An Adaptive Motion Planning Technique for On-Road Autonomous Driving

Jin, Xianjian; Yan, Zeyuan; Yin, Guodong; Li, Shaohua; Wei, Chongfeng

doi:10.1109/access.2020.3047385

Cited by 34 publications

(12 citation statements)

References 34 publications

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“…Other than propelling energy reduction, enhancement of the ride's comfort represents a crucial potential of automated driving. To foster this aspect, several motions, path, and velocity planners proposed in the literature integrate as objective reducing variables related to vehicle longitudinal acceleration, lateral acceleration and yaw rate as an example [42,43]. Following a similar approach, reducing the following vehicle's longitudinal acceleration over the entire simulated drive cycle is considered here as an optimization target in J f ollow to enhance the passenger comfort.…”

Section: Multiobjective Optimal Car-following Driving Problemmentioning

confidence: 99%

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Anselma

2021

Energies

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Assessing the potential of advanced driver assistance systems requires developing dedicated control algorithms for controlling the longitudinal speed of automated vehicles over time. In this paper, a multiobjective off-line optimal control approach for planning the speed of the following vehicle in adaptive cruise control (ACC) driving is proposed. The implemented method relies on the principle of global optimality fostered by dynamic programming (DP) and aims to minimize propelling energy consumption and enhance passenger comfort. The powertrain model and onboard control system are integrated within the proposed car-following optimization framework. The retained ACC approach ensures that the distance between the following vehicle and the preceding vehicle is always maintained within allowed limits. The flexibility of the proposed method is demonstrated here through ease of implementation on a wide range of powertrain categories, including a conventional vehicle propelled by an internal combustion engine solely, a pure electric vehicle, a parallel P2 hybrid electric vehicle (HEV) and a power-split HEV. Moreover, different driving conditions are considered to prove the effectiveness of the proposed optimization-driven ACC approach. Obtained simulation results suggest that up to 22% energy-saving and 48% passenger comfort improvement might be achieved for the ACC-enabled vehicle compared with the preceding vehicle by implementing the proposed optimization-driven ACC approach. Engineers may adopt the proposed workflow to evaluate corresponding real-time ACC approaches and assess optimal powertrain design solutions for ACC driving.

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Section: Multiobjective Optimal Car-following Driving Problemmentioning

confidence: 99%

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Anselma

2021

Energies

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“…In the straight driving condition, the vertical load transfer of vehicle front and rear axles is determined through longitudinal acceleration, and the vertical load ratio of front and rear axles is used as the driving torque distribution ratio so as to determine the amount of driving torque distributed to the rear wheels. In the turning driving condition, for the sake of ensuring good steering and stability of the whole vehicle, under the driving torque distribution control strategy with the given transmission system, the driving force is distributed from the front wheels to the rear wheels to reduce the tendency of understeer trend [13]. In highspeed operating conditions, the torque distribution control of four-wheel independent drive vehicles is prone to robust stability problems.…”

Section: Introductionmentioning

confidence: 99%

Research on Torque Distribution of Four-Wheel Independent Drive Off-Road Vehicle Based on PRLS Road Slope Estimation

Ling

Huang

2021

Mathematical Problems in Engineering

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In view of the high difficulty in coupling of various electric vehicle parameters, intractable parameter estimation, and unreasonable distribution of vehicle driving torque, the four-wheel hub motor is applied to drive electric vehicles, which can instantly obtain the torque and speed of the hub motor and achieve precise control of the torque of each wheel. According to the vehicle longitudinal dynamics model, a progressive RLS (PRLS) algorithm for real-time estimation of vehicle mass and road gradient is proposed. Meanwhile, by means of taking the longitudinal acceleration of the vehicle and the road gradient obtained from the estimation algorithm as the parameter of the torque distribution at the front and rear axles, a dynamic compensation and distribution control strategy of the front and rear axle torques is designed. Moreover, based on hardware-in-the-loop real-time simulation and real-vehicle tests, the effectiveness of the proposed estimation algorithm and the rationality of the real-time distribution control strategy of driving torque are verified.

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“…As one of the development directions of future automobiles, intelligent driving is receiving more and more attention [1]. In particular, path planning is an important part of intelligent driving.…”

Section: Introductionmentioning

confidence: 99%

Research on Global Dynamic Path Planning Method Based on Improved A $^{*}$ Algorithm

Niu

Xin

et al. 2021

Mathematical Problems in Engineering

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Aiming at the optimal path and planning efficiency of global path planning for intelligent driving, this paper proposes a global dynamic path planning method based on improved A ∗ algorithm. First, this method improves the heuristic function of the traditional A ∗ algorithm to improve the efficiency of global path planning. Second, this method uses a path optimization strategy to make the global path smoother. Third, this method is combined with the dynamic window method to improve the real-time performance of the dynamic obstacle avoidance of the intelligent vehicle. Finally, the global dynamic path planning method of the proposed improved A ∗ algorithm is verified through simulation experiments and real vehicle tests. In the simulation analysis, compared with the modified A ∗ algorithm and the traditional A ∗ algorithm, the method in this paper shortens the path distance by 2.5%∼3.0%, increases the efficiency by 10.3%∼13.6% and generates a smoother path. In the actual vehicle test, the vehicle can avoid dynamic obstacles in real time. Therefore, the method proposed in this paper can be applied on the intelligent vehicle platform. The path planning efficiency is high, and the dynamic obstacle avoidance is good in real time.

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An Adaptive Motion Planning Technique for On-Road Autonomous Driving

Cited by 34 publications

References 34 publications

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Research on Torque Distribution of Four-Wheel Independent Drive Off-Road Vehicle Based on PRLS Road Slope Estimation

Research on Global Dynamic Path Planning Method Based on Improved A $^{*}$ Algorithm

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An Adaptive Motion Planning Technique for On-Road Autonomous Driving

Cited by 34 publications

References 34 publications

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort

Research on Torque Distribution of Four-Wheel Independent Drive Off-Road Vehicle Based on PRLS Road Slope Estimation

Research on Global Dynamic Path Planning Method Based on Improved A ∗ Algorithm

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Product

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Research on Global Dynamic Path Planning Method Based on Improved A $^{*}$ Algorithm