D-AWSIM: Distributed Autonomous Driving Simulator for Dynamic Map Generation Framework

Ito, Shunsuke, Zhao, Chaoran, Okamura, Ryo, Azumi, Takuya

arXiv.org Artificial Intelligence 

Personal use of this material is permitted. Abstract--Autonomous driving systems have achieved significant advances, and full autonomy within defined operational design domains near practical deployment. Expanding these domains requires addressing safety assurance under diverse conditions. Information sharing through vehicle-to-vehicle and vehicle-to-infrastructure communication, enabled by a Dynamic Map platform built from vehicle and roadside sensor data, offers a promising solution. Real-world experiments with numerous infrastructure sensors incur high costs and regulatory challenges. Conventional single-host simulators lack the capacity for large-scale urban traffic scenarios. This paper proposes D-A WSIM, a distributed simulator that partitions its workload across multiple machines to support the simulation of extensive sensor deployment and dense traffic environments. A Dynamic Map generation framework on D-A WSIM enables researchers to explore information-sharing strategies without relying on physical testbeds. The evaluation shows that DA WSIM increases throughput for vehicle count and LiDAR sensor processing substantially compared to a single-machine setup. Integration with Autoware demonstrates applicability for autonomous driving research. I. Introduction Current autonomous driving systems are capable of operating without human input and are fully autonomous within operational design domains (ODDs).