Abstract: A vehicle control apparatus for performing autonomous driving of a host vehicle. The vehicle control apparatus includes an operating section information acquisition unit configured to acquire operating section information that is information of an operating section in which vehicle stability control by brake control has been operated in a vehicle in autonomous driving in the past; an operation plan generation unit configured to generate an operation plan of autonomous driving of the host vehicle based on a preset target route and map information; and a vehicle controller configured to perform autonomous driving along the operation plan, wherein the operation plan generation unit generates the operation plan so that the host vehicle does not stop in the operating section.

Abstract: A control apparatus according to the present disclosure is configured to execute the following first to five processes. The first process is a localization of a moving body. The second process is revising an estimated position obtained by the localization such that a displacement amount with respect to a previous position is within a predetermined range. The third process is regarding a revised estimated position obtained as a position of the moving body in a current process, and performing a control of the moving body based on the revised estimated position. The fourth process is detecting a poor accuracy of the localization based on a difference between the estimated position and the revised estimated position. The fifth process is performing an emergency control corresponding to a magnitude of the difference when the poor accuracy of the localization is detected.

Abstract: A moving body control system executes a localization process that estimates a position of a moving body based on sensor-detected information and feature object map information indicating a position of a feature object. The moving body control system executes driving assist control based on the estimated position of the moving body. A first range includes the estimated position of the moving body and becomes larger as reliability of the localization process becomes lower. A first future range is at least a part of an expected passing range of the first range. When an obstacle is present in the first range or the first future range, the moving body control system makes the moving body decelerate or stop. When no obstacle is present in the first range or the first future range, the moving body control system continues the driving assist control.

Abstract: A control system according to the present disclosure comprises one or more memories and one or more processors. The one or more memories are configured to store observation data detected by one or more sensors installed in a moving body and an estimated position of the moving body. The one or more processors are configured to execute the following first to third processes. The first process is calculating the estimated position at a current time based on at least the estimated position calculated in a previous process and the observation data up to the current time. The second process is recalculating the estimated position at a past predetermined time. The third process is evaluating accuracy of the estimated position at the current time based on a difference between the estimated position at the past predetermined time stored in the memory and the recalculated estimated position.

Abstract: A log management apparatus according to the present disclosure comprises a memory storing traveling log data of a vehicle and one or more processors. The one or more processors are configured to execute the following first to five processes. The first process is acquiring a remaining capacity of the memory at a current time. The second process is acquiring a traveling plan of the vehicle. The third process is calculating a predicted data size which is a size of the traveling log data predicted to be stored in the future in the traveling plan. The fourth process is predicting a capacity shortage of the memory in the traveling plan based on the predicted data size and the remaining capacity at the current time. The fifth process is a process of increasing the remaining capacity when the capacity shortage of the memory is predicted.

Abstract: A travel planner identifies, for a connection point where a travel lane in which a vehicle is traveling connects ahead of the vehicle with another lane different from the travel lane, an entry time range representing a time range during which entry of the vehicle from the travel lane to the connection point is recommended, and creates a travel plan including a transition of travel speed of the vehicle from a current position of the vehicle to the connection point so as to arrive at the connection point within the entry time range.

Abstract: A traveling trajectory estimation system obtains traveling record information indicating a past traveling record of a vehicle, and characteristic object position information indicating the installation position of a characteristic object, and performs a vehicle position estimation process to estimate an object vehicle position at an object time, based on the traveling record information and the characteristic object position information. In the vehicle position estimation process, not only a time previous to the object time, but also a time subsequent to the object time, is used as a reference time. The traveling trajectory estimation system sets each of a plurality of successive times as the object time, and performs the vehicle position estimation process, to estimate the object vehicle positions at the respective times, and determines a collection of the estimated object vehicle positions as a traveling trajectory of the vehicle.

Abstract: At least one processor of a vehicle is configured to execute at least one program to: generate a speed plan for a first travel route from a blind spot elimination position to a position specified by a control standby condition, the speed plan specifying a speed of the vehicle for a position on the first travel route so as to meet a requirement that the vehicle be decelerated at a predetermined allowable deceleration or less for a predetermined time from the blind spot elimination position to satisfy the control standby condition; and instruct, for a second travel route from a current position of the vehicle to the blind spot elimination position, the vehicle to travel along the second travel route by autonomous driving so as to cause the vehicle to reach a speed specified by the speed plan at the blind spot elimination position.

Abstract: The present disclosure provides to an apparatus for managing travel of a vehicle having an autonomous travel function. The apparatus executes the following steps. The apparatus sequentially acquires sensor information from a recognition sensor mounted on the vehicle. The apparatus sequentially generates prediction information showing a position of an object at a future time point based on the sensor information acquired sequentially. The apparatus transmits a remote support request to a remote support operator. The apparatus receives a remote support given in response to the remote support request by the remote support operator. The apparatus makes the vehicle autonomously travel in accordance with the remote support in response to confirming that an actual position of an object obtained from sensor information and a predicted position of an object obtained from prediction information correspond.

Abstract: A self-position estimation accuracy verification method includes a step of moving a mobile object to a first check point, a step of acquiring first check information, a step of starting a self-position estimation using the first check information as an initial value, a step of moving the mobile object to a second check point while continuing the self-position estimation, a step of acquiring second check information, and a step of calculating a deviation between a position and a posture of the mobile object on the map estimated by the self-position estimation at the second check point and a position and a posture of the mobile object on the map indicated in the second check information, and verifying the accuracy of the self-position estimation based on the deviation.

Abstract: The vehicle position estimation apparatus that estimates the position of the host vehicle includes: a laser light irradiation unit configured to illuminate laser light; a light reception element configured to receive reflection light of the laser light and reflection light of ambient light which is light other than the laser light and be able to detect an intensity of each of the received reflection light; and a host position estimation unit configured to estimate the position of the host vehicle, based on a result of light reception of the reflection light of the laser light received by the light reception element and a result of light reception of the reflection light of the ambient light.

Abstract: An assistance control system performs assistance control for causing a moving object to move to a destination based on map information. The assistance control system includes an electronic control unit. The electronic control unit is configured to generate or update the map information based on input from a sensor mounted on the moving object, acquire a plurality of route candidates to the destination, evaluate certainty of the map information for each location or each section, and calculate a map information evaluation value, evaluate accuracy of the assistance control in the acquired route candidates based on the calculated map information evaluation value, and present a route candidate having the highest priority among the route candidates to an occupant of the moving object, or control the moving object along the route candidate having the highest priority.

Abstract: An automated driving management system is applied to a vehicle that performs automated driving by using a perception sensor. The automated driving management system acquires first sensor perception information indicating a result of perception by the perception sensor. Reference information indicates a correspondence relationship between a vehicle position and expected sensor perception information that is the first sensor perception information expected when an automated driving condition is satisfied. Based on the reference information, the automated driving management system acquires the expected sensor perception information associated with a determination target position.

Abstract: A vehicle dispatch system for dispatching an autonomous vehicle in accordance with a vehicle dispatch request is proposed. The vehicle dispatch system is configured to execute generating a transportation route from a pick-up point to a destination point, generating a plurality of candidate dispatch routes for a dispatch route from a current point of the autonomous vehicle to the pick-up point, calculating a degree of overlap between the transportation route and the dispatch route for each of the plurality of candidate dispatch routes, selecting the dispatch route from the plurality of candidate dispatch routes based on the degree of overlap, and causing the autonomous vehicle to travel along the dispatch route and the transportation route.

Abstract: An automated driving trajectory generating device is configured to: recognize a mobile object which is located near a vehicle; calculate a host vehicle path for automated driving of the vehicle and a plurality of predicted paths of the mobile object based on a position of the vehicle on a map, a position of the mobile object on the map, and map information; calculate a predicted acceleration which is generated in the mobile object moving along a predicted path for each predicted path based on the plurality of predicted paths and a vehicle speed of the mobile object; identify a target path which is a predicted path used to generate the trajectory out of the plurality of predicted paths based on a result of comparison between the predicted acceleration and an acceleration threshold value; and generate the trajectory based on the host vehicle path and the target path.

Abstract: A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

Abstract: According to the method of the present disclosure, first, a plurality of data sets is generated from a travel log data group. Each of the plurality of data sets includes one or more travel log data. Each travel log data is defined by one or more parameters. Next, map data for evaluation is generated from each of the plurality of data sets. Then, an evaluation value is calculated for each map data for evaluation. Then, a relationship between a combination of conditions of the one or more parameters and the evaluation value is specified based on a correspondence relationship between each of the plurality of data sets and the evaluation value of each map data for evaluation. And finally, map data for autonomous driving in which the evaluation value is associated with each combination of conditions of the one or more parameters is generated.

Abstract: According to the method of the present disclosure, first, a plurality of data sets is generated from a travel log data group. Each of the plurality of data sets includes one or a plurality of travel log data. Next, map data for evaluation is generated from each of the plurality of data sets. Then, abnormal map data included in a plurality of map data for evaluation generated from the plurality of data sets is specified by comparing the plurality of map data for evaluation with each other. Then, abnormal travel log data is specified by comparing a data set used to generate the abnormal map data with a data set used to generate map data for evaluation other than the abnormal map data. And finally, final map data is generated using a data set that does not include the abnormal travel log data.

Abstract: A vehicle control system controls a vehicle that potentially requests remote support in a predetermined area. The vehicle control system acquires surrounding situation information including at least one of object information regarding an object around the vehicle and signal indication information indicating signal indication around the vehicle. The vehicle control system determines whether or not an exit passable condition is satisfied based on the surrounding situation information, the exit passable condition being a condition under which the vehicle is able to pass through a target exit from the predetermined area without waiting. When the exit passable condition is not satisfied, the vehicle control system withholds requesting the remote support in the predetermined area until a lifting condition is satisfied.

Abstract: A system comprises a plurality of MaaS vehicles, one or more processors configured to execute generating a dispatch plan for the plurality of MaaS vehicles. The plurality of MaaS vehicles includes one or more autonomous vehicles performing autonomous driving in accordance with the dispatch plan. The generating the dispatch plan includes acquiring an operational design domain of the one or more autonomous vehicles, acquiring a prediction of dispatch service environment for a predetermined period of time in the future regarding a dispatch service area of the one or more autonomous vehicles, specifying an inoperable vehicle among the one or more autonomous vehicles based on the operational design domain and the prediction of dispatch service environment, and modifying the dispatch plan depending on vehicle information or service information of the inoperable vehicle.