Lattarulo et al., 2018 - Google Patents

A linear model predictive planning approach for overtaking manoeuvres under possible collision circumstances

Lattarulo et al., 2018

View PDF
Document ID
2568699491248563569
Author
Lattarulo R
He D
Pérez J
Publication year
Publication venue
2018 IEEE Intelligent Vehicles Symposium (IV)

External Links

Snippet

Overtaking is one of the most difficult tasks during driving. This manoeuvre demands good skills to accomplish it correctly. In the overtaking considering multiple vehicles (more than a couple) is necessary to understand, predict and coordinate future actions of the other …
Continue reading at dsp.tecnalia.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • G05D1/0295Fleet control by at least one leading vehicle of the fleet
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0011Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2550/00Input parameters relating to exterior conditions
    • B60W2550/40Involving external transmission of data to or from the vehicle

Similar Documents

Publication Publication Date Title
Wang et al. Trajectory planning and safety assessment of autonomous vehicles based on motion prediction and model predictive control
Wang et al. Risk assessment and mitigation in local path planning for autonomous vehicles with LSTM based predictive model
Suh et al. Stochastic model-predictive control for lane change decision of automated driving vehicles
Schwarting et al. Safe nonlinear trajectory generation for parallel autonomy with a dynamic vehicle model
Schwarting et al. Parallel autonomy in automated vehicles: Safe motion generation with minimal intervention
Yu et al. A human-like game theory-based controller for automatic lane changing
Dixit et al. Trajectory planning and tracking for autonomous overtaking: State-of-the-art and future prospects
Lattarulo et al. A linear model predictive planning approach for overtaking manoeuvres under possible collision circumstances
Batkovic et al. Real-time constrained trajectory planning and vehicle control for proactive autonomous driving with road users
Bautista-Montesano et al. Autonomous navigation at unsignalized intersections: A coupled reinforcement learning and model predictive control approach
Zheng et al. Investigation of a longitudinal and lateral lane-changing motion planning model for intelligent vehicles in dynamical driving environments
Ward et al. Probabilistic model for interaction aware planning in merge scenarios
Xu et al. System and experiments of model-driven motion planning and control for autonomous vehicles
Berntorp et al. Automated driving: Safe motion planning using positively invariant sets
Claussmann et al. A path planner for autonomous driving on highways using a human mimicry approach with binary decision diagrams
Chen et al. A hierarchical hybrid system of integrated longitudinal and lateral control for intelligent vehicles
Li et al. Human-like motion planning of autonomous vehicle based on probabilistic trajectory prediction
Lee et al. Autonomous-driving vehicle control with composite velocity profile planning
Du et al. A cooperative crash avoidance framework for autonomous vehicle under collision-imminent situations in mixed traffic stream
Quirynen et al. Integrated obstacle detection and avoidance in motion planning and predictive control of autonomous vehicles
Batkovic et al. Experimental validation of safe mpc for autonomous driving in uncertain environments
Yan et al. A hierarchical motion planning system for driving in changing environments: Framework, algorithms, and verifications
Gong et al. Game theory-based decision-making and iterative predictive lateral control for cooperative obstacle avoidance of guided vehicle platoon
Quirynen et al. Real-Time Mixed-Integer Quadratic Programming for Vehicle Decision-Making and Motion Planning
Cavanini et al. Lpv-mpc path planning for autonomous vehicles in road junction scenarios