Abstract:
A vehicle includes a system and method of operating the vehicle. The system includes a camera, a map database and a processor. The camera obtains camera data of a location of a road being traversed by the vehicle. The map database provides map data of the location of the road. The processor determines a first curvature of the road at the location from the camera data, determines a second curvature of the road at the location from the map data, identifies a mismatch between the first curvature and the second curvature at the location of the road, generates a case report for one of the map data and the camera data at the location upon occurrence of the mismatch, and adjusts one of the map data and a confidence level in the camera data for the location based on the case report.
Abstract:
Methods and systems to implement sensor fusion to determine collision potential for a vehicle include identifying a specific intersection that the vehicle is approaching, and identifying collision potential scenarios associated with one or more paths through the specific intersection. Each collision potential scenario defines a risk of a collision between the vehicle and an object in a specified area. A weight with which one or more information sources of the vehicle are considered is adjusted for each collision potential scenario such that a highest weight is given to one or more of the one or more information sources that provide most relevant and reliable information about the specified area. Sensor fusion is implemented based on the adjusting the weight of the one or more information sources and performing detection based on the sensor fusion, and an alert is provided or actions are implemented according to the detection.
Abstract:
A system and method for determining the presence of a hidden hazard may include identification of an operational scene for a host vehicle, and identification of an operational situation for the host vehicle. Information from a plurality of proximity sensors is collected and classified. A plurality of hidden hazard presence probabilities corresponding to the information from each of the plurality of proximity sensors, the operational scene, the operational situation, and at least one of a comparative process and a dynamic neural network process are estimated. A fusion process may be performed upon the plurality of hidden hazard presence probabilities to determine the presence of a hidden hazard.
Abstract:
Methods and systems are provided for evaluating a CAN that includes a CAN bus and a plurality of modules configured to communicate over the CAN bus. A voltage sensor may be provided in electrical communication with the CAN bus. A number (N) of pairs of voltages may be read. Each pair may include a CAN high (CAN-H) value and a CAN low (CAN-L) value. The N pair of voltages may be processed through a comparison of the CAN-H values and the CAN-L values. Whether a fault signature is present in the CAN-H and CAN-L values may be determined from the processing.
Abstract:
A method for diagnosing a no-start fault of a vehicle push-button start system including a push-button switch, where the system starts a vehicle engine if the switch is pressed and a vehicle brake is applied. The method includes detecting that a no engine crank condition has occurred if the switch is pressed and the brake is applied, and if so, performs a no crank diagnosis. The method also includes determining that a starter control relay has not been enabled after the system is in a crank power mode, and if so, performs a starter not-enabled diagnosis. The method also includes determining that the starter control relay has been disabled before the engine is running, and if so, performs a start disable diagnosis. The method also includes determining that the engine has stalled within some minimum time after it has successfully been started, and if so, performs an engine stall diagnosis.
Abstract:
A system includes control modules, a low-voltage communications bus, e.g., a CAN bus of a vehicle, a voltage sensor that measures a bus voltage and outputs 2.5-3.5 VDC high-data and 1.5-2.5 VDC low-data, and a host electronic control unit (ECU). The host ECU detects a recoverable fault using a data pattern in the bus voltage data when the data is outside of a calibrated range, and recalibrates the sensor. Recalibration may be by adjustment to a scaling factor and/or a bias value. Non-recoverable “stuck-at-fault”-type or “out-of-range”-type faults may be detected using the pattern, as may be a ground offset fault. A method includes measuring the bus voltage using the sensor, comparing the output data to a range to detect the fault, and isolating a sensor fault as a recoverable fault using the data pattern when the data is outside of the range. The sensor is then be recalibrated.
Abstract:
A method for monitoring a controller for a vehicle includes determining configuration information associated with the vehicle and determining vehicle operating states associated with a plurality of conditions. A statistical analysis is executed to correlate a plurality of faults with the vehicle operating states and the configuration information associated with the vehicle. The plurality of faults in the controller can be isolated to one of a hardware fault or a software fault based upon the statistical analysis and the configuration information associated with the vehicle.
Abstract:
A vehicle including an internal combustion engine, a DC power source and a controller are described. The internal combustion engine includes an engine starting system and an electrical charging system. A method for monitoring the DC power source includes determining a State of Charge (SOC) for the DC power source. Upon detecting that the SOC is less than a threshold SOC, routines are executed in the controller to evaluate a plurality of potential root causes associated with the low SOC. At least one of the potential root causes associated with the low SOC may be identified as a candidate root cause, and a fault probability for each of the candidate root causes is determined. One of the candidate root causes is determined to be a final root cause based upon the fault probabilities associated with the candidate root causes.
Abstract:
A method diagnoses a no-start condition in a powertrain having an engine and a starter system operable for starting the engine. The starter system includes a battery, solenoid relay, starter solenoid, and starter motor. The method includes recording starter data over a calibrated sampling duration in response to a requested start event when the solenoid relay is enabled, including a cranking voltage and engine speed. If no battery current sensor is used, the method derives a resistance ratio using an open-circuit voltage and a minimum cranking voltage of the battery. When such a sensor is used, the method derives a battery and starter resistance. A fault mode of the starter system is then identified via a controller using the starter data and either the resistance ratio or the battery and starter resistances. A control action executes that corresponds to the identified fault mode.
Abstract:
A method is disclosed for detecting ground faults in a communications system. The method includes measuring a predetermined number of voltage points; determining if the measured voltage points represent recessive or dominant bits; identifying which of the predetermined number of voltage points represent inter-frame bits and which represent frame data bits based on whether the measured voltage points are recessive or dominant; calculating a maximum average voltage for the inter-frame bits; calculating an average frame voltage for all dominant bits within a frame; determining a high average dominant voltage count based on a number of frames for which the average frame voltage is greater than a high voltage threshold; and determining if a ground fault exists based on the average frame voltage and the high average dominant voltage count.