ToST: Tokyo SUMO Traffic Scenario

This paper introduces a new open traffic scenario — ToST (Tokyo SUMO traffic) scenario — designed for the SUMO traffic simulator and specifically targeting Tokyo urban areas. The generation of precise traffic scenarios is essential in various domains of intelligent transportation systems (ITS), particularly in transportation engineering, autonomous driving, and traffic management systems. Despite the past development of various approaches to generate traffic scenarios, these methods have certain limitations when applied to the context of Japan's urban roads and the lifestyle of its people. ToST leverages an algorithm utilizing ActivityGen, a widely-used traffic demand generation tool, to fine-tune a traffic demand based on an actual traffic volume dataset provided by the Tokyo Metropolitan Police Department. In particular, ToST covers a residential district of 32.22 km
²
in Tokyo, Japan, with a traffic demand of 298,310 trips. This scenario is publicly available on GitHub under the MIT license. We also provide an evaluation of the generated scenario, followed by a comparative analysis of the existing traffic scenarios.