Abstract: In a turn signal cancelation system for a two-wheeled vehicle, a controller is adapted to automatically cancel the turn signal of the vehicle upon: (a) a determined distance traveled by the vehicle after an occurrence of the predetermined operation of the vehicle exceeding a first distance threshold and a determined yaw angle traversed by the vehicle after the occurrence of the predetermined operation of the vehicle exceeding a yaw angle threshold; and (b) the determined distance traveled by the vehicle after the occurrence of the predetermined operation of the vehicle exceeding a second distance threshold, different from the first distance threshold, independent of the determined yaw angle traversed by the vehicle after the occurrence of the predetermined operation of the vehicle.

Abstract: A method for determining the position of a non-motorized road user including ascertaining a first geodetic position of the road user in a position determination device, which uses a global navigation satellite system, of the terminal, and transmitting the first geodetic position to a traffic device. In a control unit of the traffic device, ascertaining a second geodetic position of the road user from a geodetic traffic device position and a relative position ascertained from sensor data, showing the road user, of at least one surroundings sensor of the traffic device. At least if a limiting value for a deviation of the first position from the second position is exceeded, transmitting an item of deviation information describing the second position and/or the deviation from the traffic device to the mobile terminal, and using the deviation information to correct the position ascertainment in the position determination device.

Abstract: An embodiment driving assistance system for a vehicle includes a driving information provision unit configured to acquire and provide driving information of a traveling vehicle, a control unit configured to generate and output a control signal for driving assistance when it is determined the vehicle travels on a rough road based on the driving information of the vehicle provided by the driving information provision unit and it is determined that the vehicle is currently in a rough road traveling state, and a steering actuator configured to generate and apply a steering assistance force according to a control value of the control signal for the driving assistance output by the control unit to a steering wheel.

Abstract: A method for deploying of a backup roadside unit (RSU) vehicle to provide on-demand RSU services is described. The method may include determining, by a server, a resource specification to deploy a selected backup RSU vehicle to a requested site. The determining of the resource specification may be performed by the server in response to a scene description received from a requestor. The method also includes sending a dispatch instruction to the selected backup RSU vehicle to deploy the selected backup RSU vehicle to the requested site. In this method, a hardware/software capability of the selected backup RSU vehicle is matched to the resource specification determined by the server.

Abstract: Techniques are disclosed for evaluating an autonomous vehicle (“AV”) control system by determining deviations between data generated using the AV control system and manual driving data. In many implementations, manual driving data captures action(s) of a vehicle controlled by a manual driver. Additionally or alternatively, multiple AV control systems can be evaluated by comparing deviations for each AV control system, where the deviations are determined using the same set of manual driving data.

Abstract: Various technologies described herein pertain to autonomous vehicle consumption of real-time public transportation data to guide curb access and usage. An autonomous vehicle receives a trip request for a ride specifying a requested pullover location. The autonomous vehicle receives public transportation data specifying an expected arrival time of a public transportation vehicle at a reserved zone within proximity of the requested pullover location. The autonomous vehicle evaluates availability of the reserved zone during an expected occupancy time of the reserved zone by the autonomous vehicle based on the expected arrival time of the public transportation vehicle at the reserved zone. The autonomous vehicle selects an actual pullover location for the ride in the autonomous vehicle based on the availability of the reserved zone during the expected occupancy time. The autonomous vehicle stops at the actual pullover location for the ride in the autonomous vehicle.

Abstract: The disclosure generally pertains to systems and methods for using vehicles to detect and remediate air pollution. In an example implementation, a server computer transmits a directive to a vehicle controller of a vehicle, to measure an air pollution level around the vehicle at a first location. The vehicle controller executes an air pollution measurement and transmits measurement data to the server computer. The server computer evaluates the measurement data and directs the vehicle controller to perform a remedial action for reducing the air pollution level at the first location. The remedial action can involve, for example, the vehicle controller moving the vehicle from the first location to a second location. The server computer may also determine whether the first location is a transient pollution location or a persistent pollution by directing the vehicle controller to carry out measurements at two different times and/or by employing two different sampling rates.

Abstract: The invention provides designs and methods for a heavy vehicle operations and control system for heavy automated vehicles, which facilitates heavy vehicle operation and control for connected automated vehicle highway (CAVH) systems. The heavy vehicle management system provides heavy vehicles with individually customized information and real-time vehicle control instructions to fulfill the driving tasks such as car following, lane changing, route guidance. The heavy vehicle management system also realizes heavy vehicle related lane design, transportation operations, and management services for both dedicated and non-dedicated lanes. The heavy vehicle management system consists of one or more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicles and onboard units (OBU), (4) traffic operations centers (TOCs), and (5) cloud platform.

Abstract: When having determined that an own-vehicle has become unable to proceed in a traveling direction corresponding to a travel path of the own-vehicle and has stopped halfway through a travel path, a parking support device transmits information to an operation terminal, the information indicating a travel path and a place at which the vehicle has stopped on the travel path. When having received, from the operation terminal, specification information specifying a place to which the own-vehicle is to be moved, the parking support device sets, as a travel path of the own-vehicle, a path through which the own-vehicle is to be moved to the specified place, and outputs, to a vehicle control unit, control information for causing the own-vehicle to move to the specified place.

Abstract: Methods and systems are provided for guiding or otherwise assisting operation of an aircraft en route to an airport. One method involves identifying a reference point in advance of a runway, dynamically determining a gliding vertical trajectory for the aircraft en route to the reference point based at least in part on a current altitude of the aircraft at a current aircraft location and gliding characteristics of the aircraft, and providing a graphical indication of a difference between a predicted altitude of the aircraft at a location corresponding to the reference point resulting from the gliding vertical trajectory and an altitude criterion associated with the reference point. The graphical indication of the difference dynamically updates as the aircraft travels.

Abstract: An approach is provided for providing probe data accuracy while ensuring privacy. The approach includes receiving probe path consisting of multiple points from a vehicle, wherein each probe point includes a location of the vehicle and a timestamp indicating when the location was determined by a location sensor. The approach further includes determining a vehicle identifier from among a plurality of vehicle identifiers assigned to the vehicle based on the timestamp, wherein the plurality of vehicle identifiers are applicable for assigning at different respective time slots. The approach also involves generating a hashed vehicle identifier by using a hash function on the determined vehicle identifier and the timestamp. The approach also involves reporting the probe point using the hashed vehicle identifier to identify the probe point.

Abstract: A method for controlling traffic by a traffic control system includes transmitting, to a first traffic control vehicle, a first message requesting the first traffic control vehicle to autonomously navigate to a location corresponding to a traffic incident. The method also includes monitoring a location of the first traffic control vehicle based on receiving location information from the first traffic control vehicle. The method also includes transmitting, to the first traffic control vehicle, first information to be displayed via a first notification device integrated with the first traffic control vehicle based on the location information corresponding to the location of the traffic incident. The method still further includes transmitting, to the first traffic control vehicle after a period of time, a request to navigate away from the location of the traffic incident.

Abstract: A method for supporting an attentiveness and/or driving readiness of a driver during automated driving operation of a vehicle, including computing a failure probability value using at least one read-in map information signal, environmental condition signal, and/or probability signal. The failure probability value represents a failure probability of a driver assistance system for performing an automated driving operation. The probability signal represents an error probability and/or failure probability of at least one vehicle sensor of the driver assistance system. The method also includes determining a comparison parameter in response to the computed failure probability value, the comparison parameter representing the result of a comparison of an extent of a necessary driving requirement on the traveled travel route of the vehicle to a degree of instantaneous driver attentiveness. The method also includes providing an advance warning signal in response to the determined comparison parameter.

Abstract: A method and a device for determining braking-related actual values of a train assembly including multiple carriages for carrying out a deceleration-controlled braking of the train assembly, in which the longitudinal deceleration and the longitudinal slope are considered to be actual values, from which an adjustment value balancing the control deviation is determined for a control element of the brake by a deceleration controller/deceleration force controller according to a predefined setpoint value of a desired braking deceleration.

Abstract: Example techniques are described for determining a dynamic traffic-management plan based on factors such as predicted increases in traffic and known-structurally-deficient transportation infrastructure. Traffic patterns may be re-routed, particularly during high-congestion events, to reduce or avoid excessive weight loads travelling across weakened sections of roads, bridges, or the like.

Abstract: From a set of point data, a set of scattered rays is constructed. From the set of scattered rays, a set of ray slopes is computed. The set of ray slopes is mapped to a corresponding set of trigonometric functions. Using an optimization method, a parameter of the set of trigonometric functions is selected. Using an inverse of the set trigonometric functions, a vehicle mass corresponding to the set of point data is computed. Based on the vehicle mass, a threshold braking distance of a collision avoidance system of the vehicle is adjusted, the threshold braking distance comprising a distance from an object predicted to collide with the vehicle. By braking the vehicle at least the threshold braking distance from the object, a predicted collision between the vehicle and the object is avoided.

Abstract: Some embodiments of the present invention comprise a method of controlling a powertrain of a vehicle, the powertrain comprising drive torque means, a transmission and a driveline, the drive torque means comprising an internal combustion engine, the method comprising: detecting that coasting entry criteria have been met; causing the powertrain to assume a first coasting mode for a first time period in which the drive torque means delivers positive drive torque to the driveline to substantially balance powertrain losses; determining a value for at least one parameter, the or each parameter being indicative of: a probability that a demand will be made for torque to be delivered to the driveline in addition to torque delivered to substantially balance powertrain losses; or a probability that a demand will be made for braking of the vehicle; and setting the value of the first time period in dependence on the value of the or each parameter.

Abstract: Methods, apparatus, computer program products Geohash-based traffic management are provided. The method comprises receiving, by one or more processing units, respective operating status data of one or more vehicles travelling within a Geohash cell; generating, by one or more processing units, one or more service messages based on the received respective operating status data according to one or more service specifications; and providing, by one or more processing units, at least one of the one or more service messages responsive to a request from a vehicle travelling within the Geohash cell.

Abstract: An amusement park system in accordance with present embodiments includes multiple separated park areas, an autonomous vehicle configured to drive along ground surfaces within the multiple separated park areas, and a gondola system configured to transport the autonomous vehicle between the multiple separated park areas. The amusement park system further includes a control system configured to operate the autonomous vehicle to engage with and disengage from the gondola system to facilitate transport of the autonomous vehicle by the gondola system.

Abstract: A vehicle learning system includes a first execution device mounted on a vehicle, a second execution device outside the vehicle, and a storage device. The storage device stores mapping data including data, which is learned by machine learning and defines mapping that receives input data based on a detection value of an in-vehicle sensor and outputs an output value. The first execution device and the second execution device execute, in cooperation with each other, an acquisition process of acquiring input data, a calculation process of calculating an output value with the input data as an input of the mapping, and a relationship evaluation process of evaluating a relationship between a predetermined variable different from a variable corresponding to the output value and accuracy of the output value. The first execution device executes at least the acquisition process, and the second execution device executes at least the relationship evaluation process.