safety impact methodology
DESCRIPTION
Safety Impact Methodology. Mikio Yanagisawa RITA / Volpe ITS Connected Vehicle Public Meeting Arlington, VA September 24-26, 2013. Safety Benefits – Basic Equations. Data Sources # Target Crashes : Crash databases (GES, FARS,…) - PowerPoint PPT PresentationTRANSCRIPT
1
Safety Impact Methodology
Mikio Yanagisawa
RITA / Volpe
ITS Connected Vehicle Public Meeting
Arlington, VA
September 24-26, 2013
2
Safety Benefits – Basic Equations
Data Sources• # Target Crashes: Crash databases (GES, FARS,…)• Exposure Ratio: Field operational tests and controlled experiments• Crash Prevention Ratio: Field tests, objective tests, controlled experiments,
and computer simulation Safety Impact Methodology (SIM) tool
𝑬𝒙𝒑𝒐𝒔𝒖𝒓𝒆𝑹𝒂𝒕𝒊𝒐=𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒𝑡𝑜𝐷𝑟𝑖𝑣𝑖𝑛𝑔𝐶𝑜𝑛𝑓𝑙𝑖𝑐𝑡𝑠𝒘𝒊𝒕𝒉𝑉 2𝑉
𝐸𝑥𝑝𝑜𝑠𝑢𝑟𝑒𝑡𝑜𝐷𝑟𝑖𝑣𝑖𝑛𝑔𝐶𝑜𝑛𝑓𝑙𝑖𝑐𝑡𝑠𝒘𝒊𝒕𝒉𝒐𝒖𝒕𝑉 2𝑉
𝑪𝒓𝒂𝒔𝒉𝑷𝒓𝒆𝒗𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒂𝒕𝒊𝒐=h𝐶𝑟𝑎𝑠 𝑃𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑖𝑛𝐷𝑟𝑖𝑣𝑖𝑛𝑔𝐶𝑜𝑛𝑓𝑙𝑖𝑐𝑡𝒘𝒊𝒕𝒉𝑉 2𝑉
h𝐶𝑟𝑎𝑠 𝑃𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑖𝑛𝐷𝑟𝑖𝑣𝑖𝑛𝑔𝐶𝑜𝑛𝑓𝑙𝑖𝑐𝑡𝒘𝒊𝒕𝒉𝒐𝒖𝒕𝑉 2𝑉
𝐴𝑝𝑝𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑛𝑒𝑠𝑠=1−𝑬𝒙𝒑𝒐𝒔𝒖𝒓𝒆𝑹𝒂𝒕𝒊𝒐𝒏×𝑪𝒓𝒂𝒔𝒉𝑷𝒓𝒆𝒗𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒂𝒕𝒊𝒐
¿ h𝐶𝑟𝑎𝑠 𝑒𝑠 𝐴𝑣𝑜𝑖𝑑𝑒𝑑=¿𝑇𝑎𝑟𝑔𝑒𝑡 h𝐶𝑟𝑎𝑠 𝑒𝑠× 𝐴𝑝𝑝𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑛𝑒𝑠𝑠
3
SIM Tool Overview
Crashes without V2V
Conflict exposure
with / without V2V
Harm from crashes
without V2V
Probability of crash
V distributions
Crashes prevented
Harm reduced
SIM Tool
Safety Impact Methodology
(SIM)
• SIM estimates effectiveness of individual scenarios
• SIM estimates are based on 100% system deployment
• SIM tool is developed for evaluation, not design
4
Rear-End Pre-Crash Simulation
Rear-End SIM
Simulation
DRIVER
Reaction Time
Braking Level
Control vs. Treatment
VEHICLE
Host Vehicle State
Remote Vehicle State
SYSTEM
Time-to-Collision of Warning
Automatic System Activation
Number of Crashes Number of Non-Crashes Impact Speed Distribution ΔV Distribution Host and Remote
Effectiveness
5
Rear-End Pre-Crash Walkthrough (LVS)
Control
Treatment
6
Probability of Crash EstimationExample: Lead Vehicle Stopped – Brake Response
{IF dstop ≤ dinitial THEN crash is prevented, ELSE crash occurs}
Run Monte Carlo simulations by drawing random numbers from tR & aH distributions and account for crashes occurred and prevented:
1. tR & aH from drivers without system assistance
2. tR & aH from drivers with system assistance
𝑑𝑖𝑛𝑖𝑡𝑖𝑎𝑙=𝑇𝑇𝐶𝑤𝑎𝑟𝑛×𝑣𝐻
𝑑𝑠𝑡𝑜𝑝=𝑣𝐻
2
2𝑎𝐻
+(𝑣𝐻×𝑡𝑅 )
Initial ConditionsvH = Host velocityTTCwarn = Time-to-collision of warning
Driver ResponsetR = Reaction time from warningaH = Host average deceleration
7
Lane Change Pre-Crash Simulation
Lane Change
SIM Simulation
DRIVER
Driver Reaction Time
Driver Counter Steer
Control vs. Treatment
VEHICLE
Host Vehicle State
Remote Vehicle State
SYSTEM
Initial Lateral Distance
Number of Crashes Number of Non-Crashes Impact Speed Distribution ΔV Distribution Host and Remote
Effectiveness
8
Lane Change Pre-Crash Walkthrough
Control
Treatment
9
Intersection Pre-Crash Simulation
Intersection SIM
Simulation
DRIVER
Driver Reaction Time
Driver Braking Level
Control vs. Treatment
VEHICLE
Host Vehicle State
Remote Vehicle State
Host Distance and Acceleration (Encroaching)
SYSTEM
Time-to-Intersection
Number of Crashes Number of Non-Crashes Impact Speed Distribution ΔV Distribution Host and Remote
Effectiveness
10
Straight Crossing Paths – Both Vehicles Moving
Control Treatment
11
Straight Crossing Paths – Stopped and Starting
Control Treatment
12
Input Parameters
Driver Reaction (Control) Link
?
Driver Reaction (Treatment)
Brake Force (Control)
Brake Force (Treatment)
Link?
Data Field Track Experiment Literature
Relationships Dependencies Flexible Variable inputs
*Example Mock DataLink
?
Link
?
13
SIM Results and Analysis
Pre-crash modeCrash CountImpact ModeTreatment TypeCrash Severity
SIM
pCrashCrash Ratio
Crash SeveritySpeed Reduction
Analysis
Results from SIM analyzed for effectiveness Applied to appropriate target population Pre-crash scenarios combined Effectiveness estimates lead to overall benefits