461 results about "Road user" patented technology

A system and method for facilitating collection of Road User Charges (RUC) using a digital currency within a Distributed Ledger Technology (DLT) network are disclosed. The system generates secure digital wallets for Road Users and Facility Owners, receives trip, position, distance, and cost data from vehicles, sensors, and facility systems, and encodes settlement logic into smart contracts. These contracts automatically execute jurisdiction-specific disbursements across blockchain, directed acyclic graph (DAG), or hashgraph frameworks, ensuring scalability and auditability without reliance on centralized tolling infrastructure. An AI Activity Module processes multi-source telemetry—including vehicle sensors, GNSS / PNT data, roadside infrastructure, and third-party traffic feeds—to detect congestion, forecast conditions, optimize routing, and dynamically adjust segment-level RUC pricing in real time. The integration of AI-driven adaptive pricing with distributed ledger settlement provides a decentralized, infrastructure-agnostic framework for secure, transparent, and verifiable road use fee collection across multiple jurisdictions, distinct from conventional tolling systems.

The invention discloses a training method and device of an automatic driving decision model, a medium and a product, and relates to the technical field of automatic driving, iteratively training the decision model by adopting a trained world model, and inputting a driving action output by the decision model and a traffic structure condition corresponding to the driving action into the trained world model. The award value of the driving action is calculated according to the obtained future driving scene information, and the decision model is updated according to the award value, so that efficient closed-loop optimization of the decision model is realized, the perception ability and decision ability of the model can be remarkably improved, and the training efficiency is improved. The first reward value based on the road and the second reward value based on the road user are constructed through the future driving scene, the advantages and disadvantages of the driving action are evaluated from the two aspects of the road and the road user, the driving action is optimized, the safety and reliability of the automatic driving decision are improved, and the automatic driving performance of the vehicle in the complex traffic environment is improved.

A system and method for controlling a road user assistance network includes obtaining historical data, obtaining geo-fence data, generating probabilistic states for a future time, determining spatial proximity data for a feature based on the geo-fence data, generating a prediction based on the probabilistic state and the spatial proximity data, communicating the prediction to a road user or a roadside device and controlling the road user or roadside device based on the prediction.

The invention relates to a method for providing, by means of a warning device (12), an adaptation notification, preferably a warning notification, to at least one ego road user (10) to be notified to adapt at least one driving function to at least one surroundings road user (32) located and / or moving in the surrounding region (2) of the road user, said warning device being provided with respective movement paths (PCL, PR) which are predicted for the ego road user and for the at least one surroundings road user (32) and along which the movements of the road users (10, 32) are expected. The warning device (12) determines, on the basis of the predicted movement paths (PCL, PR), at least one notification variable, which is characteristic of a provision of the adaptation notification and which is preferably characteristic of whether an adaptation notification (I1, A32) is to be provided and / or at what time the adaptation notification (I1, A32) is to be provided. According to the invention, the warning device (12) determines the notification variable on the basis of at least one swarm prediction variable, in particular at least one statistical swarm prediction variable, for determining the prediction quality of at least one of the predicted movement paths (PCL, PR), wherein the at least one swarm prediction variable is determined on the basis of global swarm movement data of a plurality of road users, said movement data being generated in a plurality of different traffic regions (2).

A method for predicting trajectories of road users includes (i) representing a traffic scene as an agent interaction graph, each having a node for a road user corresponding to a target vehicle and for one or more other road users and having a plurality of edges, wherein each edge between two of the nodes is associated with a respective edge type, which indicates a type of movement of the road users represented by the nodes relative to each other on a respective roadway, (ii) processing the agent interaction graph by a graph transformer to determine embeddings of the target vehicle and the one or more other road users, wherein the graph transformer has an attention mechanism which takes into account the edge types of the edges of the agent interaction graph, and (iii) predicting at least one trajectory of the target vehicle from the embeddings.

The technology involves pick-up and drop-off techniques for autonomous vehicles. Pullover selection options are evaluated by considering road user inconvenience and dynamic changes to such inconvenience. In response, a change in vehicle operation is made as needed. This process may consider whether a given situation is “likely-inconvenient” or “unlikely-inconvenient” based on both statie and dynamic signals from the environment for a likely pick-up or drop-off location. The vehicle may request remote support to determine whether to pull over or to move from a stopped location, for instance based on changes to dynamic signals associated with other road users. In double parking situations, the vehicle may determine whether to remain double parked or move to limit inconvenience to a minimum number of other vehicles, such as by blocking as few other vehicles as possible or by making it as easy as possible for a parked vehicle to pull out.

A method for classifying a driving behavior of a road user in the environment of an ego vehicle. The method includes: receiving trajectory data of a driving trajectory of a road user arranged in the environment of an ego vehicle; ascertaining a latent-space representation of the driving trajectory of the road user in a latent space; ascertaining a distance of the latent-space representation of the driving trajectory of the road user to a latent-space representation of at least one normal trajectory in the latent space and classifying a driving behavior of the road user as a normal driving behavior if the distance in the latent space falls below a predetermined limit value; or classifying the driving behavior of the road user as an abnormal driving behavior if the distance in the latent space exceeds the predetermined limit value.

To provide a vehicle collision detection device capable of accurately determining collisions with vulnerable road users.SOLUTION: A processor 152 of an ECU 150 includes: an object probability calculation unit 152b that calculates a first probability indicating the likelihood that an object in front of a vehicle is a pedestrian or a bicycle; a collision probability calculation unit 152c that calculates a second probability indicating the probability of the vehicle colliding with the object; a collision prediction probability calculation unit 152a that calculates a collision prediction probability indicating the probability of colliding with the pedestrian or the bicycle based on the first probability and the second probability; a collision determination threshold acquisition unit 152d that acquires a collision determination threshold for the vehicle's deceleration based on the collision prediction probability; and a collision determination unit 152e that determines whether the vehicle collided with the pedestrian or the bicycle based on the detected value of the vehicle's deceleration and the collision determination threshold.SELECTED DRAWING: Figure 2

The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected / observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Disclosed embodiments include technologies for improving safety mechanisms in computer assisted and / or automated driving (CA / AD) vehicles for protecting vulnerable road users (VRUs). Embodiments include various mechanisms to enable early Responsibility Sensitive Safety (RSS) checks for the CA / AD vehicles driving policy to protect in-danger VRUs. Embodiments also include controlled forwarding mechanisms to notify other CA / AD vehicles and roadside infrastructure when a potentially dangerous situation is detected. Other embodiments are described and / or claimed.

The invention relates to a crash protection device for a roof frame of a motor vehicle, comprising at least the following components: - a protective element for absorbing a collision load; - a joint arrangement for moving the protective element between a normal position and a protective position; and - a drive unit for actuating the joint arrangement to transfer the protective element into the protective position, wherein, when viewed in use from a design collision direction, the associated roof frame is covered by the protective element. The crash protection device proposed here represents an efficient and cost-effective measure for the protection of road users.

A method that is computer implemented for self-learning of relevancy metrics for perception related applications, the method comprising: receiving a training dataset that comprises (i) scenario information regarding a scenario faced by a vehicle and involving a road user, and (ii) behavior information indicative of a response of the vehicle to a presence of the road user; determining, based on the scenario information and the behavior information, a relevancy metric providing an indication of an impact of the road user on a driving of the vehicle; and training, using self-learning, a machine learning process to infer the relevancy metric according to the scenario.

A computer-implemented method for warning road users of a hazardous operating condition of a heavy-duty vehicle. The method comprises obtaining, by a processor device of a computer system, a speed limit interval associated with a road on which a heavy-duty vehicle is travelling, and wherein the speed limit interval is based on a speed limit of the road; determining, by the processor device, that a travelling speed of the heavy-duty vehicle is outside the speed limit interval; determining, by the processor device, that a travelling angle of the heavy-duty vehicle and / or of the road on which the heavy-duty vehicle is travelling is outside a predetermined travelling angle range; and automatically controlling, by the processor device, the vehicle hazard lights of the heavy-duty vehicle based on the travelling speed and the travelling angle.

A driving assistance system, a driving assistance method, a non-transitory computer-readable storage medium storing a driving assistance program for assisting driving of a host vehicle plans a behavior change that is a change in a driving behavior controlled in the host vehicle, and projects a notification image that provides notification of a transition state of the behavior change onto a traveling road to cause a different road user to recognize the notification image, the different road user being expected to interact with the host vehicle.

Systems and methods for externally communicating vehicular gaming status are disclosed herein. One embodiment of a gaming-status communication system detects automatically, in a connected vehicle, activation of a gaming mode of the connected vehicle in which a gaming system of the connected vehicle supports at least one of (1) electronic game playing by one or more occupants of the connected vehicle and (2) multi-vehicle networked electronic gaming involving the connected vehicle and one or more other connected vehicles. In response to detecting the activation of the gaming mode, the system activates automatically one or more external human-machine interface (HMI) indicators on the exterior of the connected vehicle to communicate, to other road users, information pertaining to the gaming mode of the connected vehicle.

A method for providing information detected by on-board sensors about road users in the surroundings of a vehicle involves providing the detected information as data structures representing vectors. Every vector is thereby associated with a cell of a predefined vehicle-mounted occupancy grid, in which a road user described by the respective information is situated. Every vector at least includes coordinates of an associated cell, in which the respective road user is situated, a speed vector, which represents a speed of the respective road user, a time stamp, which represents a point in time of a detection of the respective road user, and an object class, which represents a type of the respective road user.

A method for assisting an automated vehicle in vehicle control, the method including continuously checking whether the automated vehicle is leaving its operational design domain and whether a comparison metric of the deviation of current environmental conditions from the associated information on a digital map is exceeded. If so, the method further includes requesting an authorization to enter a vehicle-following mode at a control center; and rejecting the request or granting the request by the control center, wherein when the request is granted by the control center, a start of the vehicle-following mode and the road user to be followed are determined. The method additionally includes carrying out a vehicle-following mode by the vehicle at the start determined by the control center behind the road user determined by the control center.

A traffic monitoring system has at least one environment sensor and a communication device for sending and receiving traffic messages from road users, which may contain status information of the road user or information from the sensors of the road user. The road user is determined with the environment sensor and a traffic map of the traffic area including the determined road users is created. Road users who can send or receive traffic messages are determined and compared with the traffic map. It is determined what kind of traffic messages road users can receive and send. If a critical situation could arise between at least two road users and if at least one of these road users can receive traffic messages, a traffic message is sent to the road user able to receive traffic messages containing information about a road user who cannot send or receive traffic messages.

The technology involves pullover maneuvers for vehicles operating in an autonomous driving mode. A vehicle operating in an autonomous driving mode is able to identify parking locations that may be occluded or otherwise not readily visible. A best case estimation for any potential parking locations, including partially or fully occluded areas, is compared against predictions for identified visible parking locations. This can include calculating a cost for each potential parking location and comparing that cost to a baseline cost. Upon determining that an occluded location would provide a more viable option than any visible parking locations, the vehicle is able to initiate a driving adjustment (e.g., slow down) prior to arriving at the occluded location. This enables the vehicle to minimize passenger discomfort while also providing notice to other road users of an intent to pull over.

A method of coordinating road users via a server device which determines instruction data by a central model and transmits the instruction data as action instruction to respective control circuits of the road user, the central model being a virtual image of a real environment created by the server device from environment data, includes when a road user reaches the real environment a local model is created by onboard sensor data and delta data relating to the central model is determined. The delta data is transmitted to the server device by the control circuit of the road user which creates an updated central model by the delta data and the central model. The server device determines and transmits updated instruction data to the road user as readjustment of the instruction data.

The present disclosure relates to methods and systems for spatiotemporal graph modelling of road users in observed frames of an environment in which an autonomous vehicle operates (i.e. a traffic scene), clustering of the road users into categories, and providing the spatiotemporal graph to a trained graphical convolutional neural network (GNN) to predict a future pedestrian action. The future pedestrian action can be: one of the pedestrian will cross a road and the pedestrian will not cross the road. The spatiotemporal graph includes a better understanding of the observed frames (i.e. traffic scene).

The application provides a weak road user trajectory prediction method and system based on motion query enhancement, which comprises the following steps: aligning the current position and direction of each motion sample through a normalization process, clustering the end points of the normalized motion samples, taking the obtained cluster centers as generated static queries, using extended static queries (DSQ) to extend the coverage of the static queries to provide more diverse motion patterns; combining the extraction and fusion of trajectory features and map features to obtain map features and enhanced trajectory features, which are used to obtain the update query features of each layer subsequently, using cross-connection dynamic queries (BDQ) to establish a connection between the dynamic queries output by the shallow and deep decoders, coordinating the query optimization between the decoding layers; and integrating the prediction results of multiple homogeneous models to obtain the final prediction trajectory. The application can more effectively extract features that can reflect the motion trend of weak road users, making the prediction results more accurate.

A method for recognizing road users in an environment of a vehicle includes determining detections that describe potential objects in the environment, identifying faulty detections within the detections, and recognizing the road users on the basis of the detections other than the faulty detections. Identifying the faulty detections further includes, for each detection, checking, on the basis of the spatial position with respect to other detections, whether the detection originates from a reflection effect of a plurality of predefined reflection effects of the radar signal, wherein the plurality of predefined reflection effects describes at least one additional reflection of the radar signal after a first reflection of the radar signal by an object.

The invention relates to a method for keeping a road intersection (10) clear for a special emergency vehicle (12) and a control device for carrying out the method. It is provided that, based on route information received from a special operations vehicle (12), an intersection point with the route of the own motor vehicle (16) is determined and the own motor vehicle (16) stops at the intersection (10) corresponding to the intersection point and informs other road users about the approaching special operations vehicle (12) in order to keep the intersection (10) clear for the special operations vehicle (12).

Aspects of the disclosure provide methods of modeling wrong-way driving of road users. For instance, log data including an observed trajectory of a first road user may be accessed. A first set of candidate lane segments for wrong-way driving may be identified from map information. A second set of candidate lane segments for not wrong-way driving may be identified from the map information. For each candidate lane segment in the first set and in the second set, a distance cost between the candidate lane segment and the observed trajectory may be determined. A candidate lane segment may be selected from at least one of the first set or the second set based on the determined distance costs. The selected candidate lane segment may be used to train a model to provide a likelihood of a second road user being engaged in wrong-way driving in a lane.

This disclosure provides methods, components, devices and systems for automated driving plan notifications. A system at an autonomous vehicle may be configured to obtain first information indicative of one or more road users. The system may be configured to generate a notification message in accordance with the first information. The notification message may include a planned action for the autonomous vehicle. The notification message may also include second information applicable to coordination of the planned action with at least one non-autonomous vehicle road user. The system be configured to transmit, via a transceiver, at least one instance of the notification message to the at least one non-autonomous vehicle road user of after generating the notification message. The at least one instance of the notification message may include respective second information for each road user of the one or more road users.

Method for providing a time-difference probability density (p(t) Δ )), namely the probability density for time differences (t Δ ) to avoid a collision between an ego vehicle and another road user, the procedure including: Providing basic data, namely the distance of the ego vehicle (x 0,ego ) and the other road user (x 0,obj ) from the possible collision area, the speed of the ego vehicle (v 0,ego ) and the other road user (v 0,obj ) the acceleration of the ego vehicle (a 0,ego ) and the other road user (a 0,obj ); where the time difference (t Δ ) depends on the basic data; Determining a domain ( D t Δ ) for one or more basic data points, in particular for the distance of the ego vehicle (x ego), namely a range of values ​​for the basic data(s) in which the time difference (t) Δ ) a predetermined criterion is met, Determining a mean value (µ) depending on I time differences (t) Δ ), each representing a basic data point or a combination of basic data points, in particular a distance (x i,ego ) of the Ego vehicle, are calculated, whereby the I basic data or combinations of basic data are taken into account the domain of definition. ( D t Δ ) be determined; Determining a standard deviation (σ) depending on the time differences (t) Δ ); Determining the time-difference probability density (p(t) Δ )) depending on the determined mean (µ) and the standard deviation (σ).

This utility model discloses a low-temperature resistant and interference-resistant vehicle lamp, including a supporting shell. An isolation cover is fixedly installed on the side of the supporting shell, and a mounting frame is fixedly connected to the outer side of the supporting shell. A fixing screw is inserted into the side of the mounting frame, and an inner isolation plate is fixedly snapped onto the inner side of the supporting shell. Advanced UV electroplating technology concentrates the light pattern, greatly improving luminous efficiency. This not only reduces glare affecting other road users but also increases the illumination distance, allowing drivers to see the road ahead more clearly at night or in adverse weather conditions, effectively ensuring driving safety. The cover is made of UV-resistant material, increasing wear resistance and effectively preventing scratches. During long-term use, even under various harsh environments and external friction, it maintains good appearance and light transmission, extending the lamp's lifespan and reducing the frequency and cost of lamp replacement.