Systems and methods are provided for label placement that provide necessary information on a map when map features conflict without significantly impacting performance. Embodiments of the present disclosure can handle placement of map labels that vary in size, have prioritized label/feature groupings, apply to point, line, and area features, minimize overlap when there is no more open space, and render fast enough for interactive viewing.

Traffic jam patterns can be identified and, based on historical traffic data, pre-traffic jam patterns that are likely to result in the traffic jam patterns can be identified as well. Real-time traffic data regarding a driving road of a community can be received and analyzed to determine whether the real-time traffic data match with a pre-traffic jam pattern. If the data matches a pre-traffic jam pattern, an alerting signal for predicting a traffic jam can be transmitted.

A lead autonomous vehicle (AV) includes a sensor configured to observe a field of view in front of the lead AV. Following AVs are on the same road behind the lead AV. A processor of the lead AV is configured to detect a road closure. The processor overrides driving instructions of the lead AV, such that the lead AV is stopped at first location coordinates. The processor sends a first message to an operation server, indicating that the road closure is detected. The operation server update the first portion of the map data, reflecting the road closure. The operation server determines whether re-routing is possible for each AV. If re-routing is possible is possible for that AV, the operation server sends re-routing instructions to the AV. If re-routing is not possible is possible for that AV, the operation server sends pulling over instructions to the AV.

The present application relates to a method and apparatus for controlling an ADAS equipped vehicle including an input for receiving a lane change request, a global positioning sensor for detecting a vehicle location, a memory for storing a map data, a vehicle controller for performing a lane change in response to a lane change navigational route, and a processor configured for generating the lane change navigational route in response to the map data and the lane change request, for calculating a predicted lateral acceleration within the lane change navigational route in response to the map data and the lane change request and for coupling the lane change navigational route to the vehicle controller in response to the predicted lateral acceleration being less than a lateral acceleration threshold.

Embodiments disclosed herein provide for a method including configuring a self-learning safety sign to: establish vehicle-to-everything (V2X) communications with a two-wheeler equipped with a V2X transceiver and positioned at a ride point and/or ridden along a common and divergent route according to a setup stage for the safety sign; receive ride parameters in the V2X communications from the two-wheeler associated with the positioning and/or riding of the two-wheeler; and analyze the received ride parameters to create a ride model for determining a future route to be taken by any two-wheeler in V2X communication with the safety sign.

Devices for alerting visually a vehicle at an intersection when a specific two-wheeler is detected in an alert zone associated with the intersection using vehicle-to-everything (V2X) communications, and methods for configuring and using such devices. The devices include a display for displaying the visual alert and a communication and processing unit for processing V2X messages received from two-wheelers and for determining the need for and type of visual alert. The devices may be configured remotely using an application running on an installer's mobile device.

A method for updating a map of the surrounding area wherein the map is used when controlling a transportation vehicle. The transportation vehicle attempts, when travelling along a carriageway, to detect a landmark recorded in the map of the surrounding area using sensors. In response to the transportation vehicle being unable to detect the landmark using its sensors, the transportation vehicle prepares a proposal for deletion which is sent to an external central computer. The proposal for deletion is examined in the external central computer and deletes the landmark from the map of the surrounding area in response to the proposal for deletion being verified. In the method, information regarding a visibility range for the landmark is entered in the map of the surrounding area specifying at what range the landmark is visible from a road permitting a more effective detection of landmarks.

A system for marking locations along roads in a map and a method therefor are disclosed. The system comprises a location marking module, a location obtaining module, a location data conversion module, and a location information displaying module. The marking is virtually performed in a map and does not need on-site signs, and the present invention is suitable for marking locations using all roads. Moreover, because the marking is performed using road names and distances from particular locations to road start points, vertical distances from the particular locations to central lines of the roads, or distances from the particular locations to intersections between lines vertical to central lines of virtual roads and central lines of actual roads, a method for intuitively and conveniently marking plane locations can be implemented; if height data is added, the method can be used as a method for marking locations in a three-dimensional space.

According to an embodiment, a surroundings recognition device includes an acquirer configured to acquire first road information including a road boundary near a host vehicle from map information on the basis of position information of the host vehicle, a recognizer configured to recognize a road boundary near the host vehicle on the basis of an output of an external environment sensor, and a determiner configured to determine that a first road boundary matches a second road boundary when the second road boundary included in second road information that is a recognition result of the recognizer is within a road boundary determination area based on a position of the first road boundary included in the first road information acquired by the acquirer. The determiner sets a size of the road boundary determination area on the basis of a predetermined condition.

A high-definition map building method includes determining a key node describing information about a key position of a lane attribute change, determining a key node layer based on a position of the key node and an attribute of the key node, and determining a high-definition map based on a navigation map and the key node layer. The navigation map provides road-level navigation information, and the high-definition map provides lane-level navigation information.