In the current economic climate many local authorities are facing reduced budgets and difficult decisions about where savings might be made reducing levels of public services. Street light provision is one such service. But to take decisions on reducing provision of night-time street lighting whilst maintaining public safety requires reliable evidence to be available to local authorities on any impacts on road safety it may have, as well as on other concerns such as crime and fear of crime. The LANTERNS project is a research collaboration between Institution of Lighting Professionals and The University of London, and aims to answer reliably whether reducing night-time street lighting levels for environmental and energy reasons has any impact on road traffic injuries and crime. For this it will use the specific locations of street lighting columns (i.e., the X-Y co-ordinates), the nature of any changes to lighting (e.g. part-night lighting; dimming) and the dates the changes were implemented. It will then compare any increase or decrease in casualties (and crimes) on the roads when lighting is reduced, with any increase or decrease in casualties (and crimes) on similar roads where street lighting remains unchanged. By April 2014 there were 69 local authorities participating in the LANTERNS project; each had provided or agreed to provide their street lighting data. Preliminary results will be presented at the ILP Professional Lighting Summit in September 2014. Talk by Rebecca Steinback, London School of Hygiene & Tropical Medicine

1. Early results of the LANTERNS
project
The LANTERNS project is funded by the NIHR Public Health Research
Programme. The views expressed here are those of the authors and
do not necessarily reflect those of NIHR or the Department of
Health

2. What are the public health
impacts of reduced street
lighting at night?

3. LANTERNS Project Aims
• To collate information on street lighting
adaptation schemes nationally
• Statistically examine whether reduced lighting
has any effects on traffic crashes or crime
• Explore local public opinion on street lighting
provision, and potential for reducing levels
• Investigate whether street lighting adaptation
schemes offer value for money

4. LANTERNS Project Aims
• To collate information on street lighting
adaptation schemes nationally
• Statistically examine whether reduced lighting
has any effects on traffic crashes or crime
• Explore local public opinion on street lighting
provision, and potential for reducing levels
• Investigate whether street lighting adaptation
schemes offer value for money

5. Does:
Switch off
Part night
Dimming
Trimming
White light
..or combinations
of these?
Cause any changes in:
ROAD CASUALTIES
- Car occupant
- Pedestrian
- Motorcyclist
- Cyclists
CRIME
- Burglary
- Criminal Damage & Arson
- Vehicle Crime
- Violence & Sexual Offences
- Robbery

6. All local authorities in
England and Wales have been
invited to participate…

7. All local authorities in
England and Wales have been
invited to participate…
67 local
authorities have
contributed data

8. All local authorities in
England and Wales have been
invited to participate…
67 local
authorities have
contributed data
Street lighting data
from 60 local
authorities will be
used in the analysis

9. Part Night
Lighting
27/60
45%

10. Trimming
29/60
48%

11. Dimming/variable
lighting
37/60
62%

12. White light
46/60
77%

13. Switch off
3/60
5%

18. 0
2000
4000
6000
8000
10000
12000
14000
16000
18000
Jan-00
Jun-00
Nov-00
Apr-01
Sep-01
Feb-02
Jul-02
Dec-02
May-03
Oct-03
Mar-04
Aug-04
Jan-05
Jun-05
Nov-05
Apr-06
Sep-06
Feb-07
Jul-07
Dec-07
May-08
Oct-08
Mar-09
Aug-09
Jan-10
Jun-10
Nov-10
Apr-11
Sep-11
Feb-12
Jul-12
Dec-12
May-13
Oct-13
Kilometres of road with lighting
interventions
Part-night lighting Dimming Trimming White Light Switch off

19. Road traffic injury data
Stats19
– Easting and Northing of collision
– Time of day of collision

22. 18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Non-day casualties
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
A roads B roads Minor roads

23. 40000
35000
30000
25000
20000
15000
10000
5000
0
Day time casualties
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
A roads B roads Minor roads

24. 0
2000
4000
6000
8000
10000
12000
14000
16000
18000
Jan-00
Jun-00
Nov-00
Apr-01
Sep-01
Feb-02
Jul-02
Dec-02
May-03
Oct-03
Mar-04
Aug-04
Jan-05
Jun-05
Nov-05
Apr-06
Sep-06
Feb-07
Jul-07
Dec-07
May-08
Oct-08
Mar-09
Aug-09
Jan-10
Jun-10
Nov-10
Apr-11
Sep-11
Feb-12
Jul-12
Dec-12
May-13
Oct-13
Kilometres of road with lighting
interventions
Part-night lighting Dimming Trimming White Light Switch off

25. 0.04
0.03
0.02
0.01
0
Non-day time casualties per km
2009 2010 2011 2012 2013
Part-night lighting Dimming Trimming
White Light Switch off Non-intervention

26. 0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
Day time casualties per km
2009 2010 2011 2012 2013
Part-night lighting Dimming Trimming
White Light Switch off Non-intervention

27. Controlled interrupted time series model
slope pre-
Injury
and
crime
count
Lighting ‘interventions’ included:
Switch off Trimming
Part-night lighting Dimming
White light LEDs
Time
change
associated with the
intervention
slope post-step

28. 푌푠,푡~ 푃표푖푠푠표푛 휇푠,푡
log 휇푠,푡 = 훼푠 + 푆 푡, 푧푠 + 훃. 퐱푠,푡
number of casualties & crimes in
road segment ‘s’ in year ‘t’
푦푠,푡 =
훼푠 = road segment effect
푧푠 = road segment characteristics
푆 푡, 푧푠 = function of year to allow for
nationwide trends, dependent on
road segment characteristics
퐱푠,푡 = vector of indicator (0,1) variables
identifying road segments affected
훃 = vector of coefficients of effect of lighting
change on casualties and crimes

29. Crime data
Police.uk (national coverage)
– Monthly counts of ASB, criminal damage, burglary, vehicle
crime, robbery
West Midlands Police Force recorded crime data
– Type of crime
– Date and time (from and to)
– Location

30. Police.uk data
National coverage (2011-)
• Month of crime (not day
or time of the day)
• Type of crime*
• Location*

31. Which Crimes?
British Crime Survey
90
80
70
60
50
40
30
20
10
0
2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/092 2009/103
% crimes during evening/night
BCS year
All Violence Theft from Person Vehicle related theft All burglary

32. Which crimes?
Police recorded crime - Aoristic
Profiles
• For many crimes the time of the offence is unknown
Midnight
Noon
6pm
6am
Midnight
crime

33. Which crimes?
Police recorded crime - Aoristic Profiles
0.08
0.06
0.04
0.02
0.00
5 10 15 20
Hour of the day
Probability crime occurs in hour t
Aoristic graph for Criminal Damage, n = 44,966

34. Police recorded crime - Aoristic Profiles
0.100
0.075
0.050
0.025
0.000
5 10 15 20
Hour of the day
Probability crime occurs in hour t
Aoristic graph for Robbery, n = 19,397
Which crimes?
0.05
0.04
0.03
0.02
0.01
0.06
0.05
0.04
0.03
0.02
0.01
0.00
5 10 15 20
Hour of the day
Probability crime occurs in hour t
Aoristic graph for Vehicle Crime, n = 69,860
0.00
5 10 15 20
Hour of the day
Probability crime occurs in hour t
Aoristic graph for Burglary, n = 79,108

35. Police.uk - Geomasking
• “Each dot marks the approximate location of an incident of
crime or anti-social behaviour and it will usually appear on a
street with 8 or more postal addresses. We have purposely
used radar-style icons to demonstrate this and also clearly
state at each dot that the incident is ‘on or near.’”
(http://www.police.uk/help?)

38. Testing the Spatial Accuracy
of police.uk data
Tompson, L., Johnson, S.D., Ashby, M., Perkins, C., and Edwards, P. (2014). UK open
source crime data: Accuracy and possibilities for research.

39. MSOA level
MSOA
0.0 0.2 0.4 0.6 0.8 1.0
Index of Similarity (S)
Burglary Total
Burglary 2011
Burglary 2012
Burglary 2013
Vehicle Total
Vehicle 2011
Vehicle 2012
Vehicle 2013
ASB Total
ASB 2011
ASB 2012
ASB 2013
Crim Dam Total
Crim Dam 2011
Crim Dam 2012
Crim Dam 2013
Robbery Total
Robbery 2011
Robbery 2012
Robbery 2013
Police
Total
Open
Total
79104
29038
25883
24183
69860
25371
22222
22267
262793
106969
80363
75461
47492
7879
20083
19530
19396
8213
5775
5408
78392
28743
25658
23991
72746
26516
23120
23110
274336
118852
80287
75197
60255
9857
25569
24829
19192
8108
5707
5377
Tompson, L., Johnson, S.D., Ashby, M., Perkins, C., and Edwards, P. (2014). UK open
source crime data: Accuracy and possibilities for research.

40. Postcode level
PC
0.0 0.2 0.4 0.6 0.8 1.0
Index of Similarity (S)
Burglary Total
Burglary 2011
Burglary 2012
Burglary 2013
Vehicle Total
Vehicle 2011
Vehicle 2012
Vehicle 2013
ASB Total
ASB 2011
ASB 2012
ASB 2013
Crim Dam Total
Crim Dam 2011
Crim Dam 2012
Crim Dam 2013
Robbery Total
Robbery 2011
Robbery 2012
Robbery 2013
Police
Total
Open
Total
79113
29043
25885
24185
69861
25372
22222
22267
262803
106972
80367
75464
47454
7879
20084
19491
19398
8213
5776
5409
78395
28745
25660
23990
72638
26464
23063
23111
274341
118853
80290
75198
60184
9849
25504
24831
19188
8108
5703
5377
Tompson, L., Johnson, S.D., Ashby, M., Perkins, C., and Edwards, P. (2014). UK open
source crime data: Accuracy and possibilities for research.

41. Outcome Analysis
• Better thought of as reflecting crime on and/or near a street
• Area level analysis
• Spatial accuracy improved substantially by modeling the error
in the data
• Case study analyses with police recorded crime data

42. LANTERNS Project Aims
• To collate information on street lighting
adaptation schemes nationally
• Statistically examine whether reduced lighting
has any effects on traffic crashes or crime
• Explore local public opinion on street lighting
provision, and potential for reducing levels
• Investigate whether street lighting adaptation
schemes offer value for money

43. Rapid appraisal
Sample of 8 contrasting Local Authorities
• Survey of web and public sources
• LA consultations
• Local media
• Key informant interviews
• Ethnographic interviews and observations
• Focus groups and in depth interviews
• Household survey in one LA comparing affected and
unaffected streets (N=1000)

44. Expressed public views
I pay my tax, I now have to walk home in the pitch black […] I
expect a basic service
I am over the moon […] to look up at the night sky and be able to
see the stars on a clear night
Am I alone in thinking it’s a fantastic idea? … the money saved …
can be ploughed back into schools and lollipop ladies….
Sleeping in the pitch black will have amazing health benefits
for the people of this town. Not to mention the impact on the
environment

45. Interaction and deliberation
• You wouldn’t want them to just totally switch things off...
• I don’t know, because it’s, on estates, because I know what
Lucy was saying, since she got burgled, because it’s so well lit
where she is. She says, the, the policeman said if, if it hadn’t
had been as well lit and they hadn’t been able to see your
house, your garage ...
• [...]
• I suppose you’re never going to please any, everybody are you?
• No.
• [laughter]
• You’re never going to please everybody.

46. Private views: wonder, and
fear
I know this sounds weird, but I got quite obsessed by it when they
first started turning them off at midnight, I started to stay up
to watch them going out – just to see how dark it was. It was
so strange watching the lights going out – an odd thing to
happen.
(Herts resident, informal conversation)
I don’t like to walk in the dark. I could carry a torch – but that
shows you up, If there’s a street light, people can say ‘I saw a
lady walk past us...’ If I’m carrying a torch, all they can see is
the torch. (Herts resident, informal conversation)

47. Private views: ‘Going
backwards’
you know, you take it for granted but the whole streetlight thing
seemed to me to be a big step forwards in the quality of life 150
years ago now probably or whatever. But the thought of actually
going backwards seems to me to be quite appalling, you know, so
I’d, I’d feel quite strongly about it in that sense. (Bucks resident,
interview)

48. Lighting ‘in the right place’:
the modern city
I used to live out in [small village], it’s very rural there, it’s
completely different. When I was there I didn’t go out as much at
night, I didn’t feel as secure. Here I go out to the theatre, cinema, I
feel safe. (Wakefield, interview)
The city people want street lights - there is a new build estate, and its
second generation people coming from London, with different
expectations – they want them. It is a divide – people do talk about
it as something people come to the country and then expect it to be
like the city (Herts, informal interview)

49. The silent majority: lights,
what lights?
• I don’t notice to be honest (informal interview, Shrewsbury)
• I don’t notice really as I don’t go out after dark (informal interview,
Swansea)
• To be honest, I haven’t got an opinion, you just get used to it.
(Informal interview, Swansea)
• I’m not going to lie, when you first, um, suggested it to me I was like,
eh, street lights, that’s a random topic. (Hackney, in depth interview)

50. Survey of residents

51. Part Night Unaffected OR p
3
Thinking about the spring and autumn periods, how often do you usually walk alone in
your neighbourhood after dark?
At least once a week 73 79 0.804 0.266
Other 177 154
4
Thinking about the spring and autumn periods, how safe do you feel walking alone in
your neighbourhood after dark?
Very safe 39 61 0.521 0.004
Other 211 172
5
Thinking about the spring and autumn periods, how safe do you feel driving home after
dark?
Very safe 115 117 0.845 0.354
Other 135 116
6
How worried are you about having your car stolen or broken into after dark in your
neighbourhood?
Very worried 7 7 0.93 0.894
Other 243 226

52. Next Steps
• Data collection is finished!
• Finalize quantitative models
• Use results from quantitative and
qualitative aims to inform cost-benefit
analysis
• Final Results due January 2015