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