面向新一代智能交通系统的车联网仿真技术

Vehicle Network Simulation Technology for New Generation Intelligent Transportation Systems

车联网仿真技术是智能交通系统以及车联网领域发展的重要测试手段,然而,已有的车联网仿真平台基于固定模型构建业务场景,如车辆跟驰模型、静态业务优先级模型等,这种模型驱动的仿真方法难以适应新一代智能交通系统特征。因此,提出了一种数据驱动的车联网仿真技术,基于海量路网信息数据、动态学习和标定典型智能交通场景下的业务特征,为车联网仿真提供柔性动态的业务适配,满足新一代智能交通系统需求。

Simulation technology of Internet of Vehicles(IoV)is an important test method for the development of intelligent transportation systems and IoVs.However,the current IoV simulation platforms establish service scenarios based on fixed models,such as vehicle following model,static service priority model,etc.This model-driven simulation method is difficult to support the characteristics of the intelligent transportation system in new generation.Therefore,this paper proposes a data-driven simulation technology of IoVs.Based on massive information data from road network,dynamically learning and calibrating the service characteristics of typical intelligent traffic scenarios,the proposed simulation technology provides flexible and dynamic service adaptation for vehicle network simulation to meet the requirements of intelligent transportation systems in new generation.