Detailed areal representations of street space are useful for a variety of different applications such as autonomous driving, driving simulators or emergency planning. In order to illustrate this claim the following section examines possible applications and describes how each one of them would benefit from detailed 3D areal street space models.
Infrastructure planning and management
Digital 3D city models can be the basis for land use management (Ross 2010). Besides settled areas the cityscape is mainly shaped by public traffic areas. Visual simulations of constructed areas as well as free space can be used in order to plan different scenarios and conduct effort and cost analysis. In this context, large construction projects such as new highway sections or bridges can be planned digitally. This can also be used to visualize the future look of these constructions and thus prevent resistance of the citizens. Many communities have a duty to fulfill their municipal obligations such as clearing streets of snow or leaves or taking care of sufficient street lighting. Planning these often very expensive tasks in order to find the most effective and economic practical implementation could be supported by detailed street space models. This also involves maintenance of streets and damage mapping. Areal street models combined with knowledge of pavement conditions can be used for assessments of expected repair costs. Kolbe et al. (2008) show how CityGML and sematic city models can be used for emergency planning. In this context, Rupprecht et al. (2011) describe ways to conduct simulations of pedestrian flows. Such simulations need the exact representation of navigable surfaces to identify bottle-necks.
Spatial analysis
Detailed street space models can be the foundation for a variety of spatial analysis methods. Local heat islands in largely sealed areas such as street intersections or plazas can be analyzed using information derived from areal street representations in combination with knowledge of solar irradiation. The optimal placement of street signs and traffic lights can be planned within city models and supported by visibility analysis. Ghassoun et al. (2014) show how city models can be useful for air quality analysis. Parameters such as number of intersecting streets, their respective width and angle between street arms can be derived from accurate street space models. In combination with other parts of a city model like buildings and vegetation highly accurate simulations can be conducted. Based on areal information of streets and footpaths clearance spaces can be easily modelled. These can be used to simulate a heavy-load transportation and identify problematic areas. While linear representations of streets are often sufficient for noise simulations, areal models can be used to visualize the results. Detailed street models with information on elevation can also be the foundation for water run-off simulations with high levels of detail. Another potential application for detailed street space models is the combination with information on utility networks.
Automotive related applications
Knowledge on the exact shape of street space objects can be of high use for autonomous driving applications. Strassenburg-Kleciak (2016) states that information on street edges can be used in order to increase driving safety. Connected vehicles in combination with data on length and width of certain street sections can be used to assist drivers with overtaking manoeuvres. Randt et al. (2007) describe how virtual 3D landscapes can be used for driving simulators and emergency driver training. Other automotive related simulations such as traffic simulations or driving dynamic simulations (see Butz et al. 2004) can also be supported by information derived from detailed street space models. Roads normally forbidden for automobiles but wide enough to be used by ambulances in emergency situations could be integrated into navigation systems. In this context knowledge on steps, curbs, etc. could be considered for barrier free route planning in order to assist persons with reduced mobility.
Digital city models and especially detailed areal representations of street space can be useful for a variety of different applications such as solar irradiation analysis, traffic simulations or land use management. The video below visualizes the results of a solar irradiation estimation for buildings and streets in central Manhattan. All surfaces are textured corresponding to irraditaion values (kWh per year), ranging from deep blue (low irradiation values) over green to red (high irradiation values). Different irradiation values (e.g. global, direct, diffuse, etc.) for each month of the year can be queried by clicking on specific building or street objects. To explore a corresponding Web Map Client Project click here.
Detailed information on the areal expansion of street and sidewalk surfaces in combination with vegetation and street furniture objects can be used for clearance space analysis as shown in the following image. In Germany for example the space up to 4,5 meter above road surfaces should be clear of any potential obstacles. For sidewalks this value is set at 2,5 meters. These spaces can easily be created once the exact surface geometry is available.
Using the Web Map Client Pro, extended analysis, potentially useful for (urban) land use management or city planning, can be performed. The city model presented contains a huge variety of semantic information such as street names, number of driving lanes, street area in m2 or information on road surface conditions. These attributes can be queried in different combinations and thus be used for gaining additional information. The video below demonstrates possible applications. First, all traffic areas (roadbeds and intersections) belonging to 5th Avenue are selected. By summing up all corresponding 'area_sqm' values, the total traffic area in m2 of 5th Avenue is calculated. Then, making use of information on street pavement conditions (rated with 1-3 = BAD, 4-7 = FAIR, 8-10 = GOOD), all roadbed objects (of the entire city) with a street pavement rating of 5 (lowest existing value) are selected. By calculating the total area in m2 of the selected roadbed objects, assumptions on potential future repair costs can be made. (Fullscreen view recommended)
Currently, we are also working on using the NYC 3D street model to derive input datasets for the micro traffic simulation software VISSIM. The video below visualizes some results so far of a Master's Thesis by Roland Ruhdorfer. A paper on this project will be published later this year