ABSTRACT
In the recent past, wireless network simulations involving pedestrians are getting increasing attention within the research community. Examples are crowd networking, pedestrian communication via Sidelink/D2D, wireless contact tracing to fight the Covid-19 pandemic or the evaluation of Intelligent Transportation Systems (ITS) for the protection of Vulnerable Road Users (VRUs). Since in general the mobile communication depends on the position of the pedestrians, their mobility needs to be modeled. Often simplified mobility models such as the random-waypoint or cellular automata based models are used. However, for ad hoc networks and Inter-Vehicular Communication (IVC), it is well-known that a detailed model for the microscopic mobility has a strong influence – which is why state-of-the-art simulation frameworks for IVC often combine vehicular mobility and network simulators. Therefore, this paper investigates to what extent a detailed modelling of the pedestrian mobility on an operational level influences the results of Pedestrian-to-X Communication (P2X) and its applications. We model P2X scenarios within the open-source coupled simulation environment CrowNet. It enables us to simulate the identical P2X scenario while varying the pedestrian mobility simulator as well as the used model. Two communication scenarios (pedestrian to server via 5G New Radio, pedestrian to pedestrian via PC5 Sidelink) are investigated in different mobility scenarios. Initial results demonstrate that time- and location-dependent factors represented by detailed microscopic mobility models can have a significant influence on the results of wireless communication simulations, indicating a need for more detailed pedestrian mobility models in particular for scenarios with pedestrian crowds. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Given the present situation brought about by the COVID-19 pandemic, social-distancing and avoiding dense situations for pedestrians is of uttermost importance. However, to know if the current path taken by a pedestrians will lead to crowded locations requires realtime, up-to-date information on the density of pedestrians in the local area. Utilizing this, pedestrians (i.e. route recommending applications) could avoid crowded areas thus mitigating or reducing exposure risks. State-of-the art system relying on centralized backend services do not provide necessary realtime information and might lead to privacy concerns.In this paper, we propose an alternative, decentralized approach to disseminate Decentralized Pedestrian Density (DPD) maps which provide realtime density data in close to medium proximity. The DPD map is based on merging and aggregating position beacons into density measures disseminated by each pedestrian. We use LTE Advanced sidelink multicast communication to disseminate beacons and DPD maps. To evaluate our approach, we simulate an urban scenario modelling a small/medium area located within the city center of Munich, Germany. This requires a realistic modelling of the pedestrians movements and of the communication system. Therefore, we make use of the open-source simulation framework CrowNet, maintained at our group which couples the microscopic pedestrian dynamics simulator Vadere with a system-level simulation of LTE-A (SimuLTE model in OMNeT++).Initial results demonstrate the feasibility of the proposed approach but also indicate that overload situations can lead to the dissemination of outdated information, implying a need for situation- and load-adaptive transmission schemes. © 2021 IEEE.