Abstract: An other-vehicle detector 18 of an other-vehicle detection device 10a detects an other-vehicle VO around a host vehicle VM based on the predetermined feature amount. A detection reference value adjustment unit 16 of the other-vehicle detection device 10a, regarding the feature amount for detecting the other-vehicle VO around the host vehicle VM, changes a threshold value of the feature amount for detecting the other-vehicle VO, and detects the other-vehicle VO, based on a relative positional relationship between the other-vehicle VO and the host vehicle VM. In this way, it is possible to detect the existence of the other-vehicle VO according to the situation more.

Abstract: A movement region prediction apparatus includes a mobile body detection device that detects a mobile body around a host vehicle; a prediction device that predicts a movement region of the detected mobile body; and a degree-of-normality acquisition device that acquires degree of normality of a situation of movement of the detected mobile body. The prediction device has a plurality of movement prediction models for predicting the movement region of the mobile body, and selects a movement prediction model from the plurality of movement prediction models based on the degree of normality acquired by the degree-of-normality acquisition device, and predicts the movement region of the mobile body using the selected movement prediction model.

Abstract: A driving assist device includes a first control portion that controls a vehicle to carry out automated driving, and a second control portion that controls the vehicle to make a shift to manual driving, in which the vehicle travels on a basis of an driving operation by a driver, when canceling the automated driving, and changes a manner of canceling the automated driving in accordance with an elapsed time from a start of the automated driving.

Abstract: A host-vehicle risk acquisition device includes a host-vehicle path acquisition portion that acquires a path of a host-vehicle, and an obstacle path acquisition portion that acquires a plurality of paths of an obstacle existing around the host-vehicle. A collision risk acquisition portion acquires an actual collision risk, which is a collision risk between the host-vehicle and the obstacle when the host-vehicle is in a travel state based on the path of the host-vehicle and the plurality of paths of the obstacle. An offset risk acquisition portion acquires an offset risk, which is a collision risk between the host-vehicle and the obstacle in an offset travel state, which is offset from the travel state of the host-vehicle.

Abstract: A driving assist device includes a first control portion that controls a vehicle to carry out automated driving, and a second control portion that controls the vehicle to make a shift to manual driving, in which the vehicle travels on a basis of an driving operation by a driver, when canceling the automated driving, and changes a manner of canceling the automated driving in accordance with an elapsed time from a start of the automated driving.

Abstract: A collision determination device determines the possibility of collision between a host vehicle and the other object on the basis of a shortest arrival time calculated by a shortest arrival time calculation unit and a passage time at each point of the host vehicle acquired by a vehicle route candidate acquisition unit. In this way, even if a locus to be taken by the other object is not generated, the shortest arrival time at which the other object can arrive at each point of the route candidate of the host vehicle with a predetermined first displacement is calculated, thereby determining the possibility of collision between the host vehicle and the other object. Therefore, it is possible to reduce a computational load for determining collision and to accurately determine collision between the host vehicle and the other object.

Abstract: An own vehicle risk acquiring ECU 1 acquires a predicted track of an own vehicle and calculates and acquires a plurality of tracks of the other vehicle about the own vehicle. According to the predicted track of the own vehicle and the plurality of tracks of the other vehicle, a collision probability of the own vehicle is calculated as a collision possibility.

Abstract: A host-vehicle risk acquisition device includes a host-vehicle path acquisition portion that acquires a path of a host-vehicle, and an obstacle path acquisition portion that acquires a plurality of paths of an obstacle existing around the host-vehicle. A collision risk acquisition portion acquires an actual collision risk, which is a collision risk between the host-vehicle and the obstacle when the host-vehicle is in a travel state based on the path of the host-vehicle and the plurality of paths of the obstacle. An offset risk acquisition portion acquires an offset risk, which is a collision risk between the host-vehicle and the obstacle in an offset travel state, which is offset from the travel state of the host-vehicle.

Abstract: Disclosed is a mobile body which plans an avoidance operation of the mobile body and an expected avoidance operation which is expected of a mobile obstacle, thereby improving efficiency of the avoidance operation. A mobile body (1) which moves along an operation target includes mobile obstacle detection means (6) and (7) for detecting a mobile obstacle in the vicinity of the mobile body (1), approach determination means (15) for determining whether or not the mobile obstacle and the mobile body approach each other within a predetermined interval, and operation planning means (16) for, when the approach determination means (15) determines that the mobile obstacle and the mobile body (1) approach each other within the predetermined interval, planning the avoidance operation of the mobile body (1) and an expected avoidance operation which is expected of the mobile obstacle.

Abstract: An own-vehicle-path determining method includes calculating a first evaluation value of each of plural predicted own-vehicle-path candidates, calculating a second evaluation value of each of the plural own-vehicle-path candidates, selecting own-vehicle-path candidates with high first evaluation values from the plural own-vehicle-path candidates, selecting own-vehicle-path candidates with high second evaluation values as appropriate own-vehicle-path candidates from the selected own-vehicle-path candidates, and selecting any one of the appropriate own-vehicle-path candidates as an own-vehicle path.

Abstract: An object of the present invention is to provide a driving assistance device which it is easy to instinctively manipulate without causing a driver to feel a sense of discomfort. According to the driving assistance device according to the present invention, when it is instructed to perform automated driving using an automated driving switch and a destination has been set using a destination setting unit, an ECU generates a route for automated driving to the destination and starts the automated driving. When a destination has not been set using the destination setting unit and it is detected that the driver has travel continuation intention by a travel intention detection unit, the ECU generates a route for automated driving along the road and starts the automated driving.

Abstract: A course evaluation that evaluates a course of a mobile unit includes: generating a predetermined first course of the mobile unit; generating, for the first course, a second course for which a controlled amount of the mobile unit after a predetermined driving condition is satisfied is increased as compared with a controlled amount of the mobile unit on the first course; estimating another object course, which is a course of another object; determining whether the second course interferes with the other object course; and evaluating a degree of safety of the first course on the basis of a result of determination as to whether the second course interferes with the other object course.

Abstract: A photodetector disclosed herein comprises an avalanche transistor having a reference junction structure in which temperature characteristics of a current amplification factor are about the same as those of an avalanche photodiode and which is reverse-biased, and a current injection junction structure which injects a reference current to the reference junction structure and which is forward-biased. Voltages to be applied to the avalanche photodiode and the reference junction structure are controlled so that the amplification factor of the reference current amplified in the reference junction structure is retained at a predetermined value, whereby the temperature characteristics of the photodetector utilizing an avalanche effect can be stabilized.

Abstract: Provided is a moveable spectrum measuring apparatus capable of improving discrimination precision of a measuring object on the basis of observation data from a spectrum sensor mounted on a movable apparatus such as a vehicle. A measuring object and a reference body are irradiated with ambient light. A spectrum acquiring device acquires measuring object data indicating the spectrum of the measuring object, and reference body data indicating the spectrum of the reference body to become a reference at the time when the spectrum of the measuring object is corrected. A spectrum converting device has reference body reflectivity data indicating the surface reflectivity of the reference body, and creates ambient light data indicating the spectrum of the ambient light, on the basis of the reference body reflectivity data and the reference body data.

Abstract: Disclosed is a route evaluation device that enables traveling along a route in consideration of an operation of the driver of another vehicle, and can realize a safer traffic environment. A route evaluation device includes a route candidate generation section that generates route candidates of a host-vehicle, a route prediction section that predicts routes of another vehicle, a classification section that classifies the interference states of the route candidates of the host-vehicle and the predicted routes of another vehicle into a plurality of interference forms, and a route evaluation section that evaluates the routes of the host-vehicle on the basis of the interference forms classified by the classification section.

Abstract: Disclosed is a vehicular environment estimation device capable of accurately estimating a travel environment around own vehicle on the basis of a predicted route of a mobile object or the like, which is moving in a blind area. A vehicular environment estimation device that is mounted in the own vehicle detects a behavior of another vehicle in the vicinity of the own vehicle, and estimates a travel environment, which affects the traveling of another vehicle, on the basis of the behavior of another vehicle. For example, the presence of another vehicle, which is traveling in a blind area, is estimated on the basis of the behavior of another vehicle. Therefore, it is possible to estimate a vehicle travel environment that cannot be recognized by the own vehicle but can be recognized by another vehicle in the vicinity of the own vehicle.

Abstract: A driving assist device includes a first control portion that controls a vehicle to carry out automated driving, and a second control portion that controls the vehicle to make a shift to manual driving, in which the vehicle travels on a basis of an driving operation by a driver, when canceling the automated driving, and changes a manner of canceling the automated driving in accordance with an elapsed time from a start of the automated driving.

Abstract: A movement region prediction apparatus includes a mobile body detection device that detects a mobile body around a host vehicle; a prediction device that predicts a movement region of the detected mobile body; and a degree-of-normality acquisition device that acquires degree of normality of a situation of movement of the detected mobile body. The prediction device has a plurality of movement prediction models for predicting the movement region of the mobile body, and selects a movement prediction model from the plurality of movement prediction models based on the degree of normality acquired by the degree-of-normality acquisition device, and predicts the movement region of the mobile body using the selected movement prediction model.

Abstract: A driving assist apparatus 1 that performs driving assist on the basis of a traffic rule of a mobile object includes a traffic rule acquisition unit 11, 12, and 13 acquiring a traffic rule which a mobile object is highly likely to observe in an arbitrary region, and performs driving assist on the basis of the traffic rule acquired by the traffic rule acquisition unit. In particular, the driving assist apparatus includes a region acquisition unit 13 acquiring a traffic rule deviation region where a defined traffic rule in an arbitrary region does not conform to the traffic rule acquired by the traffic rule acquisition unit, or a traffic rule correction unit correcting the traffic rule acquired by the traffic rule acquisition unit when a defined traffic rule in an arbitrary region does not conform to the traffic rule acquired by the traffic rule acquisition unit.

Abstract: A movable area acquisition ECU 1 compares a possible path for a host vehicle and a predicted path of another vehicle in a travel area of the host vehicle with each other to obtain a possibility of collision between the two vehicles, thus computing a degree of danger to the host vehicle. If the degree of danger to the host vehicle exceeds a predetermined threshold, the travel area is extended and then a degree of danger to the host vehicle is computed and acquired.