Functional Algorithm for Automated Pedestrian Collision Avoidance System

Similar documents
Automated Driving - Object Perception at 120 KPH Chris Mansley

Our Approach to Automated Driving System Safety. February 2019

Stereo-vision for Active Safety

GOVERNMENT STATUS REPORT OF JAPAN

Study of the Performance of a Driver-vehicle System for Changing the Steering Characteristics of a Vehicle

Control of Mobile Robots

Objective Testing of Autonomous Emergency Braking Systems for the EuroNCAP AEB rating

WHITE PAPER Autonomous Driving A Bird s Eye View

ADVANCED DRIVER ASSISTANCE SYSTEMS, CONNECTED VEHICLE AND DRIVING AUTOMATION STANDARDS, CYBER SECURITY, SHARED MOBILITY

Fleet Penetration of Automated Vehicles: A Microsimulation Analysis

ENGINEERING FOR HUMANS STPA ANALYSIS OF AN AUTOMATED PARKING SYSTEM

A Presentation on. Human Computer Interaction (HMI) in autonomous vehicles for alerting driver during overtaking and lane changing

Understanding the benefits of using a digital valve controller. Mark Buzzell Business Manager, Metso Flow Control

Preliminary Study of the Response of Forward Collision Warning Systems to Motorcycles

Rear-end. kodaka 1 REAR-END COLLISION AVOIDANCE ASSIST SYSTEM

Detailed Design Review

2015 STPA Conference. A s t u d y o n t h e f u s i o n o f S T P A a n d N i s s a n ' s S y s t e m s E n g i n e e r i n g

A factsheet on the safety technology in Volvo s 90 Series cars

ADVANCED EMERGENCY BRAKING SYSTEM (AEBS) DISCLAIMER

STPA in Automotive Domain Advanced Tutorial

Euro NCAP Safety Assist

INFRASTRUCTURE SYSTEMS FOR INTERSECTION COLLISION AVOIDANCE

Using Virtualization to Accelerate the Development of ADAS & Automated Driving Functions

Deep Learning Will Make Truly Self-Driving Cars a Reality

THE FUTURE OF SAFETY IS HERE

A factsheet on Volvo Cars safety technology in the new Volvo S90

Vehicle Dynamics and Drive Control for Adaptive Cruise Vehicles

Adaptive Cruise Control System Overview

Cooperative Autonomous Driving and Interaction with Vulnerable Road Users

Cooperative brake technology

9.03 Fact Sheet: Avoiding & Minimizing Impacts

2017 MDTSEA Manual - How it Corresponds to the ADTSEA 3.0 Curriculum for Segment 1 and 2 Classroom Education

Research Challenges for Automated Vehicles

SIMULATING AUTONOMOUS VEHICLES ON OUR TRANSPORT NETWORKS

AUTONOMOUS VEHICLES: PAST, PRESENT, FUTURE. CEM U. SARAYDAR Director, Electrical and Controls Systems Research Lab GM Global Research & Development

Defensive Driving Training

Problem Definition Review

Control Design of an Automated Highway System (Roberto Horowitz and Pravin Varaiya) Presentation: Erik Wernholt

A Communication-centric Look at Automated Driving

Safe, superior and comfortable driving - Market needs and solutions

Dr. Mohamed Abdel-Aty, P.E. Connected-Autonomous Vehicles (CAV): Background and Opportunities. Trustee Chair

Acustomer calls and says that an ADVANCED DRIVER ASSISTANCE SYSTEMS WHAT YOU SHOULD KNOW ABOUT

Compatibility of STPA with GM System Safety Engineering Process. Padma Sundaram Dave Hartfelder

AEB System for a Curved Road Considering V2Vbased Road Surface Conditions

A Review on Cooperative Adaptive Cruise Control (CACC) Systems: Architectures, Controls, and Applications

Special GRRF Session on

STOPPING SIGHT DISTANCE AS A MINIMUM CRITERION FOR APPROACH SPACING

2015 The MathWorks, Inc. 1

Expansion of Automobile Safety and Mobility Services at TRC Inc. Joshua L. Every Taylor Manahan

FANG Shouen Tongji University

Application Note. First trip test. A circuit breaker spends most of its lifetime conducting current without any

Pedestrian Autonomous Emergency Braking Test Protocol (Version II) February 2019

Tips & Technology For Bosch business partners

Citi's 2016 Car of the Future Symposium

The connected vehicle is the better vehicle!

Application of Autonomous Driving Technology to Transit - Functional Capabilities for Safety and Capacity

Virginia Department of Education

Open & Evolutive UAV Architecture

Fiat - Argentina - Wheel Aligner / Headlamp Aimer #16435

EUROPEAN NEW CAR ASSESSMENT PROGRAMME (Euro NCAP) ASSESSMENT PROTOCOL VULNERABLE ROAD USER PROTECTION

Automation is the techniques and equipment used to achieve automatic operation or control.

EB TechPaper. Staying in lane on highways with EB robinos. elektrobit.com

Purpose of the System...3. System Components...3 Instrument Cluster Display...4

Helping Autonomous Vehicles at Signalized Intersections. Ousama Shebeeb, P. Eng. Traffic Signals Engineer. Ministry of Transportation of Ontario

UNIFIED, SCALABLE AND REPLICABLE CONNECTED AND AUTOMATED DRIVING FOR A SMART CITY

EMERGING TRENDS IN AUTOMOTIVE ACTIVE-SAFETY APPLICATIONS

AEBS and LDWS Exemptions Feasibility Study: 2011 Update. MVWG Meeting, Brussels, 6 th July 2011

Investigation of Developing Vehicle Technologies

Developing a Platoon-Wide Eco-Cooperative Adaptive Cruise Control (CACC) System

Toyota s トヨタの安全への取り組み

METHOD FOR TESTING STEERABILITY AND STABILITY OF MILITARY VEHICLES MOTION USING SR60E STEERING ROBOT

GM-TARDEC Autonomous Safety Collaboration Meeting

Traffic Operations with Connected and Automated Vehicles

University of Michigan s Work Toward Autonomous Cars

Steering Actuator for Autonomous Driving and Platooning *1

Új technológiák a közlekedésbiztonság jövőjéért

Development of California Regulations for Testing and Operation of Automated Driving Systems

The Imperative to Deploy. Automated Driving. CC MA-Info, 15th December 2016 Dr. Hans-Peter Hübner Kay (CC/EB4) Stepper

Pedestrian Autonomous Emergency Braking Test Protocol (Version 1) December 2018

Leveraging AI for Self-Driving Cars at GM. Efrat Rosenman, Ph.D. Head of Cognitive Driving Group General Motors Advanced Technical Center, Israel

B60W. Definition statement. Relationships with other classification places CPC - B60W

Special edition paper

Florida Department of Education Curriculum Framework Grades 9 12, ADULT. Subject Area: Safety and Driver Education

2006 Mercedes-Benz USA, LLC. Chassis and Drivetrain 42

Can STPA contribute to identify hazards of different natures and improve safety of automated vehicles?

DRIVING STABILITY OF A VEHICLE WITH HIGH CENTRE OF GRAVITY DURING ROAD TESTS ON A CIRCULAR PATH AND SINGLE LANE-CHANGE

Appendix A: Motion Control Theory

OnGuard Display Operating Instructions

Accident Avoidance Technologies

On the road to automated vehicles Sensors pave the way!

Copyright 2018 Yamaha Motor Co., Ltd. All Rights Reserved.

Siemens ADAS. Collision avoidance as the first step towards autonomous driving

Smart Control for Electric/Autonomous Vehicles

Procedure for assessing the performance of Autonomous Emergency Braking (AEB) systems in front-to-rear collisions

SAFERIDER Project FP SAFERIDER Andrea Borin November 5th, 2010 Final Event & Demonstration Leicester, UK

Advanced Vehicle Control System Development Div.

Active Safety Systems in Cars -Many semi-automated safety features are available today in new cars. -Building blocks for automated cars in the future.

Fully Active vs. Reactive AWD coupling systems. How much performance is really needed? Thomas Linortner Manager, Systems Architecture

APPLICATION NOTE Application Note for Torque Down Capper Application

Analysis on Steering Gain and Vehicle Handling Performance with Variable Gear-ratio Steering System(VGS)

Transcription:

Functional Algorithm for Automated Pedestrian Collision Avoidance System Customer: Mr. David Agnew, Director Advanced Engineering of Mobis NA Sep 2016 Overview of Need: Autonomous or Highly Automated driving is an area of intense interest by the public and the auto industry. It is obvious that a self driving car must be able to stay in it s lane, brake at intersections, & remain under control during maneuvers, in other words exibit basic driving skills. But another fundamental aspect of the driving function is avoiding collisions (in this case with pedestrians) in emergency situations. Human drivers do this by: 1) Recognizing & responding to potential hazardous situations (identifying a risk and adjusting driving situation to reduce it) 2) Recognizing & responding to immediate hazards (identifying an imminent collision and executing strong avoidance maneuver) Performance Targets: Background for Performance Target 1: For human drivers, a measure of collision avoidance performance can be seen by comparing one s collision rate (assessed after many miles/years of driving) with the population s normal collision rate (gathered by groups such as the IIHS and NHTSA). Performance Target 1: Safety Effectiveness There shall be zero vehicle/pedestrian collisions for each of the scenarios defined in this specification. Background for performance target 2: As with many decisions within a system, a trade-off consideration is often present when deciding course of action for dealing with hazards. It can be argued that human drivers continuously deal with this as between productivity (getting the trip done) and safety (taking precautions to avoid hazards). Consider an extreme example: Safety could be greatly increased if we all decided to drive only at very slow speeds (say 10 mph), but in this case it s easy to see that there is another target in play (efficiency, productivity, etc.) in addition to our

need for safety (the posted speed limits we use can be looked at as a resulting trade-off choice). This leads to the second performance target, Efficiency. Performance Target 2: Efficiency (minimization of lost time) For this project, the efficiency performance target is to minimize any lost time experienced by the vehicle (and it s occupant(s) due to safety maneuvers. System Definition for Automated Pedestrian Collision Avoidance (APCA) General: APCA is fitted to an autonomous vehicle for the purpose of avoiding pedestrians automatically (without human driver intervention). System Functional Behavior: Monitor path in front of vehicle while driving, looking for pedestrians and identifying potential collisions with them. Determine potential collisions by analyzing collision path between vehicle and pedestrian. Take action to avoid pedestrians by executing velocity reduction commands (automatic braking) which override the current steady state velocity of the vehicle. The braking command will activate the brake by wire system in the vehicle to reduce velocity as requested by the system. When the command is ended (hazard no longer exists), vehicle velocity will automatically return to steady state velocity. System Architecture: Safety Controller Pedestrian Detection Sensor Pedestrian info PCA Algo Braking Request Vehicle Brake by Wire System Veh Red Vehicle Speed

Sub-systems and Interfaces: Pedestrian Sensor: The pedestrian sensor is a stereo camera with following properties: Output: -Pedestrian recognition and tracking -Pedestrian location (x,y)relative to car with accuracy +/-.5 m -Pedestrian velocity (speed & direction). Speed +/-.2 m/s. Direction +/- 5 deg -Cycle time: Above signals are sent as a packet every 100 ms Brake-by-Wire Actuator The BBW sub-system responds to deceleration requests by interrupting the steady state velocity control (cruise control) and then applying brake torque via elctro mechanical actuators at all four wheels of the vehicle, and sensing the actual vehicle decel for closed loop control. The BBW system can respond to these brake requests about as fast as a human driver is capable, exhibiting the following properties: -Deceleration accuracy: +/- 2% -Response time to reach requested decel: 200 ms -Release time: 100 ms -Maximum deceleration: 0.7 g (1g = 9.81 m/s^2) Vehicle: The autonomous vehicle for this application will have the following properties: -Normal steady state speed: 50 kph (13.9 m/s) -Acceleration to steady state speed (after auto brake apply):.25 g -Vehicle Width (collision zone): 2 m Pedestrian: The pedestrian for this application will be modeled/characterized as follows: -Can be static or in motion (speed = 0 or 6 kph) -Can change velocity with infinite acceleration (assumption) -The size of the pedestrian in the x-y plane shall be considered a circle with.5 m diameter -When moving, only moves at right angle to vehicle path

-Pedestrian behavior for system development & test is defined in the below scenarios

Scenarios Vehicle: Speed: Always initially at steady state velocity, controllable with brake-by-wire system Heading: Always straight along +x axis Initial Position: Always at x,y = 0,0 Pedestrian: Speed: static or constant (per spec) Heading: Always parallel to y axis Initial Position: x= 35 m, y= -7m y 0,0 x 35 m Yi Reference: potential collision at 2.5 sec Pedestrian Motion Scenarios:

Moving then stopped Initial End Position, Initial Final Scen # Position, Yi Yf Speed Speed (m) (m) (kph) (kph) 1-7 0 10 0 2-7 -2 10 0 3-7 -3 10 0 4-7 -5 10 0 Static then moving Scen # Initial Position, Yi Delay before moving Initial Speed Final Speed (m) (s) (kph) (kph) 5 0 1.5 0 10 6-2 1.8 0 10 7-4 1.1 0 10 Static (m) (kph) (kph) 8 0 NA 0 0 9-2 NA 0 0 10-4 NA 0 0 System (Algorithm) Performance Requirements: 1) Effectiveness: Zero collisions allowed under all 10 scenarios 2) Efficiency: Lost time shall be minimized for all non-collision scenarios (lost time should be reported during simulations) Definition of lost time :

Time difference (in seconds) between system on and system off to reach a common point beyond the pedestrian with controlled vehicle back again at steady state velocity. speed System on System off common point (what is time delta to reach this point) 0 m 35 m distance

Fail Safe Requirements: 1) A fail operational mode for the brake system increases the response time to reach requested decel from 200 ms to 900 ms. In this mode, the algorithm should adjust to maintain zero collisions in trade for increased lost time This mode should be simulated and verified. Notes: 1) One algorithm (system) must be used for measuring performance against all 10 scenarios 2) The system algo should be constructed assuming it does not know which scenario is occuring. The only pedestrian information available comes from the sensor. 3) Consider how to determine if system is optimized. Are you competing with other systems?