road. In the background, the registration and search process for these value-added services is supported by the Marketplace. This is where providers can make their services available to other users. Services are described using a speciic vocabulary while appropriate quality dimensions (pricing, accuracy, reputation) permit comparability. An important aspect of Smart Traic Services is their compliance with internationally accepted standards. They follow the proven standards of the Sensor Web Enablement (SWE) initiative [1] issued by the Open Geospatial Consortium 1 (OGC). The three main web service types are: (1) the Sensor Observation Service, (2) the Sensor Event Service and (3) the Sensor Planning Service. These services are shown in the architecture overview (see igure 2). The data captured by the Smart Traic On-Board Unit is uploaded to the Sensor Observation Service [2]. From there, these resources can be searched in standardized formats, including the application of thematic, temporal and spatial ilters. The Observations & Measurements Standard [3] is used for sensor data, and the SensorML Standard [4] for metadata. The raw sensor data is further processed by the Data Analytics component. A mapping service allows to visualize the data in maps. The Smart Traic Service makes it Figure 1: Basic principle of processing car data in order to enable Smart Traic Services Figure 2: System setup of the Smart Traic System including platform, on-board unit and user-apps International Transportation (67) 1 | 2015 39 Smart Traic PRODUCTS & SOLUTIONS available for client applications. To inform users about events, sensor data is regularly processed and forwarded to the Sensor Event Service. In addition, the Sensor Planning Service [5] allows remote coniguration of the Smart Traic On-Board Unit. The sensor data aggregated by the Smart Traic platform is the dynamic basis of the route query system (not shown in igure 2), which is responsible for calculating routes (or route options). As well as considering static costs (e.g. distance), it adapts dynamically to the current conditions in the traic network. Trajectory analysis is used to generate and reine statistical prediction models (e.g. energy consumption). It is also desirable that real-time data (e.g. traic low) is factored directly into routing queries. Via Smart Traic applications running on a smartphone or a tablet PC, the traveling user can access the services delivered by the Smart Traic platform and thus beneit indirectly from the data collected previously. The user interface to the Smart Trafic platform is provided by the Smart Traic App, a smartphone application for iOS (igure 3). The app ofers a navigation solution that relies on Smart Traic Services. In the event of an incident, the app is notiied and calculates a new route using the Shared E-Fleet route query system (see igure 4). Conclusions and outlook The solutions described here make it possible to expand existing traic monitoring and control mechanisms. The core idea of the approach presented here is the largescale collection of the diferent data that the- sensors deployed in modern vehicles capture already today. This approach can give rise to a large number of novel services and applications. New applications in turn will lead to more intelligent traic monitoring and control, for example, or can be used- for environmental monitoring or to improve traic planning. In future, the growing number of assistance systems will lead to a further increase in the number of sensors deployed in vehicles. This will allow the continuous development of new applications and the generation of added value for the Smart Traic approach described here. ■ 1 http: / / opengeospatial.org REFERENCES [1] Bröring, A., J. Echterhof, S. Jirka, I. Simonis, Everding, C. Stasch, S. Liang, & R. Lemmens (2011): New Generation Sensor Web Enablement. Sensors, 11 (3), pp. 2652-2699. [2] Bröring, A., C. Stasch & J. Echterhof (2012): Sensor Observation Service Interface Standard, Version 2.0. Open Geospatial Consortium. OGC 12-006. [3] Cox, S. (2010): Observations and Measurements - XML Implementation, Version 2.0. Open Geospatial Consortium. OGC 10-025r1. [4] Botts, M. (2013): OGC SensorML: Model and XML Encoding Standard, Version 2.0. Open Geospatial Consortium. OGC 12-000. [5] Robin, A. (2010): OGC® Sensor Planning Service Implementation Standard, Version 2.0. Open Geospatial Consortium. OGC 09-000. Andreas Ziller Siemens AG, Munich (DE) andreas.ziller@siemens.com Arne Bröring, Dr. Siemens AG, Munich (DE) arne.broering@siemens.com Figure 3: Screenshot of the Smart Traic App Figure 4: Screenshot of Smart Traic Web View