An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

A system and method for collecting, processing, storing, or transmitting traffic data. A localized data collection module may retrieve, receive, or intercept traffic data through or from hardware installed in a traffic control cabinet adjacent an intersection or other roadway feature of interest. Data which may have previously been confined to a closed loop traffic control system may be remotely accessible for traffic operations control or monitoring via a network connected server and/or cloud architecture.

A system and method for collecting, processing, storing, or transmitting traffic data. A localized data collection module may retrieve, receive, or intercept traffic data through or from hardware installed in a traffic control cabinet adjacent an intersection or other roadway feature of interest. Data which may have previously been confined to a closed loop traffic control system may be remotely accessible for traffic operations control or monitoring via a network connected server and/or cloud architecture.

A traffic signal recognition method and a traffic signal recognition device estimate whether or not a vehicle can be decelerated at a predetermined deceleration acceleration and can stop before a stop line based on a position of the stop line corresponding to a traffic signal located in a traveling direction of the vehicle, select the traffic signal corresponding to the stop line as a target traffic signal in a case where it is estimated that the vehicle cannot stop before the stop line, set detection area corresponding to the target traffic signal on an image obtained by capturing the traveling direction of the vehicle, and determine a display state of the target traffic signal by executing image processing on the detection area.

In one embodiment, a method includes receiving an image of an object captured in a geographic location. The method includes determining the geographic location associated with the image. The geographic location is represented in a map that includes one or more ambient light measurements corresponding to one or more geographic locations. The method includes using the one or more ambient light measurements corresponding to the geographic location in the map associated with the image to generate a color corrected image. The method includes determining a classification of the object using the color corrected image.

Disclosed is a device for identifying sirens of priority vehicles and for warning a hearing-impaired driver of a motor vehicle of a presence of at least one priority vehicle in an environment of his vehicle, including at least one sound receiver, a computing unit for analyzing the audio recording and a unit for comparing the frequencies of the audio recording with frequencies previously stored in storage of the computing unit as being associated with a siren of a given priority vehicle, and for doing so for each type of priority vehicle, and at least one visual and/or vibratory element for warning the driver when a presence of a priority vehicle is detected in an environment of the motor vehicle.

Various implementations include approaches for training a surface detection classifier and detecting characteristics of a surface, along with related micromobility vehicles. Certain implementations include a method including: comparing: i) detected movement of a micromobility (MM) vehicle or a device located with a user at the MM vehicle while operating the MM vehicle, with ii) a surface detection classifier for the MM vehicle; and in response to detecting that the MM vehicle is traveling on a restricted surface type for a threshold period, performing at least one of: a) notifying an operator of the MM vehicle about the travel on the restricted surface type, b) outputting a warning at an interface connected with the MM vehicle or the device, c) limiting a speed of the MM vehicle, or d) disabling operation of the MM vehicle.

The invention relates to a method for an automated starting of a means of transport (80) at a light-signal system (70), comprising: recording an image of the light-signal system (70) by means of a first optical sensor (30) of the means of transport (80), determining a signaling state of the light-signal system (70) by means of the recorded image, executing an automated starting process of the means of transport (80) in response to a signaling state representing and/or announcing a travel clearance, determining a user action of a driver of the means of transport (80) for plausibility checking of the starting process, and depending on a result of the plausibility check, automatically continuing or terminating of the starting process.

Systems, apparatus and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may include a light emitter positioned external to a surface of the autonomous vehicle and being configured to implement a visual alert by emitting light from the light emitter. Data representing a light pattern may be received by the light emitter and the light emitted by the display may be indicative of the light pattern. The light pattern may be selected to gain the attention of the object (e.g., a pedestrian, a driver of a car, a bicyclists, etc.) in order to avoid the potential collision or to alert the object to the presence of the autonomous vehicle.

A system for location risk determination and ranking based on vehicle events and/or an accident database includes an interface and a processor. The interface is configured to receive accident data and/or event data. The processor is configured to determine a set of incident groups, wherein an incident group of the set of incident groups is associated with a set of accidents of the accident data and/or a set of events of the event data that are grouped by location proximity. The processor is further configured to determine a set of traffic estimations, wherein a traffic estimation of the set of traffic estimations is associated with the incident group of the set of incident groups; and determine a ranking of the set of incident groups based at least in part on the set of accidents, the set of events, and the set of traffic estimations.