GIS Workshop | Urban Design and the Rates of Accidents on Roads

Page 1

DOES URBAN DESIGN EVEN MATTER? Joshua Brooks, Jialu Tan, Gonzalo Ortega GIS Workshop | DUSP MIT 2017


Boston is the ‘walking capital’ of the U.S. Are certain streets safer than others for people + bikes? What are the urban design patterns?


How do we reach Vision Zero?


By determining which neighborhoods have higher rates of accidents per person we can equitablly prioritize capitol improvement dollars across the city and determine the types of interventions that will yield positive results.


This process can be replicated in others cities.



Smaller. Smaller. Smaller.

Bigger. Bigger. Bigger.


WORK-FLOW

Processing Spatial Data in Arc Map

Parcels / Buildings / Open Space Base Maps READING

DFORD

WAKEFIELD

BURLINGTON

Street Center Lines Intersections Sidewalk Width Street Width Row Width Ratios Between Elements READING

PEABODY

BEDFORD

SALEM

STONEHAM

MELROSE

MALDEN

SOMERVILLE

BOSTON

NEWTON

BROOKLINE

ELLESLEY

WELLESLEY

BOSTON

NEEDHAM

NEEDHAM

G

GG G

BOSTON

G G GG G G G GG G G G G GG G GG G G GGG GGG G G GG G GG GG G GG GG G G G G GG GG G GG G G G G G GGGG G GG GG GG G G GG G G G G G GG GG G GGG G G GGG G G G GG G G GG G GGGG G G G GGG G G G G GGG G GG G GGG G G G GG G G GG G GG G G GG G G G G G G G G G G GG G G G G G GGG GG G G G G G G G GGG G G G GG G G GG GG GG G G GG GGG GG G GG G GG G GG G G G GG G G G G G G G G G G G GG G G G GG G G G G G G G G G G BROOKLINE G G G GG GG G G G G G G G G G G G G G G G G G G G G G GG GG G G G GG GG G G GGG G G G GGG G G G G G G G G G G G G G BOSTON G G G GGG G HULL GG G G G G GG G GG G G G G G G G G G G G G GG G HULL G G G GG G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G GG G

WINTHROP

WINTHROP

CAMBRIDGE BOSTON

WINTHROP

WATERTOWN

G

WINTHROP

MILTON

G

HINGHAM

G

CAMBRIDGE

Bike Counts Interpolated Bike Density

WESTWOOD WEYMOUTH BRAINTREE

G GG GG GG G GG G GG G GGG GGGG GGGGG G GGG G G G G G G GG GGG G GGG GGG GGG GG G G G G G GGG G G G G GG G G GG G G G GG G G G G G G G G G G GG GG G G G G G G G GG G GG G GG G GG G GG GG G G GG G G GGGG G G GG GG G GGG GGGG GGGG G GGGGG GG G GGG GG G G G G G G G G G G G G G G G G GGG G G G GG GG G G G G G GGG G G G G G GG GGG GG G GG G G G G GG G GG G G GG G GG GGGGGGGG G G GGGG G GGG G GGGG GGGG GGG G G GG G G G G G G G G G G G GG G G GGGG G GGG GGG GG G G G GG GG G GG G GG GG GG G G G GGGGG G G GGG G G G GG G G GG G GG G GG GG GG G G GG G G G G G G GG GGG GG GG G G G G G G G GG G GG GGG G G GG G G G BROOKLINE G G GG GGG GG G GG G G G G GG G G G G G GG G G G G G G G GG G G G GG G G G G G G G GGGG G G GGG G G GG G G GG G G G G G G G GG GG G GGG G G G G G G G G G GG G GG GG G G GG G G G G G GG G G GG G BOSTON G G G GG GG G GG GG HULL GG G G GG G GG G GG G GG G G GG GG GG GG G G G G G G G G GG G G G G G G G G G G G GG G G G G G GG G G HULL G GGG G G G G G G G GG G G G G GG G G G GG G GG G G GG G GGG G G G G G GGG G G GG G G G G GG G G G G G G G G G G GG G G G GG G GG G G G G G G G G G G G G G GG G G G G GGG G GG G G G G G G G G G G G G GGG G GG

NEWTON

NEWTON

BROOKLINE

WELLESLEY

WELLESLEY

HULL

BOSTON

HULL NEEDHAM

NEEDHAM

QUINCY DOVER

QUINCY DOVER

DEDHAM

MILTON

HINGHAM

[

CANTON

NORWOOD

RANDOLPH WALPOLE

Bike Accidents Rate of Accidents

WESTWOOD

NORWOOD 0.4 0.8 1.6

2.4

Miles 3.2

G

QUINCY HINGHAM GG

Pedestrian Density Interpolated Pedestrian Density

[

RANDOLPH WALPOLE

WESTWOOD

CANTON

NORWOOD 0.4 0.8 1.6

2.4

Miles 3.2

RANDOLPH WALPOLE

G

MILTON

HINGHAM

Pedestrian Accidents Rate of Accidents

WEYMOUTH

BRAINTREE

0

HULL

HULL

DEDHAM

MILTON

WEYMOUTH BRAINTREE

CANTON

0

G G GG GG G G G G GG G G WINTHROP G G G G G G BOSTON G WINTHROP G G GG G G G

Datasets Sources: City of Boston GIS, Vision Zero (Boston EMS), Anthony Vanke

G

G

WESTWOOD

G G G G G GG G

WATERTOWN

GG

DEDHAM

G

GG G G

G G QUINCY DOVER

DEDHAM

CHELSEA SOMERVILLE

WALTHAM

G

G

CAMBRIDGE

G

OVER

ALPOLE

G G

WATERTOWN

REVERE

BELMONT

SOMERVILLE

WALTHAM

GG G G GG

WINTHROP

NAHANT

MEDFORD

EVERETT

CHELSEA

BELMONT

G

SOMERVILLE

WINTHROP

CAMBRIDGE

MALDEN NAHANT ARLINGTON

REVERE

EVERETT

CHELSEA

BELMONT WALTHAM

WATERTOWN

NEWTON

MALDEN MEDFORD

ARLINGTON

REVERE

EVERETT

CHELSEA

BELMONT WALTHAM

MELROSE WINCHESTER

NAHANT

MEDFORD

EVERETT

Density of Street Trees

LEXINGTON

MALDEN NAHANT

STONEHAM

WINCHESTER

ARLINGTON

REVERE

Street Light Coverage

SWAMPSCOTT

LYNN SAUGUS

LEXINGTON

MEDFORD ARLINGTON

WAKEFIELD

MELROSE

WINCHESTER

Trees

SALEM

SWAMPSCOTT WOBURN

SAUGUS

LEXINGTON

Street Lights

PEABODY

Regulated intersections Y/N

BURLINGTON

STONEHAM

MELROSE

WINCHESTER

READING

SALEM

LYNN

SAUGUS

LEXINGTON

Traffic Lights

PEABODY

BEDFORD

SWAMPSCOTT WOBURN

LYNN

STONEHAM

SAUGUS

READING

WAKEFIELD

BURLINGTON

SWAMPSCOTT WOBURN

LYNN

Existing Bike Network Bike Network Categories SALEM

WAKEFIELD

BURLINGTON

WOBURN

PEABODY

BEDFORD

[

CANTON

0

NORWOOD 0.4 0.8 1.6

2.4

Miles 3.2

RANDOLPH

WEYMOUTH BRAINTREE

[

0

0.4 0.8

1.6

2.4

Miles 3.2


WORK-FLOW

Processing Spatial Data in Arc Map


WORK-FLOW

Processing Spatial Data in Arc Map Set Boundary Public Realm. Remove Private Land.

Spatial Data Street Center Lines Bike Network Traffic Lights Street Lights Trees

G

*

G G

Accidents Pedestrian Bike

G

BO

G

ST ON BO

G

ST

ON

* G

[ 0 0.0

G

050.0

[

1 0.0

2 0.0

BO

BO

m_

PE

D_

0.0

AC

00

0.0 01

00

77

10

1-

00

09

0.0 25

01

77

0.0 66

09

68

26

0-

- 4.0

0.0

66

67

00

2 0.0

3

0.0 Miles 4

User Density Pedestrian (Grid) Bike Counts (IDW Interpolation)

7.0 96

Cyclist /Points [

ST ON

1.4

7.5

98

.81

19

33

00

80

82

69

29

99

13

65

99

93

- 96

- 15

- 23

- 30

8.7

1.4

70

7.5

98

41

.81

19

33

80

82

99

98

30

12

41

68

54

63

67 81

/IDW interpolation

3.1

0.4

72

7.6

73

30

4.7

25

26

23

8.7

21

67

67

70

55

15

41

77

64

6.2

3.1

86

- 41

- 54

- 67

- 81

- 98

0.4

72

37

7.6

73

30

4.7

25

26

21

67

050.0

1 0.0

0.0 Miles 4

76 98 1,1 1,4 1,6 1,9

0 0.0

2

55

14

66

22

7

[

1

ST ON

<V AL UE >

15

3

0.0

0

9

23

0.0

1

BO

0-

0.0

0.0

0.0

050.0

/ Co un t

0.0

050.0

0 0.0

0.0 Miles 4

ST ON

Su

0 0.0

3

2 0.0

3

07

49

.67

04

.04

71

85

.58

39

25

6.2

.93

08

46

86

84

12

37

71

78

59

07

.20

- 1,1

- 1,4

- 1,6

- 1,9

- 2,1

49

.67

89

04

.04

71

85

.93

.58

39

08

84

77

11

2,1

45

2,4

24

2,7

84

3,2

0.0 Miles 4

3,7 4,6

70

29

.12

26

.85

15

81

.34

05

83

29

.04

22

87

59

.53

90

86

.20

90

73

89

64

36

70

.99

85

29

.12

95

- 2,4

- 2,7

- 3,2

- 3,7

- 4,6

- 5,8

26

.85

15

12

81

.34

05

82

29

.04

22

.53

90

90

Spatial Standard 50m X 50m Grid

63

72

85

86

[ 0 0.0

050.0

1 0.0

2 0.0

3

0.0 Miles 4

City Wide Analysis Average Sidewalk Width Average Street Width Average ROW Width Average Block Size Street Tree Density Street Lights Density Traffic Light Density Bike Lane Type

RATE OF PEDESTRIAN ACCIDENTS Compared to ROW Width 0.050%

Rate of Accidents

0.040% 0.030%

Relational Analysis Accident Rates Spatial Relationship

0.020% 0.010% 0.000% 30.0

50.0

70.0

90.0 ROW Width

110.0

130.0

150.0


SO, WHAT DID WE LEARN?


ACTIVE TRANSPORTATION

Accidents

Pedestrian Accidents in Boston

=

Pedestrian Density

:

Area with Higher Rate of Pedestrian Accidents 0

Accident Rates

1

2 Miles

Std. Dev. Accident Rates


ACTIVE TRANSPORTATION

Pedestrian Accidents in Boston

Accident Rates

Std. Dev. Accident Rates

0

1

2 Miles


ACTIVE TRANSPORTATION

Accidents

Bike Accidents in Boston

=

Cyclist Density

:

Area with Higher Rate of Bike Accidents

Accident Rates

Std. Dev. Accident Rates 0

1

2 Miles


CHANGING PATTERNS

Average Street Width RATE OF PEDESTRIAN ACCIDENTS Compared to Average Street Width 0.050%

Rate of Accidents

0.040% 0.030% 0.020% 0.010% 0.000%

18.0

23.0

28.0

33.0

38.0

43.0

48.0

Average Street Width Per Cell

RATE OF BIKE ACCIDENTS Compared to Avergae Street Width 0.300% 0.250%

Rate of Accidents

0.200% 0.150% 0.100% 0.050% 0.000%

18.0

28.0

38.0

48.0

58.0

68.0

Average Street Width

0

1

2 Miles

Average Street Width


CHANGING PATTERNS

Average Right-of-Way Width RATE OF PEDESTRIAN ACCIDENTS Compared to ROW Width 0.050%

Rate of Accidents

0.040% 0.030% 0.020% 0.010% 0.000%

30.0

50.0

70.0

90.0

110.0

130.0

150.0

ROW Width

RATE OF BIKE ACCIDENTS Compared to Average ROW Width 0.300%

Rate of Accidents

0.250% 0.200% 0.150% 0.100% 0.050% 0.000%

30.0

50.0

70.0

90.0

110.0

130.0

150.0

Average ROW Width

0

1

2 Miles

Average ROW Width


CHANGING PATTERNS

Street Width to ROW Width Ratio ‘Public Realm’

RATE OF PEDESTRIAN ACCIDENTS Street Width to ROW Ratio

ROW Width Sidewalk

0.050%

Road Width

Sidewalk

0.030%

0.020%

0.010%

0.000% 10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

80.00%

70.00%

Street Width to ROW Ratio

RATE OF PEDESTRIAN ACCIDENTS Sidewalk to Street Width Ratio

RATE OF PEDESTRIAN ACCIDENTS Sidewalk With ROW Ratio 0.050%

0.050%

0.040%

0.040%

0.030%

0.030%

Rate of Axis

Rate of Accidents

Rate of Accidents

0.040%

0.020%

0.010%

0.010% 0.000% 10.00%

0.020%

20.00%

30.00%

40.00%

Sidewalk Width to ROW Ratio

50.00%

60.00%

0.000% 10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Sidewalk to Street Width Ratio

70.00%

80.00%

90.00%


CHANGING PATTERNS

Sidewalk Width RATE OF PEDESTRIAN ACCIDENTS Compared to Sidewalk Width 0.050%

Rate of Accidents

0.040%

0.030%

0.020%

0.010%

0.000%

5.0

10.0

15.0

20.0

25.0

30.0

Sidewalk Width

RATE OF BIKE ACCIDENTS Compared to Average Side Walk Width

RATE OF BIKE ACCIDENTS Compared to Average Side Walk Width

0.300%

0.300% 0.250%

0.200%

Rate of Accidents

Rate of Accidents

0.250%

0.150% 0.100% 0.050% 0.000%

0.200% 0.150% 0.100% 0.050%

5.0

10.0

15.0

20.0

Average Sidewalk Width

25.0

30.0

0.000%

5.0

10.0

15.0

20.0

25.0

Average Sidewalk Width

0

1

2 Miles

Average Sidewalk Width

30.0


CHANGING PATTERNS

Street Tree Coverage RATE OF PEDESTRIAN ACCIDENTS Compare to Number of Street Trees

RATE OF BIKE ACCIDENTS Compared to Number of Street Trees

0.050%

0.800% 0.700% 0.600%

Rate of Accidents

Rate of Accidents

0.040%

0.030%

0.020%

0.500% 0.400% 0.300% 0.200%

0.010%

0.100% 0.000%

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

0.000%

0.0

2.0

4.0

6.0

Number of Street Trees Per Cell

8.0

10.0

12.0

14.0

16.0

18.0

Number of Street Trees Per Cell

RATE OF BIKE ACCIDENTS Compared to Number of Street Trees 0.800% 0.700%

Rate of Accidents

0.600% 0.500% 0.400% 0.300% 0.200% 0.100% 0.000%

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

Number of Street Trees Per Cell

0

1

2 Miles

Total Street Tree Count

20.0


CHANGING PATTERNS

Street Light Coverage RATE OF PEDESTRIAN ACCIDENTS Compared to Street Light Density

RATE OF BIKE ACCIDENTS Compared to Street Light Density

0.050%

0.300% 0.250%

Rate of Accidents

Rate of Accidents

0.040%

0.030%

0.020%

0.200% 0.150% 0.100%

0.010%

0.050%

0.000%

0.000% 0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Number of Street Lights Per Cell

Number of Street LIghts Per Cell

RATE OF BIKE ACCIDENTS Compared to Street Light Density 0.300%

Rate of Accidents

0.250% 0.200% 0.150% 0.100% 0.050% 0.000%

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Number of Street Lights Per Cell

0

1

2 Miles

Total Street Light Count


CHANGING PATTERNS

Traffic Signal Coverage RATE OF BIKE ACCIDENTS Compared to Traffic Signal Density

0.050%

0.300%

0.040%

0.250%

Rate of Accidents

Rate of Accidents

RATE OF PEDESTRIAN ACCIDENTS Compared to Traffic Signal Density

0.030%

0.020%

0.010%

0.000%

0.200% 0.150% 0.100% 0.050%

0.0

1.0

2.0

3.0

4.0

0.000%

0.0

1.0

2.0

Number of Traffic Signals Per Cell

3.0

Number of Traffic Signals Per Cell

RATE OF BIKE ACCIDENTS Compared to Traffic Signal Density 0.300%

Rate of Accidents

0.250% 0.200% 0.150% 0.100% 0.050% 0.000%

0.0

1.0

2.0

3.0

4.0

Number of Traffic Signals Per Cell

Total Traffic Light Count 0

1

2 Miles

4.0


CHANGING PATTERNS

Intersection Density (Block Size) RATE OF BIKE ACCIDENTS Compared to Density of Intersections

0.050%

0.300%

0.040%

0.250%

Rate of Accidents

Rate of Accidents

RATE OF PEDESTRIAN ACCIDENTS compared to Density of Intersections

0.030%

0.020%

0.010%

0.000%

0.200% 0.150% 0.100% 0.050% 0.000%

0.0

5.0

10.0

15.0

20.0

25.0

0.0

5.0

10.0

15.0

20.0

Number of Intersections Per Cell

Number of Intersections Per Cell

RATE OF BIKE ACCIDENTS Compared to Density of Intersections 0.300%

Rate of Accidents

0.250% 0.200% 0.150% 0.100% 0.050% 0.000%

0.0

5.0

10.0

15.0

20.0

25.0

Number of Intersections Per Cell

0

1

2 Miles

Total Intersection Count

25.0


CHANGING PATTERNS

Bike Facility Type RATE OF BIKE ACCIDENTS Compared to Facility Type 0.300%

Rate of Accidents

0.250% 0.200% 0.150% 0.100% 0.050% 0.000%

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Bike Facility Type

Bike Lane Type

0

1

2 Miles


SO, WHAT DID WE LEARN?


There is a Strong Relationship between the Rates of Pedestrian Accidents and the Urban Design Patterns that we Studied. Bikes... Not So Much.


ACTIVE TRANSPORTATION

Accidents

Pedestrian Accidents in Boston

Pedestrian Density

:

=

Area with Higher Rate of Pedestrian Accidents

Accident Rates

0

1

2 Miles

Std. Dev. Accident Rates


So What Does this Look Like?


So What Does this Look Like? Mattapan | Average Street Width

South End | Average Street Width

Mattapan | Average Sidewalk Width

South End | Average Sidewalk Width


ACTIVE TRANSPORTATION

So What Does this Look Like?


TAKE AWAY

Urban Design Does Matter Narrower streets that have a smaller foot print for vehicular traffic are safer for pedestrians than wider street. The wider sidewalks and smaller block sizes significantly decrease the rates of accidents per person. Higher concentrations of street trees led to fewer pedestrian and bike accidents. Wider ROW widths do not make safer streets. Presence of street lights increase pedestrian safety.


Limitations 1) We only had access to a sampling of pedestrian and bike density and therefore had to interpolate across the city. 2) The built environment is massivley complex and we only analyzed eight overall patterns. 3) We did not run a regression model to develope correlations 4) No accounting for social or economic factors within this research 5) Limited field verification


Next Steps 1) Build a more robust spatial data set including 3-Dimensional qualities 2) Obtain more accurate bike count information 3) Run a statistical regression model 4) Accounting for difference in Socio-economic conditions throughout the various neighborhoods 5) Field verification of high rate cells


URBAN DESIGN DOES

MATTER

THANK YOU!


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