Second Tier: Micro Simulation of Realistic Urban Mobility in the Target Urban Scenario

The second tier is developed around an evolution of the Simulator of Urban Mobility (SUMO 2016). We customized the simulator to also simulate electric mobility, that is, the discharging process of EVs as a function of vehicle characteristics and the simulated driving cycle in a realistic traffic scenario. The simulation is performed on a micro scale, that is, the simulator reproduces the movement of each single vehicle from a source to a destination zone of a real map. The simulator leverages an appropriate model that describes the behavior of individual drivers to simulate the reaction of a driver to a surrounding environment in terms of acceleration, deceleration, and lane changing.

All the details about the complex procedure to make this kind of simulation possible are described by Bedogni et al. (2015). Several data sets are needed to perform it. The first input is the topology of the urban road network, representing the transport supply. In SUMO, the road network is a directed graph composed of nodes indicating the position of intersections and edges representing the road infrastructure. In addition to this basic structure, the network contains further traffic-related information such as the number of lanes of each edge, the shape and speed limit of every lane, the right-of-way regulations, the connections between lanes at junctions, and the position and logic of the traffic lights. Road networks with related information can be imported to the simulator from different sources such as OpenStreetMap (OSM 2016), a crowd-sourced platform that creates and makes available to everyone free geographic data for cities worldwide.

The second input required is the traffic demand; it is commonly stored in an origin- destination matrix that describes the traffic intensity between the source-destination couple available in the urban scenario. An adequate traffic assignment technique defines the choice and volume of the route to get from the origin zone to the destination zone. The third input is the characteristics of EVs such as mass, weight, friction factor, and battery pack, to correctly simulate the discharging process.

The second tier is therefore able to simulate, in realistic traffic conditions, the state of charge (SoC) of the share of EVs (input from the first tier) in order to direct them to a charging station when necessary and to calculate the SoC when they reach the destination. This precise information is the input to the third tier of the DSS to assess the energy demand due to electric mobility. It is worth noting that the simulator traces any charging event by considering the time and geo-localization of the request.

 
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