AgentDrive: Agent-Based Simulator for Intelligent Cars and Its Application for Development of a Lane-Changing Assistant

Part of the Understanding Complex Systems book series (UCS)


Intelligent cars represent a promising technology expected to drastically improve safety and efficiency of automobile transportation. In this paper, we introduce an agent-based simulation platform AgentDrive and argue that it can be used to speed up the development and evaluation of new coordination algorithms for intelligent cars. We present the high-level architecture of the simulator and characterize the class of tasks for which is the tool best suited. In addition, we present a case study of AgentDrive being used for development of a lane-changing assistant technology. We describe the developed solution in detail and present the benchmark result, which were obtained using AgentDrive simulator, that demonstrate that coordinated lane changing enables safer and swifter lane changing then the traditional non-coordinated approach.


Road Network Coordination Module Coordination Mechanism Lane Change Traffic Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS16/235/OHK3/3T/13.


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© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of Computer Science, Artificial Intelligence Center, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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