Simulation of cooperative automated driving by bidirectional coupling of vehicle and network simulators

The convergence of sensor-based vehicle automation and Inter-Vehicle Communication (IVC) will be a key to achieve the full automation of vehicles. In this paper we present a new method for the design and performance evaluation of Cooperative Automated Driving (CAD) systems, based on a bidirectional coupling of vehicle and network simulators (Webots and ns-3). The coupling exploits the comprehensive capabilities of the simulators at a reasonable computational complexity and allows simulating CAD systems with high accuracy. We demonstrate the capabilities of the simulation tool by a case study of convoy driving with automated vehicles using a fully distributed control algorithm and IVC. The study compares CAD-specific metrics (safety distance, headway, speed) for an ideal and a realistic communication channel. The simulation results underline the need of accurate modeling and give valuable insights for the design of CAD systems.

[1]  Panagiotis Papadimitratos,et al.  TraNS: realistic joint traffic and network simulator for VANETs , 2008, MOCO.

[2]  András Kovács,et al.  Enhancements of V2X communication in support of cooperative autonomous driving , 2015, IEEE Communications Magazine.

[3]  Yizhen Zhang,et al.  A realistic simulator for the design and evaluation of intelligent vehicles , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[4]  Daniel Krajzewicz,et al.  iTETRIS: A modular simulation platform for the large scale evaluation of cooperative ITS applications , 2013, Simul. Model. Pract. Theory.

[5]  Andreas Festag,et al.  Cooperative intelligent transport systems standards in europe , 2014, IEEE Communications Magazine.

[6]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[7]  Alcherio Martinoli,et al.  Exploration of an incremental suite of microscopic models for acoustic event monitoring using a robotic sensor network , 2008, 2008 IEEE International Conference on Robotics and Automation.

[8]  Gerhard Fettweis,et al.  Vehicular communication performance in convoys of automated vehicles , 2016, 2016 IEEE International Conference on Communications (ICC).

[9]  Milos Vasic,et al.  Distributed graph-based control of convoys of heterogeneous vehicles using curvilinear road coordinates , 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).

[10]  Ali Marjovi,et al.  Challenges for Automated Cooperative Driving: The AutoNet2030 Approach , 2017 .

[11]  Thomas R. Henderson,et al.  Network Simulations with the ns-3 Simulator , 2008 .

[12]  Reinhard German,et al.  Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis , 2011, IEEE Transactions on Mobile Computing.

[13]  Fredrik Tufvesson,et al.  Measurement based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations , 2012, ArXiv.

[14]  Olivier Michel,et al.  Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004 .

[15]  Petr Krejci,et al.  Cooperative Control of SARTRE Automated Platoon Vehicles , 2012 .

[16]  R.M. Murray,et al.  Nonlinear lateral control strategy for nonholonomic vehicles , 2008, 2008 American Control Conference.

[17]  Richard M. Murray,et al.  DISTRIBUTED COOPERATIVE CONTROL OF MULTIPLE VEHICLE FORMATIONS USING STRUCTURAL POTENTIAL FUNCTIONS , 2002 .

[18]  Olivier Michel,et al.  Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004, ArXiv.

[19]  Björn Schünemann,et al.  V2X simulation runtime infrastructure VSimRTI: An assessment tool to design smart traffic management systems , 2011, Comput. Networks.