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Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms

Author

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  • Mauricio Marcano
  • José A. Matute
  • Ray Lattarulo
  • Enrique Martí
  • Joshué Pérez

Abstract

Advanced Driver Assistance Systems (ADAS) acting over throttle and brake are already available in level 2 automated vehicles. In order to increase the level of automation new systems need to be tested in an extensive set of complex scenarios, ensuring safety under all circumstances. Validation of these systems using real vehicles presents important drawbacks: the time needed to drive millions of kilometers, the risk associated with some situations, and the high cost involved. Simulation platforms emerge as a feasible solution. Therefore, robust and reliable virtual environments to test automated driving maneuvers and control techniques are needed. In that sense, this paper presents a use case where three longitudinal low speed control techniques are designed, tuned, and validated using an in-house simulation framework and later applied in a real vehicle. Control algorithms include a classical PID, an adaptive network fuzzy inference system (ANFIS), and a Model Predictive Control (MPC). The simulated dynamics are calculated using a multibody vehicle model. In addition, longitudinal actuators of a Renault Twizy are characterized through empirical tests. A comparative analysis of results between simulated and real platform shows the effectiveness of the proposed framework for designing and validating longitudinal controllers for real automated vehicles.

Suggested Citation

  • Mauricio Marcano & José A. Matute & Ray Lattarulo & Enrique Martí & Joshué Pérez, 2018. "Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms," Complexity, Hindawi, vol. 2018, pages 1-12, March.
    • Handle: RePEc:hin:complx:7615123
    DOI: 10.1155/2018/7615123
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    References listed on IDEAS

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    1. Ioannou, P. & Xu, Z., 1994. "Throttle And Brake Control Systems For Automatic Vehicle Following," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1vb6380h, Institute of Transportation Studies, UC Berkeley.
    2. Kalra, Nidhi & Paddock, Susan M., 2016. "Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 182-193.
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    1. Gu, Yewen & Goez, Julio C. & Mario, Guajardo & Wallace, Stein W., 2019. "Autonomous vessels: State of the art and potential opportunities in logistics," Discussion Papers 2019/6, Norwegian School of Economics, Department of Business and Management Science.

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