Model-supported allocation of vehicles to traffic lanes

• US 7,593,838 B2
• Filed: 03/08/2001
• Issued: 09/22/2009
• Est. Priority Date: 03/28/2000
• Status: Expired due to Fees

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Kederer, Werner, Detlefsen, Juergen, Winter, Klaus, Lueder, Jens
• Primary Examiner(s): Rodriguez; Paul L
• Assistant Examiner(s): PIERRE LOUIS, ANDRE
• Application Number:
  US09/980,146
• Publication Number:
  US 20020183928A1
• Time in Patent Office: 3,120 Days
• Field of Search: 703/8, 701/300, 701/93, 701/200, 701/96
• US Class Current: 703/8
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 7/4004 of parts of a radar system
• CPC Class Codes: G01S 7/4026 Antenna boresight
• CPC Class Codes: G01S 7/403 in azimuth, i.e. in the horizontal plane
• CPC Class Codes: G01S 7/4052 by simulation of echoes
• CPC Class Codes: G01S 7/4091 during normal radar operation

Abstract

A method as well as a device for the lane allocation of consecutive vehicles, the lane allocation being carried out in a model-based manner via a frequency distribution of the lateral displacements of detected radar objects. The method is additionally used for detecting the misalignment of the sensor.

Claims

1. A method for a motor vehicle having an adaptive distance and speed control for lane allocation of vehicles on multi-lane roads, by using a model-based lane and misalignment detection, the method comprising:

acquiring radar object data from measured data of a radar sensor;

filtering the radar object data by at least one of (i) considering only once every object for a lateral displacement histogram, and (ii) considering every object with a weighting, the weighting depending upon how many times an object was detected in individual measurements;

registering the filtered data in a lateral displacement histogram, a frequency of the filtered object data being stored in the lateral displacement histogram as a function of the measured lateral displacement of the vehicle'"'"'s longitudinal axis;

correlating an instantaneously determined, current lateral displacement histogram to every stored reference lane model, wherein a result of every correlation from the instantaneous lateral displacement histogram to one of the reference lane models is a correlation result that increases as a similarity of the instantaneous lateral displacement histogram increases as to the reference histogram;

selecting the reference histogram having a highest correlation to determine acquired information, which includes a number of lanes, a used lane, and a possible misalignment of the radar sensor; and

outputting the acquired information for processing.

2. The method of claim 1, further comprising:

obtaining a histogram having a plurality of maxima according to a number of detected lanes and their relative position with respect to the vehicle in the used lane;

determining a horizontal misalignment of the radar sensor from a position of average values for the lanes in the histogram with respect to a vehicle center axis, wherein in addition to a lateral displacement, a further histogram regarding a distance of an observed object is stored with an equivalent object treatment, and a misalignment angle is determined by determining a centroid of the histograms.