A vehicle control device includes a detecting unit that detects a towing state of a subject vehicle, a recognizing unit that recognizes surrounding situations of the subject vehicle, a control unit that performs automatic control in which at least one of acceleration-and-deceleration and steering of the subject vehicle is automatically controlled on the basis of the surrounding situations of the subject vehicle recognized by the recognizing unit, and a changing unit that changes, if the detecting unit has detected that the subject vehicle is in a state of towing an object, details of control performed by the control unit in such a manner that it is less likely to perform the automatic control than in the case where the detecting unit has not detected that the subject vehicle is in a state of towing an object

Vehicle control system, vehicle control method, and vehicle control program

A method includes receiving and storing sensor data including a first plurality of data points indicative of a plurality of respective states of the environment external to a vehicle at a plurality of respective times, operational data including a second plurality of data points indicative of a plurality of respective states of an operational parameter of the vehicle at a plurality of respective times, and synchronization data. The method also includes generating an animated re-creation of an event involving the vehicle using the stored data, and causing the animated re-creation of the event to be displayed.

Synchronization of vehicle sensor information

Methods and systems are provided for monitoring use of a vehicle having one or more autonomous (and/or semi-autonomous) operation features to determine and respond to incidents, such as collisions, thefts, or breakdowns. According to certain aspects, operating data from sensors within or near the vehicle may be used to determine when an incident has occurred and determine an appropriate response. The responses may include contacting a third party to provide assistance, such as local emergency services. In some embodiments, occurrence of the incident may be verified by automated communication with the vehicle operator.

Accident response using autonomous vehicle monitoring

A method includes receiving first sensor data representing information collected, during a first time period, by a sensor located on or in a vehicle configured to sense an environment external to the vehicle, storing the data in a memory, processing the data to determine a first set of one or more characteristics of the external environment, and determining, based on the first set of characteristics, a first risk indicator representing a risk of loss during the first time period. The method also includes receiving second sensor data representing information collected, during a second time period, by the sensor, storing the data in the memory, and processing the data to determine a second set of one or more characteristics of the external environment. The method also includes determining, based on the second set of characteristics, a second risk indicator representing a risk of loss during the second time period.

Assessing risk using vehicle environment information

Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous and/or semi-autonomous operation features are provided. According to certain aspects, performance data indicative of the performance of the features may be used to determine fault for a vehicle accident, such as a collision, by allocating fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to determine an adjustment to an insurance policy and/or adjust coverage levels for an insurance policy. The allocation of fault may further be used to adjust risk levels or profiles associated with the autonomous or semi-autonomous operation features, which may be applied to other vehicles having the same or similar features.

Accident fault determination for autonomous vehicles

The present invention is intended to provide a technique which is capable of detecting a collision position of a moving object crossing a road and a subject vehicle with a higher degree of accuracy. In the present invention, in cases where the moving object crossing the road into which the subject vehicle has entered is detected at the time when the subject vehicle has turned to the right or to the left, the direction of a moving vector of the moving object is fixed to a direction which is set based on a shape of the road into which the subject vehicle has turned to the right or to the left. Then, the collision position of the moving object and the subject vehicle is predicted based on this moving vector of which the direction is fixed.

Collision position predicting device

An object of the present invention is to further improve the detection accuracy of a lateral position of a target in an object detecting apparatus for detecting an object by using a radar and a monocular image sensor. In the present invention, a target corresponding to a target recognized by the radar is extracted and a right edge and a left edge of the target are acquired from an image picked up by the monocular image sensor. Further, locus approximation lines, which are straight lines or predetermined curved lines for approximating loci of the right edge and the left edge, are derived for the both edges. The edge, which has a larger number of edges existing on the locus approximation line, is selected as a true edge of the target from the right edge and the left edge. The lateral position of the target is derived on the basis of the position of the selected edge.

Object detecting apparatus and object detecting method

An object of the present invention is to provide an object detection apparatus and a driving assistance apparatus in which movement information of a target object can be obtained with high accuracy. In the present invention, the object detection apparatus is an apparatus that detects a target object from a predetermined mounting position (a vehicle and the like); performs an object detection from a predetermined mounting position; in a case where a target object is detected, acquires the position of the target object; obtains a feature amount of a fixed object existing around the target object and detects a position of a fixed object; sets the position of the fixed object as a reference point; and calculates movement information of the target object from the position of the target object with the reference point as a reference.

Object detection apparatus and driving assistance apparatus

A driving-assistance device is disclosed The driving-assistance device in which, when a three-dimensional object is present on a course of a host vehicle, driving assistance for avoiding a collision between the host vehicle and the three-dimensional object is implemented on a condition that an unavoidable three-dimensional object is present in a predetermined range including the course, the driving-assistance device comprises a setting unit configured to set the predetermined range in the vicinity of the host vehicle at a degree of width depending on the three-dimensional object, wherein, when a plurality of the three-dimensional objects are detected within the predetermined range, the setting unit makes the degree of width smaller than when a single three-dimensional object is detected within the predetermined range

Driving-assistance device and driving-assistance method

Provided is an object detection apparatus that detects objects using radar and a monocular image sensor, and wherein the detecting precision of the lateral position of an object to be detected is further improved. A detected object corresponding to a detected object identified by the radar is extracted from among the images picked up by the monocular image sensor, and the right and left edges of the detected object are also obtained. Furthermore, locus approximation lines, which are straight lines or curved lines that approximate the locus of the right and left edges, are derived for both the edges. Then, of the right and left edges, the one that has more edges existing on the locus approximation line is selected as the true edge of the detected object, and the lateral position of the detected object is derived on the basis of the position of the selected edge.

Object detection apparatus and object detection method

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