Abstract-Recently, many efforts have been made to develop more efficient Inter-Vehicle Communication (IVC) protocols for ondemand route planning according to observed traffic congestion or incidents, as well as for safety applications. Because practical experiments are often not feasible, simulation of network protocol behavior in Vehicular Ad Hoc Network (VANET) scenarios is strongly demanded for evaluating the applicability of developed network protocols. In this work, we discuss the need for bidirectional coupling of network simulation and road traffic microsimulation for evaluating IVC protocols. As the selection of a mobility model influences the outcome of simulations to a great extent, the use of a representative model is necessary for producing meaningful evaluation results. Based on these observations, we developed the hybrid simulation framework Veins (Vehicles in Network Simulation), composed of the network simulator OMNeT++ and the road traffic simulator SUMO. In a proof-of-concept study, we demonstrate its advantages and the need for bidirectionally coupled simulation based on the evaluation of two protocols for incident warning over VANETs. With our developed methodology, we can advance the state-of-the-art in performance evaluation of IVC and provide means to evaluate developed protocols more accurately.

Abstract-We present a realistic, yet computationally inexpensive simulation model for IEEE 802.11p radio shadowing in urban environments. Based on real world measurements using IEEE 802.11p/DSRC devices, we estimated the effect that buildings and other obstacles have on the radio communication between vehicles. Especially for evaluating safety applications in the field of Vehicular Ad Hoc Networks (VANETs), stochastic models are not sufficient for evaluating the radio communication in simulation. Motivated by similar work on WiFi measurements, we therefore created an empirical model for modeling buildings and their properties to accurately simulate the signal propagation. We validated our model using real world measurements in a city scenario for different types of obstacles. Our simulation results show a very high accuracy when compared with the measurement results, while only requiring a marginal overhead in terms of computational complexity.

The combination of batteries and supercapacitors is promising in electric vehicles context to minimize battery aging. Such a system needs an energy management strategy (EMS) that distributes energy in real-time for real driving cycles. Pontryagin's minimum principle (PMP) is widely used in adaptive forms to develop real-time optimization-based EMSs thanks to its analytical approach. This methodology leads to an off-line optimal solution which requires an extra adaptive mechanism for real-time applications. In this paper, a simplification of the PMP method is proposed to avoid the adaptation mechanism in real-time. This new EMS is compared to well-known conventional strategies by simulation. Furthermore, experimental results are provided to assess the real-time operation of the proposed EMS. Simulation and experimental results prove the advantages of the proposed approach by a reduction up to 50% of the batteries rms current on a real-world driving cycle compared to a battery-only EV.

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Stochastic Petri nets (SPNs) with generally distributed firing times can model a large class of systems, but simulation is the only feasible approach for their solution. We explore a hierarchy of SPN classes where modeling power is reduced in exchange for an increasingly efficient solution. Generalized stochastic Petri nets (GSPNs), deterministic and stochastic Petri nets (DSPNs), semi-Markovian stochastic Petri nets (SM-SPNs), timed Petri nets (TPNs), and generalized timed Petri nets (GTPNs) are particular entries in our hierarchy. Additional classes of SPNs for which we show how to compute an analytical solution are obtained by the method of the embedded Markov chain (DSPNs are just one example in this class) and state discretization, which we apply not only to the continuous-time case (PH-type distributions), but also to the discrete case.

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