The present disclosure generally relates to generating emergency vehicle warnings, automatic control of autonomous vehicles based upon the emergency vehicle warnings. More particularly, the present disclosure relates to generating data representative of emergency vehicle warnings and alternate autonomous vehicle routing based upon real-time information related to an emergency vehicle. The information related to the emergency vehicle may include emergency vehicle origination location data, emergency vehicle current location data, emergency vehicle route data, and/or emergency vehicle destination location data. An emergency vehicle warning and/or alternate vehicle routing for autonomous vehicles may be generated based further on information related to an autonomous vehicle. In one aspect, an emergency vehicle may wirelessly communicate with the autonomous vehicle and/or an insurance provider remote server. The insurance provider may adjust auto insurance for insured individuals, having vehicles with the vehicle safety functionality discussed herein, to reflect lower risk and provide insurance savings to customers.

Technologies disclosed herein facilitate identification of a trip route from an origin of a user to a desired destination of the user, wherein the trip route includes multiple transportation modalities, at least one of which is an autonomous vehicle (AV), and dispatching of the AV to a pickup location for the user in connection with providing transportation to the user along a portion of the identified trip route.

A method for determining a risk boundary in response to the plurality of indications of hard braking events wherein the risk boundary is indicative of a plurality of speed flow pairs at which a risk of a hard braking event is below a threshold value, determining, at a road segment level, a set of speed flow pairs of average speed and vehicle count and a plurality of indications of hard braking events , determining a host vehicle speed, and performing at least one of reducing the host vehicle speed and increasing a host vehicle following distance in response to the host vehicle speed exceeding the risk boundary for the vehicle flow density.

A system and method for predicting travel time of a vehicle on routes of unbounded length within arterial roads. It collects historical information from probe vehicles positions using GPS technology in a periodic fashion and the sequence of links traversed between successive position measurements. Further, it collects information of neighborhood structure for each link within the arterial roads network. Any of the existing conditional probability distribution functions could be used to capture the spatio-temporal dependencies between each link of the arterial network and its neighbors. It learns the parameters of this data driven probabilistic model from historical information of probe vehicle trajectories traversed within the arterial roads network using an associated expectation maximization method. Finally it predicts travel time of vehicles on routes of unbounded length in a novel fashion within the network of arterial roads using the learnt parameters and current real time information of trajectories of vehicle.

An architecture to maximize vehicular traffic flow. A method comprises receiving from database equipment a key performance indicator value representing an aggregation of connections that exist between serving equipment situated in a first vicinity of a first area and a group of user equipment traveling through the first vicinity, based on the key performance indicator value, generating a density map for the first vicinity, overlaying the density map over a group of roadways associated with the first vicinity, based on a width value associated with a roadway of the group of roadways, a defined vehicular throughput value associated with the roadway, and a demand penalty value associated with the roadway, determining a maximum vehicular throughput for the group of roadways, and based on the maximum vehicular throughput, causing a user equipment to display a ranked list of routes between the first vicinity and a second vicinity of a second area.

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Systems, methods, and computer readable media for performing task assignment, completion, and management within a crowdsourced surveillance platform. A remote server may identify targets for image capture and may assign capture tasks to users based on travel plans of the user. Users may be assigned task to capture image of target locations lying along a travel path. The remote server may aggregate data related to the captured images and use it to update a map and log changes to the target location over time.

A vehicle receives designation of a coverage area for deployment of a portable network comprised of a plurality of wireless-equipped toolboxes and determines a plurality of toolboxes available for use in the network based on indications to the vehicle from a plurality of toolboxes that they are usable in the network. The vehicle determines a placement of the available toolboxes within the coverage area to achieve a wireless network having at least one box location capable of reaching a location designated as a vehicle parking location with wireless communication, the location determined by the vehicle based at least in part on the ability of the vehicle to reach the location and a known cellular signal available at the location. The vehicle provides guidance for deployment of individual toolboxes of the plurality of toolboxes at deployment locations according to the determined placement.

An approach is provided for automatically detecting a road closure during a probe anomaly. The approach, for example, involves determining a drop in an expected vehicle volume in a geographic area over a time epoch, wherein the expected vehicle volume represents an expected number of unique vehicles traveling in the geographic area over the time epoch. The approach also involves computing an adjusted expected vehicle volume for a road segment in the geographic area based on the drop and a historical expected vehicle volume for the road segment over the time epoch. The approach further involves determining a time window comprising at least the time epoch. The approach further involves performing an automatic road closure detection on the road segment using the time window.

An automated valet parking system performs automated parking in response to a user request for entry or pick-up from a user and causes the self-driving vehicle to perform automated driving along a target route to enter or pick up. The automated valet parking system, when a self-driving vehicle stops in an emergency or experiences a communication interruption and becomes a failed vehicle, sets a restricted area based on parking place map information and a position of the failed vehicle and sets an allowed area in a parking place, including a parking space(s) located outside the restricted area, provides an instruction, based on a position of a subject vehicle that is a self-driving vehicle as a subject of the user request and the set restricted area, to the subject vehicle, and sets a target route such that the subject vehicle parks in the parking space located in the allowed area.