A method and an apparatus for testing a ramp driving performance, and a storage medium, where the method includes: controlling, according to a preset traveling track, an automatic driving vehicle to perform a stopping operation when the automatic driving vehicle is traveling on a ramp to a reference position; obtaining relative position information between an actual stopping position of the automatic driving vehicle and a reference object disposed at the reference position; and determining, according to the relative position information, whether the automatic driving vehicle is accurately stopped on the ramp. The driving performance of the automatic driving vehicle in a special scenario, such as ramp stopping, can be accurately detected, thereby ensuring a driving safety of the automatic driving vehicle in the ramp stopping scenario.

An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for generating or updating usage-based insurance policies for autonomous or semi-autonomous vehicles may be provided. A request to generate an insurance quote may be received via wireless communication, and with the customer's permission, risk levels associated with intended usage by the customer of an autonomous or semi-autonomous vehicle may be determined. An insurance policy may be adjusted based upon the risk levels and the intended vehicle usage. The insurance policy may then be presented on the customer's mobile device for review and approval. In some aspects, the vehicle may be rented, and the intended vehicle usage is measured in distance or duration of vehicle operation. Insurance discounts may be provided to risk averse vehicle owners based upon low risk levels.

A method for supporting an attentiveness and/or driving readiness of a driver during automated driving operation of a vehicle, including computing a failure probability value using at least one read-in map information signal, environmental condition signal, and/or probability signal. The failure probability value represents a failure probability of a driver assistance system for performing an automated driving operation. The probability signal represents an error probability and/or failure probability of at least one vehicle sensor of the driver assistance system. The method also includes determining a comparison parameter in response to the computed failure probability value, the comparison parameter representing the result of a comparison of an extent of a necessary driving requirement on the traveled travel route of the vehicle to a degree of instantaneous driver attentiveness. The method also includes providing an advance warning signal in response to the determined comparison parameter.

A computer-implemented method for controlling a host vehicle having a vehicle control system that controls motion of the host vehicle relative to a preceding vehicle that is immediately ahead of the host vehicle. The method includes determining a relative headway distance and a relative velocity between the host vehicle and the preceding vehicle, and an acceleration rate of the preceding vehicle. The method includes receiving message packets transmitted from a leading vehicle and the message packets contain parameters of the leading vehicle including an acceleration rate of the leading vehicle. Further, the method includes calculating an acceleration control rate for the host vehicle to maintain the headway reference distance between the host vehicle and the preceding vehicle, based on the relative headway distance, the relative velocity, the acceleration rate of the preceding vehicle, and the acceleration rate of the leading vehicle. The acceleration rate is output to a vehicle controller to control motion of the host vehicle.

A monitoring apparatus that is for installation in a vehicle, is to be communicably connected to a vehicle-mounted update apparatus that stores configuration information of a vehicle-mounted ECU that is to apply an update program, and monitors the vehicle-mounted update apparatus. The monitoring apparatus includes: a control unit that obtains the configuration information of the vehicle-mounted ECU from the vehicle-mounted update apparatus, and, if previously obtained first configuration information and most recently obtained second configuration information are different, the control unit determines that the vehicle-mounted update apparatus has been replaced and executes predetermined processing.

In some implementations, a method is provided. The method includes determining a path for an autonomous driving vehicle. The path is located within a first lane of an environment in which the autonomous driving vehicle is currently located. The method also includes obtaining sensor data. The sensor data indicates a set of speeds for a set of moving obstacles located in a second lane of the environment and wherein the second lane is adjacent to the first lane. The method further includes determining whether the set of speeds is lower than a threshold speed. The method further includes determining a new speed for the autonomous driving vehicle in response to determining that the set of speeds is lower than the threshold speed. The method further includes controlling the autonomous driving vehicle based on the path and the new speed.

A driving support ECU performs a following-travel steering control. The driving support ECU selects an other vehicle which is present on a traveling course of the own vehicle as a target candidate vehicle. When a specific condition is satisfied, the driving support ECU determines a preceding vehicle traveling on a traveling trajectory which has been generated up to a present time point as a following-travel steering target vehicle. When the specific condition is not satisfied, the driving support ECU determines the target candidate vehicle which has been selected in the present calculation timing as the following-travel steering target vehicle.

A execution monitoring device (20) includes a time-series data storage unit (225) to store time-series data and a real-time specification determining unit (204). The real-time specification determining unit (204) updates a determination result, which is a result of determining whether the time-series data stored in the time-series data storage unit (225) satisfies a real-time specification, which is part of constraints included in a monitoring specification for electronic device runtime monitoring, is stored in a memory area reserved before execution of the real-time specification determining unit (204), and is a constraint using a real time.