In a drive assist system, a map data acquiring section acquires at least one of a driver's operation ability and a load of a vehicle. An adjustment section determines an assist control amount as a control parameter of drive assist for the vehicle so that a degree of the driver's operation is increased according to reduction of the driver's operation ability or increasing of the load of the vehicle. An assist control amount calculation section transmits the assist control amount to a steering motor and a notification section so as to execute the drive assist for the vehicle.

Disclosed herein is a vehicle predictive control method that includes determining a driving prediction horizon in front of a vehicle, dividing the driving prediction horizon into a plurality of steps, at least some of the steps corresponding to a sloped section being integrated into one step according to slopes, and applying a driving prediction model based on a relationship between states of vehicle speed, traction force, and braking force for each step and collectively computing the driving prediction model over the entire prediction horizon to calculate a control value for the vehicle.

A cruise control method for a hybrid vehicle is provided. The method includes detecting a preceding vehicle and estimating the speed of the preceding vehicle from the information input from a preceding vehicle detecting unit in the on state of a cruise mode and a PnG mode. An upper limit target vehicle speed and a lower limit target vehicle speed are determined from the estimated speed of the preceding vehicle. The driving source of the vehicle is operated to alternately repeat the acceleration (pulse phase) and deceleration (glide phase) of the vehicle between the determined upper limit target vehicle speed and lower limit target vehicle speed.

A method includes detecting, via a processor of an autonomous vehicle, an upcoming downhill road segment of a route on which the autonomous vehicle is currently travelling. The detection is based on map data, camera data, and/or inertial measurement unit (IMU) data. In response to detecting the upcoming downhill road segment, a descent plan is generated for the autonomous vehicle. The descent plan includes a speed profile and a brake usage plan. The brake usage plan specifies a non-zero amount of retarder usage and an amount of foundation brake usage for a predefined time period. The method also includes autonomously controlling the autonomous vehicle, based on the descent plan, while the autonomous vehicle descends the downhill road segment.

The invention provides a method for controlling braking of a vehicle (1) driving along a downhill portion of a road, the vehicle comprising a propulsion arrangement (2, 3), for the propulsion of the vehicle, the method comprising dividing the road portion into a plurality of sections (RS0-RS2), the sections comprising a first section (RS1), and a second section (RS2) following, in the direction of travel of the vehicle, immediately upon the first section (RS1), determining, for the road portion, a road portion control strategy, with a condition that braking on the road portion is done at least partly by means of the propulsion arrangement (2, 3), wherein determining the road portion control strategy comprises determining a speed (SD21), on the second section (RS2), with an aim to minimize the time travelled on the second section, and/or, where the propulsion arrangement comprises an internal combustion engine (2), and a gearbox (3), determining a gear selection (GS2) on the second section (RS2), with an aim to minimize the time travelled on the second section, and wherein determining the road portion control strategy comprises determining, for the first section (RS1), a first section control strategy, with an aim to minimize the time travelled on the first section, and with an aim to provide a vehicle speed at the end of the first section (RS1) which is the same as said determined speed (SD21) on the second section (RS2), and/or to provide a gear selection at the end of the first section which is the same as said determined gear selection (GS2) on the second section (RS2), the method further comprising controlling the vehicle (1) according to the determined road portion control strategy.

This invention involves the effect of multiple rules of the road at different elevation profiles on the speed constraints and therefore the overall fuel efficiency. A vehicle designed to optimize fuel consumption that is comprised of the rules of the road that determine maximum speed, minimum speed, stop signs, streetlights, and/or changes in other rules that determine the allowable speeds of the road, a localization mechanism, and an optimization engine to optimize the fuel economy by selecting a speed profile within that maintains the vehicle within the assigned range of speeds and minimizes fuel consumption. A wide variety of methods that typically are used to optimize the fuel efficiency of human drivers operating standard vehicles can also be applied towards autonomous vehicles driving at different speed constraints and with different changes in the elevation.

A method and apparatus for determining a slope of a road using a side view camera of a vehicle, the method includes identifying a road image collected from a side view camera, dividing the road image into a plurality of regions, calculating a slope of a road for each of the plurality of regions based on driving lanes comprised in each of the plurality of regions, and determining a slope between the side view camera and the road using the slope of the road calculated for each of the plurality of regions.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

Disclosed are a device and a method of controlling a remote parking assist function capable of determining in advance whether to enter, adjustment, or cancel the remote parking assist function using direct or indirect environment information. The device for controlling a remote parking assist function may collect direct and indirect environment information on a location where a vehicle is to be parked from a surrounding-environment information source, analyze the collected information, and cause activation of at least one of an entry control function, an adjustment control function, or a cancellation control function.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.