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Development of a real-time autonomous driving lateral control algorithm for an articulated bus using a model predictive control algorithm

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Abstract

In this paper, an autonomous driving lateral control algorithm is introduced for bus rapid transit (BRT, with an articulated bus). The control algorithm includes an integration of model predictive control (MPC) for lateral control and PID control algorithms for longitudinal control considering the vehicle properties. To verify the algorithm in real-time, a model-in-the-loop system was developed using TruckSim in NI Veristand and Matlab/Simulink in Micro-AutoBox. In TruckSim, a BRT plant model was verified using vehicle tests and then applied. In addition, GPS data from a BRT route were acquired from the vehicle test and applied to a TruckSim scenario. In the Matlab/Simulink, the autonomous driving lateral control algorithm for MPC was developed. To communicate between the plant model and the control algorithm in real-time, a controller area network (CAN) protocol was defined and applied like a real vehicle. Therefore, a real-time verification environment was prepared to test the real-time autonomous driving lateral control algorithm for BRT. By using the verification environment, the control algorithm was verified using the ISO-11270 standard. Although many efforts have been made to develop an autonomous driving control algorithm, autonomous driving of BRT is expected more tangible because the BRT has its own lane and speed limitation. Therefore, this paper will introduce about study of real time feasibility, adaptation of vehicle variables, and precise prediction model for MPC algorithm.

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Abbreviations

t cxi, t cyi :

Axle Boolean parameters

\({\vec r_i}\) :

Displacement vector from CG position to i-th wheel (m)

t xi, t yi :

Actuator Boolean parameters

Q i :

Torque to i-th wheel (Nm)

R w :

Tire effective radius (m)

C αi :

Cornering stiffness of i-th wheel (N/rad)

α i :

Slip angle of i-th wheel (rad)

ρ :

Air density (1.206 kg/m3)

C d :

Drag coefficient (0.5)

A :

Object facing area (2.495 × 3.43 m2)

V x :

Longitudinal velocity (m/s)

m :

Total mass (kg)

m s :

Sprung mass (kg)

I xx :

Moment of inertia about roll axis (kgm2)

I zz :

Moment of inertia about yaw axis (kgm2)

I xz :

Product of inertia (kgm2)

g :

Gravitational acceleration (9.81 m/s2)

h s :

Distance of sprung mass CG from roll axis (m)

K φ :

Roll stiffness coefficient of sprung mass (N/m)

C φ :

Roll damping coefficient of sprung mass (Nm/s)

K t−i :

Roll stiffness of hitch point

F CG :

CG point force

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Acknowledgments

This work was supported by the Technology Innovation Program (or Industrial Strategic Technology Development Program-Development of the Core System Technology for a Hyper-safe Driving Platform) (20015831, Development of Hypersafe Driving Platform based on Cooperative Domain Control) funded by the Ministry of Trade, Industry, & Energy (MOTIE, Korea).

This work was supported by the research grant of Kongju National University in 2022.

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Korea Advanced Institute of Science & Technology, Daejeon, Korea

    Beomjoon Pyun

  2. Korea Automotive Technology Institute, Cheonan City, Korea

    Beomjoon Pyun & Hyungjeen Choi

  3. Department of Intelligent Mobility Engineering, Kongju National University, Cheonan City, Korea

    Dohyun Jung

Authors
  1. Beomjoon Pyun
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  2. Hyungjeen Choi
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  3. Dohyun Jung
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Corresponding author

Correspondence to Dohyun Jung.

Additional information

Beomjoon Pyun was born in the Republic of Korea in 1985. He received the bachelor degree in mechanical engineering from Hanyang University in 2013 and the Master’s degree in automotive engineering from Hanyang University in 2015. He is studying in KAIST for doctoral degree. His research interests include system modeling, control algorithms, and machine learning for vehicles.

Hyungjeen Choi received a B.S. degree in Mechanical Engineering and Electronics (minor) from Dongguk University, Korea and an M.S. degree in Mechatronics from Gwangju Institute of Science and Technology, Korea. He has been with the Korea Automotive Technology Institute (KTAECH) since 2004. His research focus includes vehicle dynamics and control, active control systems, advanced driver assistance systems (ADAS), and autonomous vehicle control.

Dohyun Jung received a B.S. degree from Seoul National University (Republic of Korea) in 1992, and M.S. degree in mechanical engineering from the Korea Advanced Institute of Science and Technology (KAIST) in 1994. He received a Ph.D. in mechanical engineering from KAIST in 2001. He is currently a Head of the Department of Intelligent Mobility Engineering in Kongju National University.

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Pyun, B., Choi, H. & Jung, D. Development of a real-time autonomous driving lateral control algorithm for an articulated bus using a model predictive control algorithm. J Mech Sci Technol 38, 901–914 (2024). https://doi.org/10.1007/s12206-024-0136-7

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  • DOI: https://doi.org/10.1007/s12206-024-0136-7

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