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:
Vehicular travel may be facilitated by user interfaces presenting travel information. Such user interfaces often involve visual displays positioned peripherally to a window through which an individual operates the vehicle (e.g., displays mounted in a dash or console) and/or non-visual interfaces (e.g., audio, speech recognition, and manual controls). While presenting visuals on the window obscuring the view of the individual may present safety concerns, peripherally presented visual interfaces that distract the gaze of the individual may raise comparable or greater concerns. Instead, visual user interfaces may be displayed on the window through which the individual operates the vehicle (e.g., a windshield or individual eyewear) to presents visuals representing travel information received from a travel service, such as routing, traffic congestion, highlighting vehicles or routes, and rendering non-visible objects (e.g., obscured traffic control signals). Such user interfaces enable user interaction while allowing the individual to maintain gaze through the window.
Abstract:
One or more techniques and/or systems for providing congestion information for a road segment presently experiencing traffic congestion and/or likely to experience traffic congestion in the future are provided. In some embodiments, traffic models are configured to determine road segments where traffic congestion is likely to occur, to determine a cause of traffic congestion, and/or to determine the effect of such traffic congestion (e.g., the duration of such traffic congestion, the expected time delays due to such traffic congestion, etc.). Congestion information indicative of the cause of congestion and/or the effect(s) of such traffic congestion, for example, may be provided to a user to explain to the user why the congestion is occurring, to describe one or more road segments to avoid, and/or to explain why a particular route was selected as a preferred route to a destination, for example.
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 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:
The environmental impact of vehicle transit through an area is often evaluated through indirect and/or aggregate metrics, such as visibility and/or health effects from smog, or the contamination of air or water quality. However, such environmental metrics may be inaccurate, incomplete, delayed, and/or insufficient to inform a user of a vehicle as to the environmental impact of the vehicle transit of his or her vehicle on the environment. Instead, a vehicle device may collect driving metrics for a vehicle, and may transmit such driving metrics to an environmental monitoring service, which may correlate such driving metrics for the vehicle with the environmental impact. A notification of environmental impact may be transmitted back to the vehicle device, which may present the environmental impact to the user, and/or may adjust an autonomous operation of the vehicle, such as a speed or route of the vehicle, in view of the environmental impact.
Abstract:
One or more techniques and/or systems are provided for providing driver alerts. For example, a client device module (e.g., a smartphone, a vehicle navigation unit, etc.) may collect driving behavior information (e.g., braking patterns, vehicle speed, weather conditions, acceleration/deceleration patterns, etc.) and/or user specified information (e.g., a number of passengers) of a driver driving a vehicle. The client device module may provide the driving behavior information and/or the user specified information to a driver alert provider. The driver alert provider may maintain a driver profile for the driver based upon the driving behavior information and/or the user specified information. The driver alert provider may generate a driver alert (e.g., a driver risk score of the driver) based upon the driver profile, and may provide the driver alert to other drivers that are within a threshold distance of the vehicle.
Abstract:
Vehicles feature various forms of automated driving control, such as speed control and braking distance monitoring. However, the parameters of automated control may conflict with the user driving behaviors of the user; e.g., braking distance maintained with respect to a leading vehicle may seem overcautious to users who prefer shorter braking distances, and unsafe to users who prefer longer braking distances. Presented herein are techniques for controlling vehicles according to the user driving behaviors of users. While a user operates a vehicle in a driving context, a device monitors various driving features (e.g., acceleration or braking) to determine various user driving behaviors. When requested to control a driving feature of the vehicle, a controller may identify the user driving behaviors of the user in the driving context, and control the driving features according to the user driving behaviors, thus personalizing automated driving to the preferences of the user.
Abstract:
One or more techniques and/or systems are provided for generating a trip library. Locational information, obtained from a device of a user (e.g., a mobile device, a wearable device, etc.), may be evaluated to identify trips traveled by the user and terminals traveled to by the user above a visitation frequency threshold (e.g., work, a favorite coffee shop, school, etc.). The trips and terminals may be evaluated to determined preferred trips that the user travels above a travel frequency threshold (e.g., routes that the user prefers to travel when going to a terminal, such as routine routes to a grocery store, work, etc.). A trip library, comprising the terminals, the preferred trips, and conditional likelihoods that he user will travel to a terminal given one or more conditions, may be created and used to preemptively provide the user with suggestions (e.g., notice of an event, coupon, alternative route, accident, etc.).