Honda Motor Co., Ltd.

Honda Giken Kogyo Kabushiki Kaisha

The University of Tokyo

Takamasa Koshizen

Hiroshi Tsujino

Junji Eguchi

Katsuhiro Nishinari

Kazuyuki Aihara

Bernd Heisele

Koji Akatsuka

Kazunori Kuroda

Shugo Miyamoto

Hideaki Ono

Motohri Kon

A traffic monitoring system includes a storage device that stores a program and a hardware processor, in which the hardware processor executes a program stored in the storage device, thereby acquiring a position of a mobile object based on information from a detection device for detecting the position of the mobile object, generating information on a density distribution in which index values having a distribution according to the position of the mobile object are superimposed on one another for a plurality of mobile objects, and predicting whether a target mobile object is likely to enter a gap between two of the mobile objects based on a temporal change in density value indicated by the information on a density distribution.

Traffic monitoring system, traffic monitoring method, and storage medium

A traffic flow estimation apparatus includes: a vehicle number detector which detects a number of preceding vehicles in front of the traffic flow estimation apparatus and; a traffic flow estimator which estimates a traffic flow from the number of preceding vehicles, and the traffic flow estimator includes: an acquisition unit which acquires a time series of the number of preceding vehicles in a first predetermined period as a vehicle number time series; an evaluation index calculation unit which calculates an evaluation index of the vehicle number time series in the first predetermined period; a congestion state determination unit which determines the traffic flow of the preceding vehicles on the basis of the evaluation index; and a traffic flow controller which notifies a following vehicle behind the traffic flow estimation apparatus of an indication with respect to travel on the basis of the traffic flow of the preceding vehicles.

Traffic flow estimation apparatus, traffic flow estimation method, and storage medium

A prediction device includes a camera configured to repeatedly image a region ahead of a vehicle, an extractor configured to extract a region including other vehicles from each of a plurality of images repeatedly captured by the camera, and a predictor configured to predict that a traffic jam will occur in a road on which there is the vehicle on the basis of a change in the region extracted from each of the plurality of images by the extractor between the images.

Prediction device, prediction method, and storage medium

A conversation device that has conversation with a user of an electric wheelchair traveling in a facility in which a plurality of beacon transmitters are disposed includes: a conversation processing part that has conversation with the user using a prediction model; a conversation registration part that stores the conversation as a history; and a model generation part that generates the prediction model through learning, in which in the history of the conversation, a situation of the conversation at a time point when the conversation is made, details of the conversation, and a user's satisfaction with the conversation are associated, the situation of the conversation includes information with which the beacon transmitter that has received radio waves during the conversation is able to be identified, and the model generation part learns the prediction model again at a predetermined timing by classifying the history of the conversation.

Conversation device and conversation system

A movable body control system includes a movable body including a beacon receiver for receiving beacon radio waves from a plurality of beacon transmitters installed around a traveling road, and at least one processing equipment configured to generate a model for determining a position of the movable body based on a distribution of time-series measurement values of beacon radio wave reception intensities in the beacon receiver and to control travel of the movable body while determining an area in which the movable body travels at present based on a distribution of time-series measurement values of the beacon radio wave reception intensities at present and the model.

Movable body control system

A driving assistance method includes: a step of, by a driving assistance apparatus, calculating a power spectrum by a frequency analysis of an acceleration obtained by a three-dimensional accelerometer; a step of, by the driving assistance apparatus, obtaining information on an angle based on a magnitude of an inclination of a single regression line of the power spectrum in a predetermined frequency range; a step of obtaining a speed by the driving assistance apparatus; a step of, by the driving assistance apparatus, calculating a traffic jam sign index as a product of a value associated with a degree of variation in the angle and a value associated with the speed; and a step of, by the driving assistance apparatus, sensing a traffic jam sign based on a change in the traffic jam sign index within a predetermined time.

Driving assistance method, program, and driving assistance apparatus

A driving assistance method executed by a driving assistance device including a tri-axial accelerometer, an information presentation controller, and an information presentation section. The driving assistance method includes: a congestion warning sign information acquisition step for acquiring congestion warning sign information based on change in the acceleration; a multi-lane information acquisition step for acquiring information regarding whether or not the position of the driving assistance device is on a multiple lane travel path; a restriction information presentation step for presenting information indicating lane change restriction when the position is on the multiple lane travel path and congestion warning sign information indicates traffic flow tending toward congestion; and a non-restriction information presentation step for presenting information indicating non-restriction of lane change when the position is on the multiple lane travel path and congestion warning sign information does not indicate traffic flow tending toward congestion.

Driving support method, program, and driving support device

An information terminal transmits present position information and acceleration information to a server device. The server device receives the present position information and the acceleration information of the information terminal, generates congestion prediction degree using the acceleration information, associates the congestion prediction degree with map data such that the congestion prediction degree can be displayed on a road map, and transmits association information indicating the association. The information terminal displays the congestion prediction degree on the road map on the display device using the association information transmitted from the server device.

Server device, congestion prediction information display system, congestion prediction information distribution method, congestion prediction information display method, and program

A congestion sign detection method that is executed by a congestion sign detection devicewhich includes three-dimensional acceleration sensorthat acquires acceleration information in each axis direction of an X axis, a Y axis, and a Z axis forming an orthogonal coordinate system of the three-dimensional space. The method includes: an input data calculation step of calculating an acceleration vector using the acceleration information acquired by the three-dimensional acceleration sensor, and calculating a norm of a difference of the vectors at two different timings as input data; a frequency analysis step of calculating an autocorrelation of the input data and calculating a power spectrum by performing a Fourier transform on the autocorrelation; an angle information acquisition step of converting the power spectrum into angle information; and a congestion sign detection step of detecting congestion sign according to the angle information.

Congestion sign detection method, program, and congestion sign detection device

A synchronized driving assist apparatus includes: a first acceleration power spectrum acquisition section that acquires a first acceleration power spectrum according to acceleration of a first vehicle; a second acceleration power spectrum acquisition section that acquires a second acceleration power spectrum according to acceleration of a second vehicle; a cross power spectrum calculation section that calculates a cross power spectrum between the first vehicle and the second vehicle by using the first acceleration power spectrum and the second acceleration power spectrum; a coherence calculation section that calculates coherence from the cross power spectrum; and a correlation evaluation section that evaluates correlation in a synchronized driving of the first vehicle and the second vehicle on the basis of the coherence.

Synchronized driving assist apparatus and synchronized driving assist system

Disclosed is a method of traffic congestion estimation including a speed detection step of detecting speed of a vehicle in a predetermined period of time and outputting the detection result; a frequency analysis step of analyzing a frequency of the result of the speed detection and outputting the power spectrum; a slope detection step of detecting a slope of a power spectrum and outputting the detection result; a time variation calculation step of calculating time variation of the slope and outputting the calculation result; and a traffic congestion estimation step of estimating occurrence of traffic congestion from the calculation result of the time variation of the slope and outputting the estimation result.

Method of traffic congestion estimation

Disclosed is a method of displaying traffic congestion estimation including a step of detecting a transition state that exists when transitioning from a free flow in which a possibility (probability of occurrence) of an occurrence of traffic congestion is lower than a first set value, to a mixed flow in which states of braking and accelerating the vehicle are mixed as the state of the flow of traffic, and a step of displaying the possibility (probability of occurrence) of transition from the free flow to the mixed flow in a continuous and visual manner on the basis of the detection result of the transition state.

Method of displaying traffic congestion estimation

An electric vehicle driving support system includes an acquisition unit that acquires predictive information of traffic congestion calculated based on acceleration of an electric vehicle and an economical driving mode output unit that outputs a control instruction to prioritize speed maintenance or acceleration when the predictive information of traffic congestion acquired by the acquisition unit indicates a non-congestion tendency, and that outputs a control instruction to prioritize deceleration when the predictive information of traffic congestion indicates a congestion tendency.

Electric vehicle driving support system

Disclosed is a congestion estimation device including a speed detection unit configured to detect a speed of a host vehicle and then outputting a speed detection result, an inter-vehicle distance detection unit configured to detect an inter-vehicle distance between the host vehicle and other vehicle and then outputting an inter-vehicle distance detection result, a correlation calculation unit configured to calculate a correlation based on the speed detection result and the inter-vehicle distance detection result and then outputting a correlation calculation result, and a display unit configured to display the correlation calculation result or information relating to the correlation calculation result.

Congestion estimation device

A driving assist apparatus for a vehicle is provided. The apparatus includes a determination unit that determines a state of a traffic flow in a lane in which a ego-vehicle is driving, on the basis of acceleration of the ego-vehicle and inter-vehicle distances to other vehicles around the ego-vehicle. The apparatus also includes a drive control unit that controls a motion of the ego-vehicle and is capable of switching drive control according to a determination result by the determination unit. The drive control unit switches the drive control when the determination result indicates that the state of the traffic flow is a state of a critical region which is present in a transition period from a free-flow state to a mixed-flow state. Here, the free-flow state is a state in which the probability of occurrence of traffic congestion is low, and the mixed-flow state is a state in which a braking state and an acceleration state of a vehicle are mixed.

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Wako, Japan

Takamasa Koshizen