The proliferation of rich automotive data contents keeps increasing the communication demand from / to connected vehicles, putting a strain on the limited bandwidth resources of cellular networks. Vehicle-to- Vehicle (V2V) communication holds promise to mitigate the load on the network infrastructure, as it enables vehicles to directly re-distribute the downloaded data contents to other vehicles, while gathering and aggregating sensor data from their neighbors before uploading the data to cloud computing platforms. However, the feasibility of V2V-assisted communications remains unclear in many aspects, with the biggest challenge being the lack of large-scale vehicle trace datasets, representing the mobility of privately owned vehicles, which can be used as input for network simulations. Although synthetic vehicle traces generated by a road traffic simulator could be a possible alternative to the real-world datasets, the plausibility of the network simulation results is largely attributed to the accuracy of the simulated road traffic volume along roads. In this paper, we develop a realistic vehicle mobility simulation model of the whole city of Nagoya, Japan. The road traffic volume is thoroughly calibrated on 1,618 road segments across the city, while traffic light cycles are also aligned with the historical data. The model can be executed in an open-sourced road traffic simulator SUMO, which can easily be interfaced with various network simulators like OMNeT++. 1.6 million vehicle trips are processed during a simulation for a 24-hour period, making it one of the largest SUMO traffic scenarios that are open to the research community.
NUMo: Nagoya Urban Mobility Scenario for City-Scale V2X Simulations
2024-05-29
3767324 byte
Conference paper
Electronic Resource
English
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