[go: up one dir, main page]

Wu et al., 2021 - Google Patents

Motion planning of autonomous vehicles under dynamic traffic environment in intersections using probabilistic rapidly exploring random tree

Wu et al., 2021

Document ID
6039256889071925178
Author
Wu X
Nayak A
Eskandarian A
Publication year
Publication venue
SAE International Journal of Connected and Automated Vehicles

External Links

Snippet

In motion planning of autonomous vehicles, non-signalized intersections pose challenges due to a variety of tra c flows. Common motion planning algorithms use the current environmental information to find an optimal path that satisfies tra c safety and e ciency …
Continue reading at www.sae.org (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
    • G05D1/0287Control 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
    • G05D1/0297Fleet control by controlling means in a control room
    • 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
    • G05D1/0231Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • 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
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • 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
    • G05D1/0268Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • 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
    • G05D1/0044Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2201/00Application
    • G05D2201/02Control of position of land vehicles

Similar Documents

Publication Publication Date Title
Ji et al. TriPField: A 3D potential field model and its applications to local path planning of autonomous vehicles
Stahl et al. Multilayer graph-based trajectory planning for race vehicles in dynamic scenarios
Bae et al. Cooperation-aware lane change maneuver in dense traffic based on model predictive control with recurrent neural network
JP7150067B2 (en) Vehicle control system, method for controlling vehicle, and non-transitory computer readable memory
Wang et al. Predictive maneuver planning for an autonomous vehicle in public highway traffic
Wei et al. A behavioral planning framework for autonomous driving
Zhang et al. Dynamic trajectory planning for vehicle autonomous driving
Xu et al. System and experiments of model-driven motion planning and control for autonomous vehicles
Artunedo et al. Motion planning approach considering localization uncertainty
Ward et al. Probabilistic model for interaction aware planning in merge scenarios
Wu et al. Motion planning of autonomous vehicles under dynamic traffic environment in intersections using probabilistic rapidly exploring random tree
CN105573323A (en) automatic driving track generation method and apparatus
Du et al. Online monitoring for safe pedestrian-vehicle interactions
Svensson et al. Adaptive trajectory planning and optimization at limits of handling
Damerow et al. Balancing risk against utility: Behavior planning using predictive risk maps
Eilbrecht et al. Cooperative driving using a hierarchy of mixed-integer programming and tracking control
Wang et al. Optimal control-based highway pilot motion planner with stochastic traffic consideration
Kim et al. Hybrid approach for vehicle trajectory prediction using weighted integration of multiple models
Gao et al. Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation
Peng et al. Lane‐change model and tracking control for autonomous vehicles on curved highway sections in rainy weather
Garrido et al. A two-stage real-time path planning: Application to the overtaking manuever
Wang et al. A convex trajectory planning method for autonomous vehicles considering kinematic feasibility and bi-state obstacles avoidance effectiveness
Lattarulo et al. Fast real-time trajectory planning method with 3rd-order curve optimization for automated vehicles
Krishnan et al. A look at motion planning for AVs at an intersection
Sarvesh et al. Reshaping local path planner