Automated Spatial Separation of Self-Driving Vehicles From Other Vehicles Based on Occupant Preferences
US-2017057507-A1 · Mar 2, 2017 · US
US9669833B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9669833-B2 |
| Application number | US-201514804842-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 21, 2015 |
| Priority date | Jul 21, 2015 |
| Publication date | Jun 6, 2017 |
| Grant date | Jun 6, 2017 |
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A system and method are provided for operating an adaptive cruise control system of a host vehicle. The method includes receiving data measured from a plurality of sensors, wherein the measured data relates to one or more target vehicles in the host vehicle's field of view. The method further includes generating a following score for each target vehicle based on the measured data and controlling the host vehicle response based on the following score.
Opening claim text (preview).
The invention claimed is: 1. A method for operating an adaptive cruise control system of a host vehicle, the method comprising the steps of: receiving data measured from a plurality of sensors, wherein the measured data relates to one or more target vehicles in the host vehicle's field of view; generating a following score for each of the one or more target vehicles based on the measured data, wherein the following score represents the driving behavior of a particular target vehicle and indicates a desirability of the host vehicle to follow that target vehicle in a host vehicle equipped with an adaptive cruise control system; and controlling a host vehicle response based on the following score. 2. The method of claim 1 , wherein the plurality of sensors are forward-looking vehicle-mounted sensors configured to detect one or more of: a driving lane of each target vehicle relative to the host vehicle, longitudinal or lateral ranges and range rates between the host vehicle and each target vehicle, frequency of turning and brake lights for each target vehicle, and speed of each target vehicle relative to surrounding traffic or posted speed limit. 3. The method of claim 1 , further comprising collecting and storing data from the plurality of sensors for a predetermined period of time in a profile buffer. 4. The method of claim 1 , further comprising creating a profile for the one or more target vehicles in the host vehicle's field of view. 5. The method of claim 1 , further comprising comparing the measured data for the one or more target vehicles to predetermined patterns associated with certain types of driving behaviors. 6. The method of claim 5 , further comprising reducing a target vehicle's following score if a correlation is identified between the measured data for that particular target vehicle and the predetermined patterns associated with undesirable driving behavior. 7. The method of claim 6 , wherein the target vehicle's following score is quantitative and is reduced by a value assigned to the identified predetermined pattern associated with undesirable driving behavior. 8. The method of claim 6 , wherein the target vehicle's following score is qualitative and is reduced by an increment assigned to the identified predetermined pattern associated with undesirable driving behavior. 9. The method of claim 6 , wherein the following score is initially assigned an ideal score and each predetermined pattern has a negative score that is applied to the following score once the predetermined pattern of bad driving behavior has been identified. 10. The method of claim 1 , wherein controlling the host vehicle response based on the following score includes initiating a predefined response, calibration setting, or both based on the following score. 11. The method of claim 10 , wherein the host vehicle response includes increasing the time gap between the host vehicle and the target vehicle based on the following score. 12. The method of claim 10 , wherein the host vehicle response includes suggesting a lane change to the host vehicle driver or autonomously performing a lane change. 13. The method of claim 10 , wherein each of the predefined responses and calibration settings are ranked from the most subtle response to the most significant response. 14. The method of claim 10 , wherein the calibration settings include at least one of: a normal following setting; a moderate following setting; a conservative following setting; a following acceleration and deceleration calibration; a following distance calibration, and open lane speed settings. 15. The method of claim 1 , wherein controlling the host vehicle response based on the following score includes selecting a vehicle response from a plurality of predefined responses, calibration settings, or both. 16. The method of claim 15 , wherein the vehicle response is selected using a lookup table. 17. The method of claim 1 , further comprising associating a following score threshold with each of the predefined responses, calibration settings, or both. 18. A control system for a vehicle, the system comprising: a plurality of vehicle sensors configured to measure data relating to one or more target vehicles in the host vehicle's field of view; an adaptive cruise control system configured to: receive the measured data relating to the one or more target vehicle; generate a following score for the one or more target vehicles based on the measured data, wherein the following score represents the driving behavior of a particular target vehicle and indicates a desirability of the host vehicle to follow that target vehicle in a host vehicle equipped with an adaptive cruise control system; and control the host vehicle response based on the following score. 19. The system of claim 18 , wherein controlling the host vehicle response based on the following score includes initiating a predefined response, calibration setting, or both based on the following score. 20. The system of claim 18 , wherein the adaptive cruise control system is further configured to: compare the measured data for the one or more target vehicles to predetermined patterns associated with undesirable driving behaviors; and reduce a target vehicle's following score if a correlation is identified between the measured data for that particular target vehicle and the predetermined patterns.
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