A system, a transportation vehicle, a network component, apparatuses, methods, and computer programs for a transportation vehicle and a network component. The method for a transportation vehicle and for verifying a proposed route includes determining an exceptional traffic situation based on an environmental model for the transportation vehicle and transmitting information related to the exceptional traffic situation to a network component using a mobile communication system. The method also includes receiving information related to a proposed route from a network component, and verifying the proposed route based on the environmental model of the transportation vehicle.

An online agricultural system manages and optimizes interactions of entities within the system to enable the execution of transaction and the transportation of crop products. The online agricultural system accesses historic and environmental data describing factors that may impact crop product transactions and/or transportation to determine market prices for crop products and crop product transportation. Responsive to receiving a request from an entity, the online agricultural system determines an optimal transaction for the entity, such as a price for selling a crop product, an available crop product for purchase, or a transportation opportunity to transport a crop product.

A simulation device that on the basis of: a traffic network (10) as a graph of route sections (3) and nodes (4), with starting places (1) and destinations (2).
so as to determine the traffic volume on the route sections (3) performs the following steps: for each starting place (1) and for each of a multiplicity of traffic participants of the starting place (1): determining allocated to each of the destinations (2) respectively a traffic participant fraction, corresponding to an allocation of the traffic participants to the destinations; determining allocated to each of the destinations (2) respectively an optimal route (6) from the starting place (1) to the destination (2); determining for each of the destinations (2) and for each route section (3) of the optimal route (6) a dwell portion (5) of the traffic participant in the route section (3) as a function of the traffic participant fraction that is allocated to this destination (2); for each of the route sections (3) of the traffic network (10): determining the traffic volume on the route section (3) by means of summating the dwell portions (5) of all traffic participants in this route section (3).

An example integrated circuit (IC) die in a multi-die IC package, the multi-die IC package having a test access port (TAP) comprising a test data input (TDI), test data output (TDO), test clock (TCK), and test mode select (TMS), is described. The IC die includes a Joint Test Action Group (JTAG) controller having a JTAG interface that includes a TDI, a TDO, a TCK, and a TMS, a first output coupled to first routing in the multi-die IC package, a first input coupled to the first routing or to second routing in the multi-die IC package, a master return path coupled to the first input, and a wrapper circuit configured to couple the TDI of the TAP to the TDI of the JTAG controller, and selectively couple, in response to a first control signal, the TDO of the TAP to either the master return path or the TDO of the JTAG controller.

The vehicle control system/method for adapting a control function based on a user profile may comprise: a gesture recognition module; a user profile module; a function control module; a processor; a non-transitory storage element coupled to the processor; encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to: identify a user; retrieve a user profile for the identified user; receive at a gesture recognition module, an input indicating a gesture from the user; identify a control function request corresponding to the gesture input; send a verification of the control function request; and receive at a function control module characteristics parsed from the user profile that effect the control function request by the user profile module to adapt a control function command for an adapted control function output by the function control module.

A local computing device receives lidar data and radar data from one or more road side units (RSUs). The local computing device performs ground plane removal based on range to detect targets and perform local sensor fusion. The local computing device may use a global nearest neighbor (GNN) algorithm and a Kalman filter. The local computing device may create an HD map or the data may be brought together with other target data at a central computing device to produce the HD map. Vehicle position and motion are controlled based on the HD map. Detecting and removing a ground plane based on range are illustrated. Fusion, ground plane removal, and delay filtering may be used in various contexts, such as roadways, parking lots and shipping yards.

An example integrated circuit (IC) die in a multi-die IC package, the multi-die IC package having a test access port (TAP) comprising a test data input (TDI), test data output (TDO), test clock (TCK), and test mode select (TMS), is described. The IC die includes a Joint Test Action Group (JTAG) controller having a JTAG interface that includes a TDI, a TDO, a TCK, and a TMS, a first output coupled to first routing in the multi-die IC package, a first input coupled to the first routing or to second routing in the multi-die IC package, a master return path coupled to the first input, and a wrapper circuit configured to couple the TDI of the TAP to the TDI of the JTAG controller, and selectively couple, in response to a first control signal, the TDO of the TAP to either the master return path or the TDO.

The vehicle control system/method for adapting a control function based on a user profile may comprise: a gesture recognition module; a user profile module; a function control module; a processor; a non-transitory storage element coupled to the processor; encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to: identify a user; retrieve a user profile for the identified user; receive at a gesture recognition module, an input indicating a gesture from the user; identify a control function request corresponding to the gesture input; send a verification of the control function request; and receive at a function control module characteristics parsed from the user profile that effect the control function request by the user profile module to adapt a control function command for an adapted control function output by the function control module.

Contemporary navigation systems are often tasked with routing a vehicle to a destination, but are poorly equipped to assist with finding a vacancy of a parking opportunity in which the vehicle may be parked. Static information, such as enumeration of parking garages and curbside parking meters, may be frustrating if such parking opportunities have no vacancies. The determination of vacancies with certainty may be difficult to achieve due to the characteristic volatility of parking, in which vacancies may be taken in seconds. Presented herein are navigation device configurations involving probabilistic evaluation of parking routes in a vicinity of a destination that may be generated and compared, optionally weighted by various factors, to identify a parking route with parking opportunities that collectively present a high probability of vacancy as compared with other parking routes, which may be presented to the user and/or appended to a current route of an autonomous vehicle.

Contemporary navigation systems are often tasked with routing a vehicle to a destination, but are poorly equipped to assist with finding a vacancy of a parking opportunity in which the vehicle may be parked. Static information, such as enumeration of parking garages and curbside parking meters, may be frustrating if such parking opportunities have no vacancies. The determination of vacancies with certainty may be difficult to achieve due to the characteristic volatility of parking, in which vacancies may be taken in seconds. Presented herein are navigation device configurations involving probabilistic evaluation of parking routes in a vicinity of a destination that may be generated and compared, optionally weighted by various factors, to identify a parking route with parking opportunities that collectively present a high probability of vacancy as compared with other parking routes, which may be presented to the user and/or appended to a current route of an autonomous vehicle.