Cooperative vehicle path generation during merging using model predictive control with real-time optimization

Cao, Wenjing; Mukai, Masakazu; Kawabe, Taketoshi; Nishira, Hikaru; Fujiki, Noriaki

doi:10.1016/j.conengprac.2014.10.005

Cited by 154 publications

(68 citation statements)

References 14 publications

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“…In this paper the initial guess of the merging path to be optimized for Vehicle1 is designed as l 3 expressed as Eq. (3), we call it Cao curve [15], [16]. l 3 is derived from l 1 and l 2 .…”

Section: Modeling Of Roadmentioning

confidence: 99%

“…To obtain realistic traffic condition, the time history of a merging scene was taken from a helicopter at the exit of Kiyama parking area in Kyushu Motorway, Japan (Jan. 15,2011). A picture of the road is shown in Fig.…”

Section: Computer Simulation and Analysismentioning

confidence: 99%

“…However under some initial conditions the method proposed in [14] could not prevent the oscillating deviation from the center line of the main lane after merging since the whole trajectory of the merging vehicle was generated from the optimization problem. To solve this problem, a new formulation base on MPC is proposed in [15] and improved in [16]. With the improved method proposed in [15] and [16], a merging trajectory was generated successfully for a single main lane vehicle and a single merging vehicle but not for multiple main lane vehicles.…”

Section: Introductionmentioning

confidence: 99%

“…To solve this problem, a new formulation base on MPC is proposed in [15] and improved in [16]. With the improved method proposed in [15] and [16], a merging trajectory was generated successfully for a single main lane vehicle and a single merging vehicle but not for multiple main lane vehicles.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Gap Selection and Path Generation during Merging Maneuver of Automobile Using Real-Time Optimization

Cao

Mukai

Kawabe

et al. 2014

SICE Journal of Control, Measurement, and System Integration

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: This paper has proposed a gap selection and path generation method during merging maneuver of automobile. In this method the merging problem of one merging vehicle and multiple main lane vehicles is formulated using a model predictive control method. Lanes of a motor way are approximated with proposed smooth lines. Assuming that the main lane vehicles run on the centerline of the main lane, an appropriate path of the merging vehicle can be simply designed and modified according to the motions of the main lane vehicles. To generate mild merging, accelerations of all the relevant vehicles are constrained. Effectiveness of the proposed method is validated by computer simulations of the merging maneuvers of one merging vehicle and two main lane vehicles in different conditions. An example of actual cooperative merging maneuver is generated by the proposed method. Further the collision avoidance ability and the initial condition dependent property of the proposed method are tested.

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Section: Modeling Of Roadmentioning

confidence: 99%

Section: Computer Simulation and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Gap Selection and Path Generation during Merging Maneuver of Automobile Using Real-Time Optimization

Cao

Mukai

Kawabe

et al. 2014

SICE Journal of Control, Measurement, and System Integration

Self Cite

View full text Add to dashboard Cite

show abstract

“…Other authors, as [21], are tackling the problem considering the importance of dealing with the general case of driving (especially in urban scenarios). The idea is handling situations that goes from, for example, cruise control to being able of respecting traffic lights or signs, among other things.…”

Section: Introductionmentioning

confidence: 99%

Urban Motion Planning Framework Based on N-Bézier Curves Considering Comfort and Safety

Lattarulo

Gonzalez

Martí

et al. 2018

Journal of Advanced Transportation

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In last decades, great technology advances have been done related to the automotive sector, especially in Advanced Driver Assistance Systems (ADAS) developed to improve mobility in terms of comfort and safety during driving process; hence, automated driving is presented as an evolution of those systems in the present and upcoming years. The aim of this work is to present a complete framework of motion planning for automated vehicles, considering different constraints with parametric curves for lateral and longitudinal planners. Parametric Bézier curves are used as the core approach for trajectory design in intersections, roundabouts, and lane change maneuvers. Additionally, a speed planner algorithm is presented using the same parametric curve approach, considering comfort and safety. A simulation environment is used for testing the planning method in urban conditions. Finally, tests with the real platform in automated mode have been performed showing goods results.

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A parameter setting method to find the required state estimation accuracy for a motion control method in merging scenario

Cao

Mukai

Kawabe

2021

Asian Journal of Control

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In this study, we propose a procedure for parameters setting of the motion control method to find the required state estimation accuracy. A lot of motion control methods have been proposed for automatic driving vehicles in recent years to reduce fuel consumption and drivers' mental load. Mode predictive control (MPC) method is one of the often‐used control methods in motion control of automobiles. The technique to find the required state estimation accuracy is necessary to implement a motion control method. However, to the best of the authors' knowledge, such a technique has not been presented in any literature before. Therefore, we proposed a parameter setting method to find the required state estimation accuracy, assuming a model‐predictive‐type motion control method designed based on an optimal control problem. The contributions of this work are as follows: (1) A specific procedure to set the control parameters is proposed. (2) To overcome the difficulty of the parameter setting problem, we divide the control parameters into two sets. The first set of parameters are unrelated to the robustness against state estimation errors, while the others are related. (3) The parameters in the first set are designed independently of the others, so that parameter setting can be easily accomplished. The parameters in the first set are designed to obtain desirable motion of the ego vehicles ignoring the errors. The other parameters are set to find the required state estimation accuracy. (4) The parameter tuning problem and the specification of the state estimation accuracy is considered together. As a result, once the control parameters are determined, the required state estimation accuracy is specified. As an example, a robust motion control method based on MPC for merging scenario was considered. Calculations for some cases were conducted to show the effectiveness of the proposed procedure. The results showed that, if the estimation errors in the displacements of the vehicles are bounded in [− 1, 1][m]and that in the velocities are bounded in [− 1/30, 1/30][m/s], desirable motion control is possible for all the tested initial conditions.

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Cooperative vehicle path generation during merging using model predictive control with real-time optimization

Cited by 154 publications

References 14 publications

Gap Selection and Path Generation during Merging Maneuver of Automobile Using Real-Time Optimization

Gap Selection and Path Generation during Merging Maneuver of Automobile Using Real-Time Optimization

Urban Motion Planning Framework Based on N-Bézier Curves Considering Comfort and Safety

A parameter setting method to find the required state estimation accuracy for a motion control method in merging scenario

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