Articles | Volume 17
https://doi.org/10.5194/ars-17-189-2019
https://doi.org/10.5194/ars-17-189-2019
19 Sep 2019
 | 19 Sep 2019

Extending the vehicular network simulator Artery in order to generate synthetic data for collective perception

Christoph Allig and Gerd Wanielik

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Cited articles

Aramrattana, M., Larsson, T., Jansson, J., and Nåbo, A.: A Simulation Framework for Cooperative Intelligent Transport Systems Testing and Evaluation, Transport. Res. F-Traf., 61, 268–280, https://doi.org/10.1016/j.trf.2017.08.004, 2017. a
Barthauer, M. and Hafner, A.: Coupling Traffic and Driving Simulation: Taking Advantage of SUMO and SILAB Together, EPiC Series in Engineering, 2, 56–66, 2018. a
BASELABS: Sensor Fusion Library for Algorithm Implementation, available at: https://www.baselabs.de/create/, last access: 15 January 2019. a
ETSI: Intelligent Transport Systems (ITS); Access Layer Specification for Intelligent Transport Systems Operating in the 5 GHz Frequency Band, EN 302 663 V1.3.0, ETSI, 2019. a
Gomez, A. E., Dos Santos, T. C., Filho, C. M., Gomes, D., Perafan, J. C., and Wolf, D. F.: Simulation Platform for Cooperative Vehicle Systems, in: IEEE Intelligent Transportation Systems Conference, 1347–1352, 8–11 October 2014, Hyatt Regency Qingdao, Qingdao, China, 2014. a
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Short summary
A fundamental for an automated driving car is the awareness of its surrounding road participants. Current approach to gather this awareness is to sense the environment by on-board sensors. In the future, Vehicle-to-X (V2X) might be able to improve the awareness. We propose to create synthetic data for investigating cooperative perception by a simulation tool. Therefore, Artery and its counterpart SUMO is extended by modelling realistic vehicle dynamics and probabilistic sensor models.