Abstract: Described herein is a method of determining a current location speed limit in a road vehicle (1) speed limit information system (20). The method comprises receiving (6): one or more signals corresponding to respective candidate speed limits (7); and one or more signals related to observed vehicle dynamics affecting changes (8) in one or more vehicles (1, 5) pre and post a most recently passed anticipated speed limit change location (2). It further comprises evaluating (9) the confidence of the different candidate speed limits (7) based on the signals related to observed vehicle dynamics affecting changes (8) and validating (10a) or discarding (10b) candidate speed limits (7) based on the evaluated confidences. A signal (13) corresponding to a highest confidence validated speed limit is output.

Abstract: Described herein is a method of determining a current location speed-limit in a road-vehicle (1) speed-limit information system (2). One or more signals (3, 4) corresponding to respective candidate speed-limits for the current location are received. A parametrized heuristic algorithm with an associated cost function is applied (7) to decide which candidate speed-limit (3, 4), if any, that is applicable. If available for the current location, a cloud service (8) supplied estimated true speed-limit (9) and an associated confidence in this estimate is received. An online learning or a reinforcement learning method is used to, based on the cloud service (8) supplied estimated true speed-limit (9) and the associated confidence in that estimate, constantly fit (10) the heuristic's parametrization to, with a high confidence, reproduce the cloud service (8) supplied estimated true speed-limit (9). A speed-limit information signal (11) corresponding to the decision of the parametrized heuristic algorithm is output.

Abstract: Described herein is a method of determining a current location speed-limit in a road-vehicle (1) speed-limit information system (2). One or more signals (3, 4) corresponding to respective candidate speed-limits for the current location are received. A parametrized heuristic algorithm with an associated cost function is applied (7) to decide which candidate speed-limit (3, 4), if any, that is applicable. If available for the current location, a cloud service (8) supplied estimated true speed-limit (9) and an associated confidence in this estimate is received. An online learning or a reinforcement learning method is used to, based on the cloud service (8) supplied estimated true speed-limit (9) and the associated confidence in that estimate, constantly fit (10) the heuristic's parametrization to, with a high confidence, reproduce the cloud service (8) supplied estimated true speed-limit (9). A speed-limit information signal (11) corresponding to the decision of the parametrized heuristic algorithm is output.

Abstract: An information sharing system derives from a roadway vehicles management system position-related data of a roadway vehicle along a road and determines a roadway vehicle timing at or during which the roadway vehicle is estimated to arrive at or cross a railway crossing. The information sharing system further derives from a railway vehicles management system position-related data of a railway vehicle along the railway and determines a railway vehicle timing at or during which the railway vehicle is estimated to arrive at or have passed the railway crossing. The information sharing system determines, based on comparing a roadway vehicle time window to a railway vehicle time window, that the roadway vehicle time window and the railway vehicle time window at least partly overlap. The information sharing system provides information associated with the overlap to the roadway vehicle or the railway vehicle.

Abstract: Described herein is a method of determining a current location speed limit in a road vehicle (1) speed limit information system (20). The method comprises receiving (6): one or more signals corresponding to respective candidate speed limits (7); and one or more signals related to observed vehicle dynamics affecting changes (8) in one or more vehicles (1, 5) pre and post a most recently passed anticipated speed limit change location (2). It further comprises evaluating (9) the confidence of the different candidate speed limits (7) based on the signals related to observed vehicle dynamics affecting changes (8) and validating (10a) or discarding (10b) candidate speed limits (7) based on the evaluated confidences. A signal (13) corresponding to a highest confidence validated speed limit is output.

Abstract: The present disclosure relates to a method for determining a road work area characteristic set comprising at least one characteristic associated with a road work area. The method comprises: determining a starting position of the road work area, receiving actual vehicle status information from each vehicle in a vehicle set, wherein each vehicle in the vehicle set has passed or is determined to pass the starting position of the road work area, the actual vehicle status information being generated by an individual generation component associated with the vehicle, the actual vehicle status information comprising vehicle position data for the vehicle, determining an actual vehicle status information set from the actual vehicle status information of each vehicle in the vehicle set, and determining the road work area characteristic set using the actual vehicle status information set.

Abstract: A suitability determining system for establishing whether a road section is suitable for at least semi-autonomous vehicle driving is described. The system identifies a road section including at least one lane and delimited by at least one lateral road boundary, and derives from at least a first estimate providing vehicle a respective utilization direction estimate along with a corresponding respective detection confidence value for each of respective lanes detected by the estimate providing vehicle along the road section.

Abstract: The present disclosure relates to a method for determining a road work area characteristic set comprising at least one characteristic associated with a road work area. The method comprises: determining a starting position of the road work area, receiving actual vehicle status information from each vehicle in a vehicle set, wherein each vehicle in the vehicle set has passed or is determined to pass the starting position of the road work area, the actual vehicle status information being generated by an individual generation component associated with the vehicle, the actual vehicle status information comprising vehicle position data for the vehicle, determining an actual vehicle status information set from the actual vehicle status information of each vehicle in the vehicle set, and determining the road work area characteristic set using the actual vehicle status information set.

Abstract: An information sharing system derives from a roadway vehicles management system position-related data of a roadway vehicle along a road and determines a roadway vehicle timing at or during which the roadway vehicle is estimated to arrive at or cross a railway crossing. The information sharing system further derives from a railway vehicles management system position-related data of a railway vehicle along the railway and determines a railway vehicle timing at or during which the railway vehicle is estimated to arrive at or have passed the railway crossing. The information sharing system determines, based on comparing a roadway vehicle time window to a railway vehicle time window, that the roadway vehicle time window and the railway vehicle time window at least partly overlap. The information sharing system provides information associated with the overlap to the roadway vehicle or the railway vehicle.

Abstract: A suitability determining system for establishing whether a road section is suitable for at least semi-autonomous vehicle driving is described. The system identifies a road section including at least one lane and delimited by at least one lateral road boundary, and derives from at least a first estimate providing vehicle a respective utilization direction estimate along with a corresponding respective detection confidence value for each of respective lanes detected by the estimate providing vehicle along the road section.