![]() ![]() In this sense, SUMO includes capabilities for re-routing vehicles dynamically. If vehicles are equipped with a re-routing device, they can change their current routes, taking into account the road network’s current state. This behavior is emulated in SUMO utilizing an additional feature, called re-routing device. In this context, most drivers are familiarized with the road network and, therefore, can decide to try an alternative path during their trips. Besides, drivers can be informed through the vehicular network about the road network’s events during their trips. Most modern vehicles are equipped with real-time navigation services allowing drivers to better use the available road capacity. SUMO is an open-source space-continuous road traffic simulator commonly used for testing vehicular networks and ITS applications. In this regard, a wide-spread road traffic simulator is Simulation of Urban MObility (SUMO) . Regarding this last, we can differentiate two main groups: (i) vehicles’ traces defined by hand, mostly used when evaluating simple map topologies (e.g., highway, Manhattan) and (ii) vehicles’ traces defined using traffic demand generation tools , used with large size maps or complex topologies (e.g., city map). The main elements in order to generate the traffic simulation are (i) the network data consisting on roads and intersections, a.k.a edges and junctions (ii) traffic infrastructure containing traffic lights elements and logic (iii) vehicles’ type consisting on a description of vehicle’s characteristics (e.g., gas/diesel, passenger/bus) and (iv) vehicles’ traces that vehicles will follow during the simulation (e.g., routes, trips, flows). In this context, jointly considering realistic mobility models and traffic demand generation are keys to obtain accurate results when evaluating vehicular networks. Hereabouts, wireless system researchers put their effort into the network modeling without considering the effect of the traffic during the simulation. Here, realistic mobility models allows simulators to interact with obstacles along the route, traffic/weather conditions, and drivers behavior. Traffic simulators implement the traffic-related elements (e.g., road network, traffic demand, mobility models) (e.g., VISSIM, MATSim, SUMO, TranSims). Network simulators implement the stack of protocols for vehicular communications (e.g., Veins following the IEEE WAVE specification, Artery following the ETSI ITS-G5 specification). In this regard, the simulation of vehicular communications usually involves the coupling of a network simulator and a traffic simulator. Particularly, while the deployment of real test scenarios is feasible in most cases (e.g., sensor networks), simulation techniques are commonly used to evaluate vehicular networks and new emerging services for intelligent transportation systems (ITS). Nowadays, simulation is the main approach that researchers follow to assess the performance of wireless networks. Additionally, we propose an automatized tool that facilitates researchers the generation of synthetic traffic based on real data. Our results provide insights into the behavior of the vehicle’s mobility and the nodes’ connectivity of SUMO demand generation tools. Lastly, we analyze the node’s connectivity using well-known graph metrics. Then, we analyze the available tools in terms of resources usage (CPU, RAM, disk). This last feature allow cars to re-compute their routes in front of congestion situations. Using the data traffic in the district of Gracia in Barcelona (Spain), we analyze the generated traffic demand in terms of traffic measures: (i) traffic intensity, (ii) trip time/distance, (iii) emissions, and (iv) re-routing capabilities. This paper provides a thorough analysis of the influence of using the different SUMO’s traffic demand generation tools on mobility and node connectivity. In this context, vehicular traces affect vehicles’ signal strengths, radio interference, and channel occupancy. When assessing VANETs, it is crucial to use realistic mobility models and traffic demand to produce meaningful results. Mainly, vehicular ad hoc networks (VANETs) are a particular type of mobile ad hoc networks that raise specific technical challenges. Simulations are the traditional approach used by the research community to evaluate mobile ad hoc networks. ![]()
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