Abstract:
One or more techniques and/or systems are provided for notifying drivers to assume manual vehicle control of vehicles. For example, sensor data is acquired from on-board vehicles sensors (e.g., radar, sonar, and/or camera imagery of a crosswalk) of a vehicle that is in an autonomous driving mode. In an example, the sensor data is augmented with driving condition data aggregated from vehicle sensor data of other vehicles (e.g., a cloud service collects and aggregates vehicle sensor data from vehicles within the crosswalk to identify and provide the driving condition data to the vehicle). The sensor data (e.g., augmented sensor data) is evaluated to identify a driving condition of a road segment, such as the crosswalk (e.g., pedestrians protesting within the crosswalk). Responsive to the driving condition exceeding a complexity threshold for autonomous driving decision making functionality, a driver alert to assume manual vehicle control may be provided to a driver.
Abstract:
One or more techniques and/or systems are provided for estimating parking occupancy. For a paid parking period, parking meter transaction data may be acquired for a parking meter encompassed by a zone of one or more parking spaces. The parking meter transaction data may be evaluated to determine status data, such as an estimation of whether one or more parking spaces are available, occupied, and/or will become available. A parking occupancy, indicative of a likelihood of available parking spaces, may be estimated based upon the status data. For a free parking period, the parking occupancy may be estimated based upon vehicle flow data that is indicative of vehicles entering, parking, and/or leaving the one or more parking spaces. In this way, the parking occupancy may be provided to a driver to mitigate wasted time and/or gas otherwise spent searching for an available parking space.
Abstract:
One or more techniques and/or systems are provided for determining a scaled flow rate of traffic for a road segment. For example, probe flow rate information is determined based upon locational information from one or more probe vehicles on a road segment (e.g., a flow rate of probe vehicles corresponding to a sum of probe vehicles identified from time stamped global positioning system coordinates provided by the probe vehicles). Satellite imagery of the road segment is analyzed to identify a count of vehicles on the road segment. Scale factor and offset information is estimated based upon the probe flow rate information and the count of vehicles. The scale factor and offset information is used to scale the probe flow rate information to determine a scaled flow rate that may be a relatively accurate flow rate of traffic, which may correspond to an inferred traffic volume along the road segment.
Abstract:
Various types of vehicle navigation may facilitate a driver of a vehicle, including lane suggestions (e.g., a message indicating that the current route of the vehicle involves an exit from the rightmost lane of a causeway). A device may be configured to formulate lane change suggestions by detecting a current lane of the driver; comparing the travel conditions of the current lane with the travel conditions of other lanes of the causeway; and presenting a lane change suggestion of another lane presenting advantageous travel conditions as compared with the current lane. The inclusion of the current lane in the selection and formulation of lane change suggestions may improve the relevance of the suggestions (e.g., presenting lane change suggestions only if the travel condition of another lane is advantageous over the current lane, and presenting lane change suggestions relative to the current lane, e.g., “move two lanes to the left”).
Abstract:
Techniques are described for generating and using information regarding road traffic in various ways, including by obtaining and analyzing road traffic information regarding actual behavior of drivers of vehicles on a network of roads. Obtained actual driver behavior information may in some situations be analyzed to identify decision point locations at which drivers face choices corresponding to possible alternative routes through the network of roads (e.g., intersections, highway exits and/or entrances, etc.), as well as to track the actual use by drivers of particular paths between particular decision points in order to determine preferred compound links between those decision point locations. The identified and determined information from the analysis may then be used in various manners, including in some situations to assist in determining particular recommended or preferred routes of vehicles through the network of roads based at least in part on actual driver behavior information.
Abstract:
One or more techniques and/or systems are provided for to creating an avoidance zone spatially proximate a venue, where the avoidance zone is created based upon identifying road segments where increased traffic congestion is expected due to an event at the venue. Information pertaining to the avoidance zone, such as a description of road segments to avoid and/or expected travel delays, may be provided to a route planner configured to develop vehicle routes. In this way, the route planner can take into consideration the impact of events on one or more road segments when planning a route.
Abstract:
One or more techniques and/or systems are provided for managing traffic, such as road traffic. When a traffic authority indicates a desire to reduce load on a route or within a particular geographic zone, an offer is provided to a group of one or more users. The offer is indicative of a reward provided to the users in return for avoiding the route during a specified time window. If a user accepts the offer, movement of the user is monitored during the specified time window to verify that the user avoided the route, in which case the reward is provided to the user. If an insufficient number of offers are accepted (e.g., to achieve a desired load reduction), the offer communicated to the users is adjusted (e.g., to increase an incentive for users to accept the offer). Outstanding offers are revoked once a sufficient number of offers are accepted (e.g., to achieve the desired load reduction).
Abstract:
Among other things, one or more techniques and/or systems are provided for authorizing an action using vehicle identification information (e.g., supplied by a vehicle) and user identification information (e.g., supplied by a mobile device associated with a user of the vehicle). Such an action may relate to, among other things, refueling the vehicle, parking the vehicle, using a fee-based road segment, and/or other vehicle-centric actions, for example. Moreover, in one embodiment, as part of the authorization, a payment transaction may be initiated by an authorization system configured to authorize the action.
Abstract:
One or more techniques and/or systems are provided for notifying drivers to assume manual vehicle control of vehicles. For example, sensor data is acquired from on-board vehicles sensors (e.g., radar, sonar, and/or camera imagery of a crosswalk) of a vehicle that is in an autonomous driving mode. In an example, the sensor data is augmented with driving condition data aggregated from vehicle sensor data of other vehicles (e.g., a cloud service collects and aggregates vehicle sensor data from vehicles within the crosswalk to identify and provide the driving condition data to the vehicle). The sensor data (e.g., augmented sensor data) is evaluated to identify a driving condition of a road segment, such as the crosswalk (e.g., pedestrians protesting within the crosswalk). Responsive to the driving condition exceeding a complexity threshold for autonomous driving decision making functionality, a driver alert to assume manual vehicle control may be provided to a driver.
Abstract:
Techniques are described for using information regarding road traffic and other types of transportation-related information to determine and/or assess alternative inter-modal passenger travel options in a geographic area that supports multiple modes of transportation. For example, a particular user may have multiple alternatives for travel from a starting location to a destination location in the geographic area, including to use alternative modes of transportation (e.g., private vehicle, bus, train, walking, etc.) for some or all of the travel, and these alternatives may have different travel-related characteristics in different situations (e.g., depending on current road traffic; mass transit schedules and current actual deviations; travel-related fees for gas, parking, mass transit, etc; parking availability; etc.). Multiple alternative travel options are thus assessed for a given situation based on multiple types of information, enabling one or more preferred travel options for the given situation to be identified and used.