Connected automated vehicle (CAV) platoon control is becoming increasingly prevalent because of its unique advantages in reducing fuel consumption and improving traffic efficiency. A novel framework for CAV designed this article. First, a model predictive (MPC)-based method proposed to obtain the optimal velocity whole platoon, which both transport efficiency are taken into account optimization process. Then, distributed adaptive triple-step nonlinear strategy investigated from perspective...

Drivers are being confronted by the task of controlling vehicles together with automation systems before autonomous even fully realized. A novel human-oriented online driving authority optimization shared steering framework is proposed to solve problem allocating between and human driver, in which model predictive control(MPC) method used optimize authority. The merits this that, on one hand, driver workload can be alleviated case that have similar intentions. On other has absolute control...

Vehicle trajectory prediction plays a vital role in intelligent driving modules and helps vehicles travel safely efficiently complex traffic environments. Several learning-based methods have been developed that accurately identify vehicle behaviour patterns actual data. However, these rely on manually curated structured data are difficult to deploy vehicles. In addition, modular information channels perform detection, tracking, tasks encounter error propagation issues insufficient computing...

To promote the intelligent vehicle safety and reduce driver steering workload, stackelberg game theory is adopted to design shared control strategy that takes neuromuscular delay characteristics into account. First, a framework with adjustable driving weight proposed, coupling interaction model considering constructed by using theory. Moreover, driver-automation optimal deduced theoretically when equilibrium reached. Finally, simulation virtual tests are carried out verify superiority of...

A method for estimating the velocity and road slope of a four-wheel drive vehicle based on full-order observer is proposed. First, we set up simplified dynamic model ramp driving which use longitudinal acceleration as input. This paper correction term respectively design nonlinear velocity; Secondly, estimation used value inputs. Finally, experimentally evaluate recommended high-precision software-veDYNA to verify validity proposed observer. Then two ways selecting terms are compared...

Q-learning usually carries out global path planning in grid environment, which is difficult to satisfy the requirements of vehicle dynamics practice. In this paper, a local for intelligent based on algorithm proposed. Firstly, vehicle-road model established. The information lane boundary and center line obtained by interpolation method, position relationship between main environment determined. Secondly, variables that can reflect driving state with surrounding are determined describe...

When a vehicle faces an imminent collision, it becomes imperative for intelligent vehicles to make emergency collision avoidance decisions in order mitigate traffic accidents and reduce injuries. To address scenarios, this study proposes model predictive decision-making (MPDM) approach that incorporates the consideration of lane-changing time. First, simplified integrated longitudinal lateral is established, its accuracy validated through comparison with real data. Second, mixed integer...

It proposes a path following control strategy for intelligent vehicles under extreme conditions based on feedback linearization and linear quadratic regulator (LQR). Firstly, the vehicle dynamics model kinematics are established, affine nonlinear system condition is established by these two models. Second, complex linearized using method to obtain simpler model. Finally, according obtained model, LQR used design tracking controller optimal input, so as ensure stability of optimality target,...

In urban conditions, the road environment is very complex and vehicle itself has strong nonlinearity, which makes decision control of obstacle avoidance path planning challenging. To solve problem difficult planning, this paper proposes a method for that combines artificial potential fields with model predictive control. Drawing on concept virtual force field, field prediction are organically combined by abstracting function as optimization objective, can realize modeling dynamic through...

Vehicle platoon has become a research hotpot due to its potential for improving traffic utility and fuel efficiency, which reliable tracking performance is critical. This paper proposes nonlinear moving horizon control strategy that ensures all vehicles in truck maintain the consensus speed desired spacing distance between adjacent vehicles. The proposed guarantees of following by predicting state preceding To verify availability strategy, simulations with two homogeneous trucks are carried...

This paper proposes a road risk assessment(RRA) algorithm based on lane and obstacle information, including selection line equations assessment time to collision (TTC). The can integrate the functions of warning change assessment, be implemented actual vehicles. RRA provide for vehicles in also give lane-changing suggestions, conduct changed according needs changing. In addition, alarm logic is designed, that is, when multiple risks appear at same time, it determined which HMI signal prompt...

This paper uses a nonlinear longitudinal control method for distributed drive electric vehicles(DDEV) to solve the safety problem of DDEV when driving on snow-covered road. Therefore, an optimal slip scheme based tire force prediction is proposed. First, use Burckhardt model draw µ– <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex> curve, magic formula F <inf xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> – get maximum that can be...