state of the art automated safety analysis and data collection … · 2014-01-23 · surrey data...
TRANSCRIPT
State of the Art Automated
Safety Analysis and Data
Collection Techniques
Tarek Sayed, Ph.D., P.Eng.
Professor
University of British Columbia
Outline
Motivation
Applications
Diagnosing Safety Issues
Before/After Safety Evaluations
Automated Identification of Violations (Non Conforming
Behaviour)
Automated Data Collection (Volume, Speed and
Classification)
Future Developments
Conclusion
Motivation (Safety)
Traditional road safety analysis is a reactive approach, based on historical collision data There are well-recognized availability and quality
problems associated with collision data
Long observation periods
Less complete understanding of the complex interaction of collision factors and how safety measures work
A more proactive approach is needed which provides a better understanding of collision occurrence The earlier that road safety is considered, the more
cost-effectively it can be accommodated
Traffic Conflicts (near-misses)
Shortcomings Cost of data collection
Issues related to the reliability and accuracy of human observers
Automation can enable the traffic conflict analysis in an accurate, objective, and cost-efficient way
Source: Hyden, 1987
Motivation – Data Collection
Road-user movements and behavior are complex
and difficult to capture manually
A disparate mix of road users share the same road
Manual methods are more expensive, error-prone,
and time consuming
Features Tracking Features Grouping Objects Classification
Prototypes Generation Events Detection Violation Detection
Automated Analysis Procedure
Real-world Coordinates
Recovery
1 2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
1
2
3
4
5 6
7 8 9 1
0 11
12
13
14
15
16
17
18
19 2
0
21
22
Camera Calibration
Classify Road-Users based on their Speed
Profiles using computer vision
Pedestrians: Ambulation
Cyclists: Pedaling
Vehicle: Mostly-Linear Movements
Movement Mechanisms
Classification
12
Pedestrian Ambulation
Surrey Data Set 2 UBC Roundabout Data Set 3
85-96% Correct Classification rate
Surrey Data Set 1
Classification: Road-Users
Classification: Road-Users
Pedestrians
Pedestrians
Vehicles
Cyclists
Classification: Road-Users Size
Analysis of Collisions
Safety Diagnosis - UBC
Roundabout
Wesbrook Mall & 16th Ave
18
Camera Calibration
Results
Exposure calculation
Entering V.
4902
Existing V.
4350
544
Passing Ped.
Crossing Ped.
651
465 Crossing Ped.
Passing Ped.
384
Circulating inn. out. Lane
7681 + 4716 = 12397 Existing
10913
Passing Ped.
396 600
Crossing Ped.
Circulating
6386
1 2
1 2
1 2
1
2
1
2
Non- Conforming Driver
Behavior
Diagnosing Safety
Problems
Vehicle-Vehicle conflicts/area
Diagnosing Safety
Problems
Vehicle-Vehicle conflicts/area
Cyclists Data Collection at a Roundabout
(Westbrook Mall and 16th Avenue, UBC)
Cyclist Conflicts Zone
Burrard and Pacific Intersection
Camera
Location
Vehicle Conflicts Zones Burrard and Pacific Intersection
Camera
Location
Location Manual
Detection per
hour
Automated
Detection per
hour
Accuracy
Southbound 64 73 86%
Northbound 92 99 92%
Vehicles Violations Identification
Burrard and Pacific Intersection
Camera
Location
Vehicles Conflicts Evaluation Burrard and Pacific Intersection
Cyclists Conflicts Evaluation Burrard and Pacific Intersection
Countermeasures
Road Markings and Signage
Close The Right Turn Ramp
Urban Smart Channels
Proposed Geometric Modifications Burrard and Pacific Intersection
Proposed Geometric Modifications Burrard and Pacific Intersection
Signal Phasing for the Proposed Modifications Burrard and Pacific Intersection
MicroSimulation Evaluation of the Proposed Modifications
Burrard and Pacific Intersection
Location Violations per
Hour
Eastbound 35
Westbound 210
Southbound 145
Vehicle Violations Identification
Hastings and Main Intersection
Pedestrians Conflicts Evaluation Hastings and Main Intersection
Conflicts Analysis Summary Hastings and Main Intersection
North-South Crossing Pedestrians and Right-turn Vehicles TTC range # Events 0-1 seconds 66 1-2 seconds 43 2-3 seconds 45
TOTAL 154
EDMONTON – B/A YELLOWHEAD
/ VICTORIA TRAIL RAMP
Motion Patterns
Results Frequency and Cumulative Distributions of
Conflicts
Results
Conflict Severity Distribution
Conflict Severity Analysis
Penticton, BC - Before/After
Analysis of Right-turn Treatment
Penticton, BC - Before/After
Analysis of Right-turn Treatment
Comparison with Collision-based FB
B/A Evaluation
Intersection/severity Traffic conflicts
(Average Hourly Conflicts)
Collisions
(on 4-month basis)
T1 – Channel/Green 33% 34.2%a
T2 – Channel/Warren 57% 60.3%a
T3 – Channel/Duncan 55% 48.1%a
Overall 51% 56.3%b
Total Severity Conflict Severity: 41% PDO: 59.2%c
F+I: 48.8%c
Before/After Evaluation of Pedestrian
Scramble
Results
Before-and-After Conflict Indicators
0 2 4 6 8 10 12 14 16 18 200
100
200
300
400
500
600Histogram of Before-and-After TTC
TTCmin
in seconds
Fre
quency o
f tr
aff
ic e
vents
-10 -8 -6 -4 -2 0 2 4 6 8 100
2000
4000
6000
8000
10000
12000
DSTmax
in seconds
Fre
quency o
f tr
aff
ic e
vents
Histogram of Before-and-After DST
-20 -15 -10 -5 0 5 10 15 200
500
1000
1500
2000
2500
3000
PET in seconds
Fre
quency o
f tr
aff
ic e
vents
Histogram of Before-and-After PET
0 2 4 6 8 10 12 14 16 18 200
1000
2000
3000
4000
5000
|PET| in seconds
Fre
quency o
f tr
aff
ic e
vents
Histogram of Before-and-After |PET|
-5 0 5 10 15 200
1000
2000
3000
4000
GTmin
in seconds
Fre
quency o
f tr
aff
ic e
vents
Histogram of Before-and-After GT
0 2 4 6 8 10 12 14 16 18 200
1000
2000
3000
4000
|GTmin
|in seconds
Fre
quency o
f tr
aff
ic e
vents
Histogram of Before-and-After |GT|
TTC Before
TTC After
DST Before
DST After
PET Before
PET After
|PET| Before
|PET| After
GT Before
GT After
|GT| Before
|GT| After
Manual
Counts
Automated
Counts
Accuracy
Screen line 1 229 255 88.6%
Screen line 2 4880 4441 91 %
Screen line 1
Screen line 2
Counting Road-Users
Right-Turn Vehicles Southbound Cyclists
Burrard and Pacific Intersection
Counting Road-Users
Time Screenline1 Screenline2 Screenline3
Manual 1581 110 39
Automatic 1661 127 47
Accuracy 94% 84% 80%
Total
Count
6423 368 190
Screen line 2
Screen line 3
Screen line 1
Burrard and Pacific Intersection
14m
Automatic Speed Validation
Manual vs. Automatic speed measurements
Acceptable Accuracy
RMSE = 0.374 m/s
R2 = 0.8647
55
Automatic Speed Validation
Automatic Speed Validation
Results Summary
Average Speed Distribution throughout the Roundabout
Attribute Category Statistics
ANOVA/
t-stat (P-Value) Count Mean Speed
(SD)
Group Size 1 681 4.66(3.87)
0.011 2+ 53 3.96(3.5)
Lane Position
Left 42 4.06(2.89) 0.026 Middle 372 4.5(4.67)
Right 322 4.8(2.98)
Helmet Use With 681 4.73(3.79)
<0.0001 Without 53 3.06(2.29)
Travel Path Street 395 5.91(2.45)
<0.0001 Sidewalk 303 3.12(1.24)
Results Summary
As group size increases, cycling speed decrease
Cyclists using helmets tend to travel at higher speed
s1 s2 s3 s4
Manual 211 82 315 296
Automated 178 91 274 290
Accuracy 0.843 0.89 0.869 0.979
Counting Road-Users
Future Directions
CV Improvements (tracking, camera calibration)
Use of gait variability in identifying pedestrian
attributes (distracted walking, health)
Simulating pedestrian movements
Conflict-based safety performance functions
Summary
A new approach to road safety and data
collection analysis
Proactive, generic and low cost approach
Provides better understanding of driver behavior
especially collision avoidance mechanisms
BA safety evaluations can be undertaken in shorter
time periods