Mathematical quantisation method for vehicle multiple target coordinating type self-adapting cruise control performance

Abstract

The invention relates to a mathematic quantization method for vehicle multi-target coordination type self-adaption cruising control performance, which integrates a two-norm function and a linear inequality constraint and establishes mathematic quantization indexes of fuel economy, tracking performance and driver feeling performance in the vehicle MTC ACC process: firstly, utilizing two-norm of the fuel consumption rate in the driving process to reflect a vehicle fuel consumption total amount and establishing a norm type quantization index of the fuel economy; secondly, utilizing the two-norm of a difference of a vehicle speed and a difference of a vehicle distance in the driving process to describe the tracking performance and establish a norm type quantization index of the tracking performance; meanwhile, utilizing an allowed tracking difference standard for a driver obtained by driver test data statistics and establishing a constraint type index of the vehicle distance difference and the vehicle speed difference; thirdly, carrying out quantization on the driver feeling performance comprising a steady-state following distance index, a longitudinal riding comfort index and a driver dynamic following index which are respectively a constraint type index, a constraint type index and a norm type index. The invention can provide a basis for parameter design and performance evaluation of the vehicle MTC ACC.

Description

technical field [0001] The invention relates to a performance evaluation technology of a vehicle driver assistance system, in particular to a mathematical quantification method for the performance of a vehicle multi-target coordinated adaptive cruise control (Multi-Target Coordinated Adaptive Cruise Control, MTC ACC). Background technique [0002] At present, the design of traditional adaptive cruise control (Adaptive Cruise Control, ACC) systems is mostly aimed at tracking performance. With the increasing popularity of the ACC system, people put forward new requirements for its performance, that is, in addition to the necessary tracking performance, it should have the characteristics of low fuel consumption and meet the driver's characteristics at the same time. However, during adaptive cruise, fuel economy, tracking performance and driver experience are at odds with each other. The improvement of fuel economy usually leads to a decrease in vehicle dynamics, which in turn ...

AI Technical Summary

Problems solved by technology

However, during adaptive cruise, fuel economy, tracking performance, and driver experience are in conflict

Increased fuel economy often results in reduced vehicle dynamics, which in turn affects vehicle tracking performance

The reduction of tracking performance will bring about two problems: 1) When the vehicle in front accelerates, the excessive distance between vehicles due to insufficient acceleration ability will easily cause frequent cut-in of the vehicle in front, which will affect the fuel consumption and driver experience of the vehicle; When decelerating, the inter-vehicle distance will decrease rapidly due to insufficient braking capacity, and rear-end collisions are prone to occur, which will affect the safety of the vehicle

Limited to the lack of quantitative standards for vehicle MTC ACC performance, it is difficult to compare the advantages and disadvantages of different MTC ACC methods

Even for the same MTC ACC method, it is impossible to judge the influence of different parameters on the control performance, and it is difficult to realize the parameter optimization design of the control system, which directly affects the development and application of the vehicle MTC ACC system

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