Two-dimensional merging path generation using model predictive control

Cao, Wenjing; Mukai, Masakazu; Kawabe, Taketoshi

doi:10.1007/s10015-012-0059-8

Cited by 22 publications

(17 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using this assumption the trajectory of the merging vehicle can be designed by designing l 3 appropriately. The problem of [14] can be solved by using l 3 . If there is no vehicle on the main lane, the merging vehicle can run on l 3 and merge smoothly.…”

Section: Vehicle Dynamicsmentioning

confidence: 99%

“…The idea of this research is to formulate a merging problem into an optimization problem and to generate a vehicle trajectory for cooperative merging with model predictive control method (MPC). The possibility of this idea has been verified in the past research [14]. 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.…”

Section: Introductionmentioning

confidence: 99%

“…The possibility of this idea has been verified in the past research [14]. 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].…”

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

: 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.

show abstract

Section: Vehicle Dynamicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

“…Another reference profile that is used is obtained using similar parameters as described by [15] and given by the equation (11). …”

Section: Objective Functionmentioning

confidence: 99%

Highway Lane Merge for Autonomous Vehicles Without an Acceleration Area using Optimal Model Predictive Control

Hussain¹,

Jahromi²,

Karakaş³

et al. 2018

IJNTR

View full text Add to dashboard Cite

“…In the first category, the desired trajectory tracking is realized by the PID [1] and optimal control method [2,3] based on a vehicle linearized model. The second category includes robust control [4,5], predictive control [6,7], sliding mode control [8,9], self-adaptive control [10,11], and so forth.…”

Section: Introductionmentioning

confidence: 99%

A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

Wang

Lian

et al. 2014

Advances in Mechanical Engineering

View full text Add to dashboard Cite

A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

show abstract

Two-dimensional merging path generation using model predictive control

Cited by 22 publications

References 8 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

Highway Lane Merge for Autonomous Vehicles Without an Acceleration Area using Optimal Model Predictive Control

A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

Contact Info

Product

Resources

About