A vehicular control system includes a camera disposed at an in-cabin side of a windshield of a vehicle, the camera viewing forward of the vehicle through the windshield, and the camera capturing image data representative of at least an upcoming road surface of a road ahead of the vehicle. The vehicular control system, via processing at an image processor of image data captured by the camera, determines traction condition of at least a portion of the imaged upcoming road surface that is ahead of the vehicle. The vehicular control system, via processing at the image processor of captured image data, determines a change in traction condition ahead of the vehicle and adjusts an adaptive cruise control system of the vehicle responsive at least in part to the determined change in traction condition ahead of the vehicle.

A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.

Described herein are techniques for generating and providing feedback to an operator of a vehicle in real-time to optimize operation of that vehicle. Such techniques may involve receiving, from a vehicle, operation data related to performance of one or more operations of the vehicle, obtaining expected operation data relevant to the vehicle, calculating a variance representing a difference between the between the operation data and the expected operation data, generating, based on the calculated variance, feedback to be provided to an operator of the vehicle, and providing the feedback to the vehicle to be presented to the operator.

Excess fuel consumption monitor and feedback systems for vehicles include sensor arrays of two primary types including those sensors deployed as part of a vehicle manufacturer established sensor suite and sensors deployed as after-market sensors. Together, these sensor suites include sensors coupled to vehicle subsystems and operating environments associated with the vehicle. Data from these sensors may be used as parametric inputs to drive algorithmic calculations which have outputs that express excess fuel consumption. Expressions of excess fuel consumption may be made instantaneously as real-time feedback to a vehicle operator/driver and/or a fleet manager as part of a summary report.

A method is used to control a fuel level gauge of a vehicle system and includes: monitoring, via an engine controller, a fuel economy of the vehicle system; comparing, via the engine controller, the fuel economy with a predetermined fuel economy threshold to determine whether the fuel economy is less than the predetermined fuel economy threshold; adjusting, via the engine controller, a sensitivity of a display filter in response to determining that the fuel economy is less than the predetermined fuel economy threshold for a predetermined amount of time in order to maximize an accuracy of the fuel level gauge, wherein the display filter smoothes an unfiltered fuel level signal received from a fuel level sensor of the vehicle system, thereby generating a filtered fuel level signal; and controlling, via an instrument panel controller, the fuel level gauge of the vehicle system.

One way to improve fuel efficiency of a vehicle is to detect the vehicle operational shortcomings related to fuel consumption by determining whether fuel used during operation of the vehicle is normal fuel use or wasted fuel use. Considerations of idling, speeding and inappropriate gear shifts are some ways to measure the amount of fuel wasted due to operator shortcomings. Communicating this information to the operator in real-time so adjustments can be made will improve vehicle fuel efficiency. These techniques are applicable to tracking employment of other driving best practices as well.

Present invention optimizes utilization of different fuels in various single and multi-fueled engines. The fuel system and optimization controller links fuel properties (physical, reactionary, combustion etc.) to on-board computer systems during the refueling process. This link enables fuel and additive producers an opportunity to optimize combustion parameters of their proprietary fuel blends to increase performance, fuel efficiencies and reduce emissions.

A system includes a processor configured to determine that travel data, reflecting previous travel, exists for an upcoming route segment. The processor is also configured to derive a fuel-efficient control strategy for the upcoming segment, based on fuel efficient behavior reflected in the travel data. The processor is further configured to execute the control strategy in a vehicle while the vehicle travels over the route segment to instruct vehicle control in accordance with the control strategy for at least a portion of the segment.

A system includes a processor configured to receive a user profile responsive to an efficiency determination request for a vehicle model. The processor is also configured to obtain efficiency-affecting data from the user profile. The processor is further configured to compare the efficiency-affecting data to data gathered from drivers of the vehicle model, to determine a correlation between the user profile and similar drivers of the vehicle model. Also, the processor is configured to predict fuel efficiency for the new vehicle model based on efficiency achieved by the similar drivers.

A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.