A system for associating perceived and mapped lane edges can include a processor and a memory. The memory includes instructions such that the processor is configured to receive a sensor data representing a perceived object; receive map data representing a map object; determine a cost matrix a cost matrix indicative of an association cost for associating the map object to the perceived object; compare the association cost with an association cost threshold; and associate the perceived object with the map object based on the association cost.

Systems and methods for an On-Demand Autonomy (ODA) service. The system includes a selection module of a leader vehicle (Lv) connected to an ODA server to determine whether to confirm a request for an on-demand autonomy (ODA) service which has been broadcast wherein the ODA service request includes control of a follower vehicle (Fv) to a requested location by creating a virtual link between the Lv and the Fv to configure a vehicle platoon to enable transport of the Fv by the Lv wherein the vehicle platoon is a linking of the Lv to the Fv via the virtual link to enable the Lv to assume the control of the Fv to the requested location.

A computer-implemented method and computer program product for directing a driver of an electric vehicle to a point of interest and a charging station in close proximity to the point of interest. The method includes the steps of: (a) receiving from a user a requested activity of interest; (b) identifying one or more points of interest matching the requested activity of interest and that are within a pre-determined point of interest range from the electric vehicle; (c) identifying charging stations within a pre-determined station distance from each of the identified points of interest; and (d) presenting to the user the identified points of interest having an identified charging station within the pre-determined station distance. The computer program is configured to perform the aforementioned steps.

A system for generating linear feature data is provided. The system may determine, from sensor data, detection data associated with at least one link. The at least one link comprises a plurality of sub links. The system may further determine, using map data, one or more linear feature clusters for each of the plurality of sub links, based on the detection data. Furthermore, the system may determine a plurality of linear feature groups for the at least one link, based on at least one set of feature matched distances and the determined linear feature clusters, where a given linear feature group respectively comprises at least one first linear feature cluster associated with a first sub link and at least one second linear feature cluster associated with a second sub link. Furthermore, the system may generate the linear feature data, based on the plurality of linear feature groups.

Implementations of various methods and systems for creating and calculating a transportation capacity unit index and trading derivative products based thereon to transact and trade transportation seats or freight or transportation capacity units and resulting financial swap, futures, forwards and option structures in airline transport, subway transport, train transport, automobile transport, autonomous vehicle transport, taxi transport, space transport, package freight transport, tractor trailer freight transport, cargo freight transport, container freight transport, virtual transport, underground transport, ship or sea transport, public transport, private transport or drone transport on a computer, mobile computer device, audio computer device, virtual reality computer device or mixed reality computing device.

A method includes determining a first route from a first location to a second location using a first map that includes first map elements, wherein the first route includes a series of the first map elements from the first map. The method also includes matching the series of the first map elements from the first route to second map elements from a second map to define a subset of the second map elements, and determining a second route from the first location to the second location using the subset of the second map elements. The second route is constrained to the subset of the second map elements and the second route includes a series of the second map elements from the subset of the second map elements. The method also includes outputting information describing the second route for at least one of storage or display.

A method includes determining a first route from a first location to a second location using a first map that includes first map elements, wherein the first route includes a series of the first map elements from the first map. The method also includes matching the series of the first map elements from the first route to second map elements from a second map to define a subset of the second map elements, and determining a second route from the first location to the second location using the subset of the second map elements. The second route is constrained to the subset of the second map elements and the second route includes a series of the second map elements from the subset of the second map elements. The method also includes outputting information describing the second route for at least one of storage or display.

Systems and methods for providing product samples to users in autonomous vehicles, thereby allowing businesses to advertise their products via the rideshare platform. A physical advertising platform is provided leveraging existing rideshare and delivery infrastructure to allow businesses to advertise their products by providing samples in rideshare vehicles and/or with rideshare vehicle deliveries. Consumers have the opportunity to try new products from local businesses that they may otherwise not be exposed to. In some implementations, a rideshare application interface can allow users to see what new local product samples are available. In some examples, a user can select one or more product samples to try.

Systems and methods in accordance with aspects of this disclosure may be provided to determine and calculate an overall driving risk index value corresponding to a driver and scene configuration. The overall driving risk index value may provide driving risk modeling and estimation at a personalized driving level. In some cases, the overall driving risk index value may be determined using a risk-predictive modeling system with weighting and machine learning and may include one or more of: a driver score system, a driver-contextual risk score system, and a conflict index system.

A parking cruise request is received. A network version starting segment is identified and a route determination algorithm is expended starting at the network version starting segment. When the route determination algorithm is expanded to a new segment, a cost value is determined for the new segment based at least on the likelihood of finding parking on the new segment. Responsive to determining that the likelihood of finding parking along the cruise route does satisfy the threshold probability requirement, map version agnostic identifiers for each segment of the cruise route are generated. Each of the map version agnostic identifiers are coded using at least one coding function to generate coded map version agnostic identifiers. A bloom filter having the coded map version agnostic identifiers as members is generated. A parking cruise route response comprising the bloom filter is provided such that a mobile apparatus receives the parking cruise route response.