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Enhanced AHS Safety Through the Integration of Vehicle Control and Communication. October 2002 J. K. Hedrick, R. Sengupta, Q. Xu, C. Lee, Y. Kang. Communication architecture. Goal = wireless network useful for: 1) Cooperative friction estimation 2) Cooperative Emergency Maneuver

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Enhanced AHS Safety Through the Integration of Vehicle Control and Communication

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Enhanced ahs safety through the integration of vehicle control and communication l.jpg

Enhanced AHS Safety Through the Integration of Vehicle Control and Communication

October 2002

J. K. Hedrick, R. Sengupta,

Q. Xu, C. Lee, Y. Kang


Research areas l.jpg

Communication architecture

Goal = wireless network useful for:

1) Cooperative friction estimation

2) Cooperative Emergency Maneuver

3) AHS and cooperative

adaptive cruise control

Emergency Braking Maneuvers

Tire/road friction estimation

Goal: Develop a safe control strategy for the emergency braking maneuver of platoons.

Goal: Real time estimation of maximum tire-road friction

Research Areas


Project goals l.jpg

Communication architecture

Tire/road friction estimation

Road

Condition & Maximum

Friction Coeff.

Information from other vehicles and road side infra structure.

Emergency Braking Maneuvers

“ SAFETY ”

Project Goals


Slip based road condition estimation l.jpg

Slip-based Road Condition Estimation


Overview and benefits of the research l.jpg

Overview andBenefits of the Research

  • Overview

    • Empirical approach

    • Effect-based method

    • Real Time work

  • Benefits

    • Estimation of max. acceleration limit of the vehicle.

    • Emergency Braking Control for the Platoon.

    • Road Condition vs. Position Map.


Slip friction coefficient calculation l.jpg

Slip/Friction Coefficient Calculation

  • Friction Coefficient

  • Slip

  • Max Acceleration

Maximum friction coefficients determines

maximum acceleration or deceleration


Slip slope vs l.jpg

Slip Slope Vs

Affecting Factors

  • Road Condition

  • Tire Type

  • Tread Pattern

  • Tread Depth

  • Velocity

Focus on Linear Region

Slip Slope, k


Schematic of the estimator l.jpg

Schematic of the Estimator


Static normal force observer l.jpg

Static Normal Force Observer

Normal Force friction coefficient calculation

effective tire radius estimation

Static normal force observer assumes a static model for vehicle3% error comparing to dynamic vehicle model

Static Normal Force Model


Effective tire radius observer l.jpg

Effective Tire Radius Observer

  • Tire radius is required for Slip Calculation

Tire Radius Change is a Function of

  • Normal Force

  • Tire Pressure

  • Velocity


Tractive force estimation l.jpg

Tractive Force Estimation


Brake gain estimator l.jpg

Brake Gain Estimator

  • Brake Gain Change

    • Heat

    • Water

    • Wear of Brake Pad, etc.

sometimes changes more than 50%

  • Model : Front Wheel Dynamics

  • Method : Recursive Least Square Method Using Bounded Forgetting


Slip slope vs13 l.jpg

Slip Slope Vs

Each vehicle has its own slip slope under same road

Dry road condition set as Reference slip slope

Maximum friction coefficient change rate / Slip slope change rate based on reference slip slope

Linear Assumption


Slip slope and estimation l.jpg

Slip Slope and Estimation

  • Example : Wet  Dry

Slip Slope Estimation

Using RLS method

Estimation

Based on slip slope


Emergency braking maneuvers l.jpg

Emergency Braking Maneuvers


Emergency braking controller longitudinal control l.jpg

Emergency Braking Controller(Longitudinal Control)

  • Requirements for emergency braking control

    • Control robustness against the high slip condition between road and tire.

    • Friction coefficients estimation algorithm.

  • Control method : Dynamic Surface Control


Experimental set up l.jpg

Experimental Set-up

  • Experimental Vehicle used

    : Ford red Lincoln town car

  • Sensors and actuators

    : wheel speed sensors

    brake pressure sensors

    5th wheel speed sensor

    brake and throttle actuators

  • Computers with real-time OS

    : QNX operating system


Simulation results l.jpg

Simulation Results

  • Simulation with Dynamic Surface Control (6 m/s2 deceleration)


Experimental results l.jpg

Experimental Results

  • Experiments in same situation

    ( 6 m/s2 deceleration)


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Analysis of the Result

  • The performance of the Dynamic Surface Controller is reasonable(1~2m error with –6 m/s2) in an emergency braking situation.

  • Control performance depends on friction coefficients.

     “Friction coefficient estimation” is

    important.


Emergency braking control strategies for platoons l.jpg

((((

Emergency Braking Control Strategies for Platoons

  • Emergency braking for the Platoons

    : Difference of max. deceleration limit between vehicles can result in collision.

  • Cooperative Emergency Control.

))))

Vehicle with Worst Braking Capacity transmits its info.


Simulation results22 l.jpg

Simulation Results

  • Space & velocity tracking

[m/s]

[m]


  • Login