Abstract: A method of correcting a GPS vehicle trajectory of a vehicle on a roadway for a high-definition map is provided. The method comprises receiving first bitmap data from a first sensor of a first vehicle to create a plurality of first multi-layer bitmaps for the first vehicle using the first bitmap data and receiving second bitmap data from a plurality of second sensors of a plurality of second vehicles to create a plurality of second multi-layer bitmaps. The method further comprises creating first probability density bitmaps and an overall probability density bitmap with a probability density estimation, and matching an image template from each of the first probability density bitmaps with the overall probability density bitmap to define match results. The method further comprises combining the match results to define combined utility values and determining the maximal utility value with the combined utility values.

Abstract: An automatic lane change activation system includes a host vehicle including an in-vehicle computer. A telematics module communicates global positioning system (GPS) data between the computer and the telematics module. A host vehicle display device receives signals from the computer. A visual system status is presented to a host vehicle user by the display device including an information screen presenting a roadway information message, a control screen presenting an opportunity message identifying to the user an opportunity to switch the host vehicle from a first roadway lane into a second roadway lane, and a lane change directional arrow to indicate a path for the host vehicle to take. A motion control module in the host vehicle receives control signals from the computer including a lane change execution signal to initiate and control vehicle automatic lane changes in a non-congested area of a roadway for the host vehicle.

Abstract: A method of creating a high-definition (HD) map of a roadway includes receiving a multi-layer probability density bitmap. The multi-layer probability density bitmap represents a plurality of lane lines of the roadway sensed by a plurality of sensors of a plurality of vehicles. The multi-layer probability density bitmap includes a plurality of points. The method further includes recursively conducting a hill climbing search using the multi-layer probability density bitmap to create a plurality of lines. In addition, the method includes creating the HD map of the roadway using the plurality of lines determined by the hill climbing search.

Abstract: A system for estimating cloud cover from moving vehicles includes: vehicle mounted sensors communicating with one or more control modules. The control modules have processors, memory, and input/output (I/O) ports. The I/O ports of the control modules of the vehicles communicate with the sensors. The control modules execute program code stored in the memory including first and second algorithm portions. The first algorithm portion, collects sensor data from the sensors, estimates atmospheric parameters from the sensor data; and computes measurement coordinates from the sensor data and atmospheric parameters. The second algorithm portion generates and selectively updates a cloud map based on from data received from the first algorithm portion, and from high-definition map (HD Map) data.

Abstract: A method includes receiving sensor data from a plurality of sensors of a plurality of vehicles. The sensor data includes vehicle GPS data and sensed lane line data of the roadway. The method further includes creating a plurality of multi-layer bitmaps for each of the plurality of vehicles using the sensor data, fusing the plurality of the multi-layer bitmaps of each of the plurality of vehicles to create a fused multi-layer bitmap, creating a plurality of multi-layer probability density bitmaps using the fused multi-layer bitmap, extracting lane line data from the plurality of multi-layer probability density bitmaps, and creating the high-definition (HD) map of the roadway using the multi-layer probability density bitmaps and the lane line data extracted from the plurality of multi-layer probability density bitmaps.

Abstract: A system to locate seat controls and belt buckles includes a vehicle having at least one seat. A seat belt system is provided with the at least one seat having a seat belt, a belt latch and a seat belt buckle. A haptic device is provided with the seat belt system, the haptic device generating a haptic signal.

Abstract: An event scheduling system for collecting image data related to one or more events by one or more autonomous vehicles includes a centralized scheduling system in wireless communication with one or more autonomous vehicles. Each autonomous vehicle collects the image data related to the one or more events while following a unique travel schedule. The centralized scheduling system executes instructions to determine the unique travel schedule for a specific autonomous vehicle, where the unique travel schedule directs the specific autonomous vehicle to the specific location of the filtered event to collect the image data.

Abstract: An ego vehicle includes a system having one or more input devices for generating an input signal associated with a remote vehicle. The system further includes a computer having one or more processors programmed to receive the input signal from the input device. The processor is further programmed to determine a speed profile of the remote vehicle based on the input signal, determine that the remote vehicle is a traffic impediment based on the input signal, and determine a predicted slowdown event associated with the traffic impediment and the speed profile. The processor is further programmed to generate an actuation signal, in response to the processor determining the speed profile, the traffic impediment, and the predicted slowdown event. The notification device provides the notification of the predicted slowdown event to a user in response to the notification device receiving the actuation signal from the processor.

Abstract: A system is provided for mitigating a road network congestion. The system includes a plurality of motor vehicles positioned in associated locations in a road network. Each vehicle has one or more sensors generating an input and a Telematics Control Unit (TCU) for generating at least one location signal for a location of the associated motor vehicle and at least one event signal for an event related to the associated motor vehicle, with the location signal and the event signal corresponding to a High Speed Vehicle Telemetry Data (HSVT data) based on the input from the sensors. The system further includes a computer, which communicates with a display device and the TCUs. The computer includes a processor and a computer readable medium including instructions, such that the processor is programmed to identify the congestion and determine that the congestion is a recurring or a non-recurring congestion.

Abstract: According to one or more examples, a system includes an observer vehicle, and a vehicle in a predetermined vicinity of the observer vehicle. The observer vehicle detects an operating condition of the vehicle using one or more perception devices. The observer vehicle determines that the operating condition does not satisfy a predetermined norm. The observer vehicle generates a message indicating the operating condition of the vehicle. The observer vehicle identifies a communication identifier of the vehicle. The observer vehicle sends the message to be received by the vehicle using the communication identifier via a vehicle to everything (V2X) communication module.

Abstract: An energy management system for an electric autonomous vehicle comprises a battery and a controller comprising a processor and a non-transitory computer-readable medium. The system comprises a pre-allocation input mechanism transmitting an input signal to the processor relating to a travel destination for the vehicle. The system comprises a navigation module receiving a wireless signal from a satellite network relating to a current location of the vehicle. The system comprises an autonomous input mechanism powered by the battery and transmitting an autonomous signal to the processor relating to dynamic conditions for autonomous operation of the vehicle. The processor determines a route between the current location and the travel destination, performs autonomous operation of the vehicle along the route, and selectively powers or tunes the usage of the at least one autonomous input mechanism with the battery during autonomous operation of the vehicle.

Abstract: A distributed computing system for determining road surface traction capacity for roadways located in a common spatio-temporal zone includes a plurality of vehicles that each include a plurality of sensors and systems that collect and analyze a plurality of parameters related to road surface conditions in the common spatio-temporal zone. The distributed computing system also includes one or more central computers in wireless communication with each of the plurality of vehicles. The one or more central computers execute instructions to determine a road surface traction capacity value for the common spatio-temporal zone.

Abstract: A system, method and server for a controlling a relation between a vehicle and traffic flow over a road segment. The system includes a telemetric device of the vehicle and a processor of the server. The telemetric device obtains telemetric data related to the road segment being traversed by the vehicle. The processor determines a property of the road segment based on the telemetric data and a road profile for the road segment, determines a disruption score indicative of a level of disruption in the traffic flow for the road segment based on the property, and outputs a notification signal when the disruption score is above a selected disruption threshold. The notification signal is usable for controlling the relation between the vehicle and the traffic flow.

Abstract: A system for providing route guidance based on road brightness metrics includes a primary vehicle having an on-board data processor, a driver interface in communication with the on-board data processor and adapted to allow a driver to interact with the on-board data processor, and a wireless communication module, a cloud-based data processor adapted to collect real-time road brightness data from the primary vehicle and a plurality of other vehicles and to store collected data and build a model of road brightness metrics, the cloud-based data processor further adapted to receive data related to a starting position and final destination, calculate brightness characteristics for a shortest path route and at least one viable alternate route between the starting point and the final destination, and present to a driver of the primary vehicle the at least one viable alternate route which satisfies pre-determined brightness preferences better than the shortest path route.

Abstract: A system for providing weather conditions to a target vehicle includes a plurality of sensors mounted within the target vehicle adapted to measure weather conditions at the target vehicle and a computer processor adapted to collect data of weather conditions at the target vehicle from the plurality of sensors mounted within the target vehicle, collect data of measured weather conditions of at least one known location remote from the target vehicle, and build a temporal-spatial effectiveness model adapted to estimate weather conditions of at least one unknown location remote from the target vehicle using the data of weather conditions at the target vehicle and the data of measured weather conditions of the at least one known location remote from the target vehicle.

Abstract: A driver monitoring system configured to monitor the performance of a driver of a vehicle communicating wirelessly with the driver monitoring system. The system comprises a driver behavior module that receives from the vehicle event data captured by a plurality of sensors in the vehicle and identifies at least one of a plurality of driver behaviors. A behavior characterization module receives from the driver behavior module the at least one identified driver behavior and characterizes the at least one identified driver behavior into at least one of a plurality of behavior categories. A risk assessment module analyzes the at least one characterized driver behavior in the plurality of behavior categories and determines therefrom a driver profile that may include a risk assessment for the driver of the vehicle system.

Abstract: A one pedal driving system for an electric vehicle including one or more electric motors includes a controller in wireless communication with one or more external vehicle networks. The controller executes instructions to receive, from the one or more external vehicle networks, an active zone notification that indicates the electric vehicle is traveling into a one pedal driving zone. The one pedal driving zone represents a section of roadway where the electric vehicle decelerates from an initial speed. The controller executes instructions to receive a pedal notification that a driver foot is removed from an accelerator pedal of the electric vehicle. In response to receiving the active zone notification and the pedal notification, the controller instructs the electric vehicle to decelerate from the initial speed by a regenerative braking torque that is created by the one or more electric motors to counteract a forward momentum of the electric vehicle.

Abstract: A first closed lane segment file including a first lane change histogram and a lane closure start point associated with a closed lane segment of a first lane of a road is received from a lane change data aggregation system at a lane change management system. The first lane change histogram includes a distribution of a plurality of lane change points received from vehicles that previously engaged in a lane change from the first lane to a second lane of the road in response to the closed lane segment. A lane change control point is determined based on the first lane change histogram at the lane change management system. A command is issued from the lane change management system to an ADS of the autonomous vehicle to initiate a lane change from the first lane to the second lane at the lane change control point.

Abstract: A system for predicting a door opening event of a vehicle includes an identity recognition device associated with an individual occupant profile. The system also includes one or more controllers in electronic communication with the identity recognition device, where the one or more controllers store one or more individual occupant profiles in memory of the one or more controllers that includes historical occupant behavior exhibited by one or more occupants associated with the identity recognition device. The one or more controllers execute instructions to determine a predetermined condition has occurred, where the predetermined condition indicates the vehicle is undergoing a potential engine off event. The one or more controllers determine a door opening event probability value based on at least the gear position probability value and the engine off probability value.

Abstract: A sequence of images and a vehicle location associated with each of the images is received at a traffic light ROI management system. At least one traffic light is detected in each image. A ECS traffic light ROI is defined for each image. The ECS traffic light ROI encloses the detected traffic lights. A visual feature template is generated for each image. The visual feature template is based on the ECS traffic light ROI for the image. Each visual feature template is mapped to the vehicle location associated with the image to a HD map. The HD map is transmitted to an autonomous vehicle to enable the autonomous vehicle to identify a real-time traffic light ROI in a real-time image based on a match between a first visual feature template and real-time visual features of the real-time image at the vehicle location associated with the first visual feature template.