RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow
Zhengbang Zhu, Shenyu Zhang, Yuzheng Zhuang, Yuecheng Liu, Minghuan, Liu, Liyuan Mao, Ziqin Gong, Shixiong Kai, Qiang Gu, Bin Wang, Siyuan Cheng,, Xinyu Wang, Jianye Hao, Yong Yu

TL;DR
RITA enhances driving simulators by generating realistic, diverse, and controllable traffic flows, improving autonomous driving strategy evaluation and enabling online fine-tuning in highway scenarios.
Contribution
We introduce RITA, a novel integrated component that provides high-fidelity, diverse, and controllable traffic flow generation for driving simulators, addressing limitations of existing systems.
Findings
RITA produces diversified, high-fidelity traffic flows.
Traffic flows generated by RITA improve driving strategy evaluation.
RITA enables online fine-tuning of autonomous driving strategies.
Abstract
High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating traffic patterns that accurately reflect the various features of real-world data while also simulating human-like reactive responses to the tested autopilot driving strategies. Taking one step forward to addressing such a problem, we propose Realistic Interactive TrAffic flow (RITA) as an integrated component of existing driving simulators to provide high-quality traffic flow for the evaluation and optimization of the tested driving strategies. RITA is developed with consideration of three key features, i.e., fidelity, diversity, and controllability, and consists of two core modules called RITABackend and RITAKit. RITABackend is built to support vehicle-wise control and provide traffic generation models from…
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