Lane change assistant for optimizing the traffic flow (traffic flow assistant)

• US 9,576,483 B2
• Filed: 08/01/2013
• Issued: 02/21/2017
• Est. Priority Date: 08/23/2012
• Status: Active Grant

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Maass, Alexander
• Primary Examiner(s): Tweel, Jr., John A
• Application Number:
  US14/420,037
• Publication Number:
  US 20150194055A1
• Time in Patent Office: 1,300 Days
• Field of Search: 340/905, 340/933, 340/934, 701/23, 701/96, 701/118, 701/301
• US Class Current: 1/1
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
• CPC Class Codes: G08G 1/096708 where the received information might be used to generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

A device for a traffic flow assistant for a vehicle includes a surroundings sensor system, which recognizes traffic-relevant objects on a traffic lane, on which the vehicle is traveling, and on at least one further adjacent lane, gaps in the traffic are recognized with the aid of the surroundings sensor system and vehicle-dynamic parameters of the objects are determined and future gaps in the flow of traffic are able to be predicted therefrom. For these recognized gaps and predicted gaps, lane change options are ascertained and, from this and the present and/or predicted presence of gaps in the traffic suitable for changing lanes and the vehicle-dynamic state of the vehicle, a signal for the lane selection is generated, which is dependent on the lane change options and an optimization strategy.

Claims

1. A traffic flow assistant for a vehicle, comprising:

a surroundings sensor system configured to;

(i) recognize traffic-relevant objects on a traffic lane on which the vehicle is traveling and on at least one adjacent lane, and (ii) recognize specific presently existing gaps in the traffic surrounding the vehicle and determine vehicle-dynamic parameters of the objects, wherein specific future gaps in the traffic are predicted based on the vehicle-dynamic parameters; and

a control unit configured to;

(a) ascertain options for changing lanes, depending on the vehicle-dynamic state of the vehicle and at least one of;

i) the specific presently existing gaps in the traffic suitable for changing lanes, and ii) the predicted presence of specific future gaps in the traffic suitable for changing lanes, and (b) generate a signal for the lane selection, depending on the ascertained options for the lane change and a predefined optimization strategy;

wherein, on the basis of the signal, one of;

a lane selection is suggested to the driver autonomously;

or a driving maneuver is automatically initiated without action of the driver.

2. The traffic flow assistant as recited in claim 1, wherein vehicle-dynamic capabilities of at least one of the host vehicle and the traffic-relevant objects are also taken into consideration to ascertain the options for changing lanes.

3. The traffic flow assistant as recited in claim 2, wherein the optimization strategy includes at least one of:

a strategy of rapid progress;

a strategy of minimizing lane changes;

a strategy of achieving predefined safety distances of the vehicle from the other objects;

a strategy of one of a predefined energy consumption rate or a predefined fuel consumption rate;

a strategy of one of a predefined acceleration or a predefined difference between the vehicle and at least one object;

a strategy of minimizing one of a hazard or hazard potential; and

a strategy of an early signaling to the other objects.

4. The traffic flow assistant as recited in claim 3, wherein the strategy is determined by one of:

manual input;

surroundings conditions;

prioritization;

or vehicle-dynamic capabilities of the vehicle.

5. The traffic flow assistant as recited in claim 3, wherein the optimization strategy is oriented at least one of:

to the host vehicle; and

to all traffic-relevant objects.

6. The traffic flow assistant as recited in claim 2, wherein the signal for the lane selection is generated by additionally taking into account a lane evaluation of at least one of the vehicle'"'"'s present lane and the at least one adjacent traffic lane.

7. The traffic flow assistant as recited in claim 6, wherein the lane evaluation is dependent on at least one of:

a present geometry of the traffic lanes;

upcoming geometry of the traffic lanes;

ground condition of the traffic lanes;

a reason for a driving speed change;

a lane end; and

a lane expansion.

8. The traffic flow assistant as recited in claim 2, wherein traffic regulations are also taken into consideration in generating the lane selection signal.

10. The traffic flow assistant as recited in claim 1, wherein the specific presently existing gaps in traffic and the specific future gaps in traffic are suitable for changing lanes when a distance between two traffic-relevant objects is sufficiently large that the vehicle can fit therebetween.

9. A method for optimizing a traffic flow for a vehicle, comprising:

ascertaining traffic-relevant objects on a traffic lane on which the vehicle is traveling and on at least one adjacent lane;

ascertaining specific presently existing gaps in the traffic surrounding the vehicle and determining vehicle-dynamic parameters of the objects, wherein specific future gaps in the traffic are predicted based on the vehicle-dynamic parameters;

ascertaining options for changing lanes, depending on the vehicle-dynamic state of the vehicle and at least one of;

i) the specific presently existing gaps in the traffic suitable for changing lanes, and ii) the predicted presence of specific future gaps suitable for changing lanes in the traffic; and

generating a signal for the lane selection, depending on the ascertained options for the lane change and a predefined optimization strategy;

wherein, on the basis of the signal, one of;

the lane selection is suggested to the driver autonomously;

or a driving maneuver is automatically initiated without action of the driver.

11. The traffic flow assistant as recited in claim 9, wherein the specific presently existing gaps in traffic and the specific future gaps in traffic are suitable for changing lanes when a distance between two traffic-relevant objects is sufficiently large that the vehicle can fit therebetween.