Adaptive Cruise Control Virtual Target Vehicle Group
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Solution Overview
Problem
Existing adaptive cruise control systems are ineffective in managing the behavior of a single lead vehicle, leading to inefficient fuel consumption and poor performance when the lead vehicle brakes and accelerates beyond the desired time gap, and struggle in adverse weather conditions and with non-reflective vehicles.
Innovation Solution
An adaptive cruise control system that simultaneously detects and monitors multiple target vehicles, calculates a virtual target vehicle's velocity and distance based on group behavior, and adjusts the equipped vehicle's velocity to maintain a smooth and eco-friendly pace, using radar, LIDAR, or camera units, and considers road conditions and vehicle importance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single lead vehicle is monitored for adaptive cruise control, then the system is simple to operate, but fuel consumption increases and performance deteriorates when the lead vehicle brakes and accelerates beyond the desired time gap
Solution Approach 1:
The patent combines multiple target vehicle detections into a unified control decision system. Instead of selecting a single lead vehicle, the system integrates information from multiple detected vehicles and generates coordinated control signals that consider the collective behavior of all detected targets, thereby reducing unnecessary braking and acceleration events that waste fuel
2Loss of energy
If multiple vehicles are monitored simultaneously, then fuel efficiency improves by predicting and smoothing vehicle actions, but the system complexity increases
Solution Approach 1:
The patent creates virtual target vehicles that represent aggregated behavior patterns of multiple detected vehicles. Instead of processing each individual vehicle separately, the system generates simplified virtual targets that capture the essential motion characteristics of the group, reducing computational complexity while maintaining the fuel efficiency benefits of multi-vehicle monitoring
Solution Approach 2:
The system performs preliminary analysis of multiple target vehicle behaviors to predict future motion patterns before generating control signals. By anticipating the collective behavior of detected vehicles in advance, the system can smooth acceleration and braking actions, improving fuel efficiency while managing complexity through proactive rather than reactive control
3Ease of manufacture
If laser-based sensors are used for detection, then the system cost is reduced, but detection performance deteriorates in adverse weather conditions and with non-reflective vehicles
Solution Approach 1:
The patent implements a multi-functional detection system that can operate with different sensor types (laser-based and radar-based) depending on environmental conditions. The system automatically selects or combines sensor modalities to maintain reliable detection performance across varying weather conditions and vehicle types, ensuring both cost-effectiveness and reliability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the negative impact of lead vehicle behavior by predicting and smoothing the actions of multiple vehicles, improving fuel efficiency and performance by correlating the motions of vehicles in a group, and enhancing operation in adverse conditions.
Implementation Method 1
The object detecting means comprises a radar unit or a LIDAR unit or a camera unit for establishing a distance value and a velocity value for each of the detected target objects
Implementation Method 2
The object detecting means comprises a radar unit or a LIDAR unit or a camera unit for establishing a distance value and a velocity value for each of the detected target objects
Data Source
Figure 1~2
AI summary
An adaptive cruise control system for a motor vehicle (1) comprises a forward looking object detecting means arranged to simultaneously detect several target objects (3, 4, 5) moving in the predicted path and adjacent paths of the equipped vehicle (1). The means are further arranged to continuously monitor velocity and distance to each of said target objects (3, 4, 5), processing means arranged to process signals from said detecting means to provide information of distance to and relative speed of vehicles (3, 4, 5) travelling in front of the equipped vehicle (1), wherein the processing means further is arranged to repeatedly generate velocity control signals based on the information of distance to and relative speed of vehicles (3, 4, 5) travelling in front of the equipped vehicle (1), and means to control velocity of the equipped vehicle (1) in response to the control signals from the processing means. The processing means is further arranged to calculate a distance in time from the equipped vehicle (1) to a virtual target vehicle (6), the distance to and velocity of said virtual target vehicle (6) calculated on basis of the number of vehicles in said group, the spread in distance of the group, and thus the vehicle density of said group, and the variability of positions in the group, such that the algorithm of the processing means decides from the above parameters on the allowed deviations in time distance, wherein the processing means is arranged to produce a signal to the means for controlling the velocity of the equipped vehicle (1) that is based on the calculated distance in time between the equipped vehicle (1) and said virtual vehicle (6).