Adaptive Cruise Control Shadow Detection via Temporal Motion Analysis

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing driver assistance systems face challenges in accurately distinguishing and evaluating shadows cast by static objects, such as bridges or overpasses, in sensor images due to lighting effects, which can lead to difficulties in object detection and adaptive cruise control in varying traffic conditions.

Innovation Solution

A method for evaluating sensor images using time series analysis to determine if dark areas are moving at the speed of the vehicle, employing detection areas with specific distance thresholds and exposure control to differentiate static shadows from moving objects and ignore moving shadows, with a computer program product for implementing this method in a vehicle's environment recognition system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If dark areas in sensor images are evaluated to detect shadows cast by static objects, then the system can identify bridges and overpasses, but moving objects with similar brightness patterns may be misidentified as shadows

Engineering Contradiction:
Improveshadow detection accuracyVSAvoiddistinguishing shadows from moving objects
Core Design Contradiction:
ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system dynamically evaluates the temporal behavior of dark areas by comparing their motion patterns against the carrier's movement. Static shadows remain stationary relative to the ground while moving objects change position independently, allowing the system to distinguish between them through dynamic analysis of brightness value changes over time

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system uses feedback from the carrier's speed and position data to verify whether detected dark areas move consistently with the carrier's motion. By continuously comparing the apparent motion of dark areas against expected motion based on carrier dynamics, the system can confirm or reject shadow hypotheses

Inventive Principle:
Principle #23Feedback

2Measurement precision

If time series analysis is used to evaluate brightness values and determine if dark areas move at carrier speed, then static shadows can be accurately identified, but the computational complexity and processing time increase

Engineering Contradiction:
Improveshadow detection precisionVSAvoidevaluation system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The evaluation process is segmented into distinct stages: initial detection of dark areas, temporal evaluation of brightness values, motion verification against carrier speed, and final classification. This segmentation allows complex time series analysis to be broken down into manageable processing steps that can be implemented efficiently

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system applies partial action by evaluating only those pixel regions that exhibit darkness characteristics, rather than processing the entire image. By focusing computational resources on suspicious dark areas and their temporal variations, the system achieves high measurement precision without requiring excessive processing of all image data

Inventive Principle:
Principle #16Partial or excessive action

3Reliability

If detection areas with specific distance thresholds are employed to differentiate static shadows from moving objects, then shadow identification improves, but the system becomes more sensitive to variations in detection parameters

Engineering Contradiction:
Improveshadow recognition reliabilityVSAvoidparameter sensitivity
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system adapts detection parameters dynamically based on carrier speed, imaging geometry, and environmental conditions. By adjusting distance thresholds and brightness evaluation criteria according to current operating parameters, the system maintains high reliability across varying driving conditions while reducing sensitivity to fixed parameter settings

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP2181414B1Method and system for evaluating brightness values in sensor images of image-evaluating adaptive cruise control systems
Publication Date: 2017.06.14 VALEO SCHALTER & SENSOREN GMBH
  • EP2181414B1 patent drawingFigure 1~2
  • EP2181414B1 patent drawingFigure 3~4
  • EP2181414B1 patent drawingFigure 5

AI summary

The invention relates to a method and a system for evaluating brightness values in sensor images of an image-evaluating adaptive cruise control system on a moving support, preferably a vehicle (1). According to the invention, areas in the sensor images detected by a camera (4) which are dark in comparison to the surroundings are evaluated in temporally successive evaluation steps to see whether they move towards the support at the speed of the support. These dark areas are recognized as the shadows (7) of a static object and a corresponding alert is given.