Public street lighting service standard assessment and achievement

https://doi.org/10.1016/j.seps.2015.12.001Get rights and content

Highlights

  • Addressed an important public service issue of nighttime lighting.

  • Examined neighborhood lighting to assess efficiency issues and achievement of established safety standards and guidelines.

  • Detailed location modeling based approach for assessment and planning.

  • Illustrated how safety and security needs could be satisfied, sensitive to long term costs.

Abstract

Nighttime lighting is an important public service that impacts human activities and promotes transportation and pedestrian safety. Of course, such services are not free and have been found to have negative impacts on the environment. Responsible stewardship of the built environment requires that efficiency and care in the delivery of services be taken, particularly in the context of sustainability concerns. A significant problem with existing urban infrastructure systems like street lighting is that they have evolved over time using rule-of-thumb planning standards. Given this, systematic assessment and re-evaluation offers much potential for enhancing the spatial efficiency of infrastructure but also the opportunity to explicitly account for environmental impacts in combination with safety and security. This paper applies a methodology for studying lighting in urban areas based upon the use of spatial analytics, including GIS and spatial optimization. Findings and results are reported for a study area in San Diego, California, highlighting current system configuration issues, method development and the potential long term benefits of systematic analysis of public sector services.

Introduction

Street lighting is an important component of the built environment, contributing to the charm and character of neighborhoods and business districts alike but also serving to make areas safer in various ways. Lighting can reduce crime and violence as well as decrease the likelihood of pedestrian, bike and/or vehicle accidents. Yet, there are quantifiable costs to providing public lighting, consuming significant tax dollars to maintain and operate not to mention the environmental impacts attributable to electricity generation/usage, product manufacturing, etc. Of course there are many non-quantifiable impacts as well, such as physiological disruptions, general altering and reshaping of ecosystems, and contributing to light pollution. Because of the contrast of benefits and impacts, street lighting is a curious public service. Traditionally little systematic planning of spatial efficiency has gone into street lighting, especially once lights have been installed. Increasingly, however, communities across the globe are re-thinking street lighting in various ways. Some communities have turned them off to save money. Others have begun to explore more energy efficient alternatives. What has not yet happened is system-wide re-assessment of street lighting that takes into account competing objectives and concerns.

The benefits of nighttime lighting are very compelling, no doubt justifying their widespread adoption. Street lighting reduces/eliminates opportunities for criminal behavior that can be attributable to urban layout and structure, but also the fear of crime [22]. The reason for this is that light increases surveillance potential, improving visibility and making perpetrator detection more likely. Beyond this, lighting can reduce the chance of pedestrian, bike and vehicle (or some combination thereof) accidents [23], [31]. Finally, lighting enhances community pride, neighborhood cohesiveness, and informal social control [18].

The impacts of artificial nighttime lighting are also undeniable, consuming nearly 20% of total global electricity and accounting for greenhouse gas emissions of some 1900 Mt of CO2 per year [43]. Of course, electricity consumption translates into real operational costs for public street lighting. Continuing economic challenges are proving to be motivators for cities and communities (Detroit, Colorado Springs, Santa Rosa, Rockford and others in the U.S. and Surrey, Essex, Northamptonshire and others in the UK) to dim, turn off or remove street lighting in order to save thousands to millions of dollars per year [4], [5], [14], [21]. Beyond direct operational costs, lighting has been found to have serious physiological impacts on humans as well as animal and plant populations [19], [25], [44]. For humans, this includes disrupting sleep patterns, increased risk of cancer and degraded air quality. For animals, the impacts of artificial light have been linked to adverse changes in feeding, reproduction and migration patterns [29], [45].

Nighttime lighting of streets is an interesting planning problem given the compelling need for light yet there are competing considerations having to do with costs and impacts. To support a balanced assessment as well as contribute to informed planning and management, this paper details a framework for assessing/planning public street lighting based on location modeling. The next section offers a literature review, including street lighting standards relied upon in planning as well as spatial optimization modeling research. This is followed by details regarding the applied analytical framework, including the specification of the location model. Case study results are then presented. The paper ends with discussion and concluding comments.

Section snippets

Background

The provision of public street lighting is essentially regulated through local planning standards and guidelines derived from state/federal agencies. A prominent resource for establishing standards and guidelines is the U.S. Department of Transportation, Federal Highway Administration, and in particular the FHWA Lighting Handbook [31]. This handbook details appropriate street light layouts, such as one-sided, opposite, staggered, median, etc., depending on the type of road but also based on

Methods

The needs of an area/neighborhood dictate good placement of public street lights. In particular, lighting requirements are location dependent, taking into account streets, sidewalks, travel patterns, behavioral characteristics, safety, security, etc. Given this, a range of detailed spatial information is necessary to support analysis and planning, hopefully translating to a good understanding of needs. Further, processing geographically based data is essential for deriving properties and

Street lighting

Issues associated with public street lighting were investigated using an existing system serving a neighborhood, primarily focusing on service efficiency relative to established standards and guidelines. The analysis was carried out on an Intel i7 (2.70 GHz) computer running Windows 7 64 bit with 16 GB of RAM. ArcGIS 10.2.2 was utilized for data creation, management, manipulation, analysis and display. A Python library, Shapely, was relied upon to structure the integer program, implementing a

Discussion and conclusions

Maintaining standards and guidelines associated with the provision of public street lighting is both important and necessary. Lighting enhances safety and security in neighborhoods, as well as contributes to its charm and character. Cities establish street lighting standards as a mechanism for addressing these concerns, but doing so in a manner that manages costs and impacts on the environment.

The primary benefits of lighting are human safety and security. Such benefits are embodied in

Acknowledgments

This research benefited from seed funding provided by the College of Liberal Arts and Sciences as well as the School of Geographical Sciences and Urban Planning at Arizona State University. The authors also thank Dr. Ran Wei (University of Utah) for assistance with model solution quality assurance.

Alan Murray (BS, MA, PhD UC Santa Barbara) is Professor in the Department of Geography at the University of California at Santa Barbara. He formerly held appointments at Drexel University, Arizona State University and Ohio State University. He is currently an editor of International Regional Science Review, associate editor for Socio-Economic Planning Sciences and Annals of the Association of American Geographers, and former editor of Geographical Analysis. His research and teaching interests

References (60)

  • A.T. Murray

    Strategic analysis of public transport coverage

    Socio Econ Plan Sci

    (2001)
  • A.T. Murray

    Optimising the spatial location of urban fire stations

    Fire Saf J

    (2013)
  • A.T. Murray et al.

    A computational approach for eliminating error in the solution of the location set covering problem

    Eur J Oper Res

    (2013)
  • D.A. Schilling et al.

    Some models for fire protection locational decisions

    Eur J Oper Res

    (1980)
  • A. Suzuki et al.

    On the p-center location problem in an area

    Locat Sci

    (1996)
  • D. Tong et al.

    Maximizing coverage of spatial demand for service

    Pap Reg Sci

    (2009)
  • Q. Wang et al.

    Budget constrained location problem with opening and closing of facilities

    Comput Oper Res

    (2003)
  • C.D.T. Watson-Gandy

    Heuristic procedures for the m-partial cover problem on a plane

    Eur J Oper Res

    (1982)
  • P. Yin et al.

    Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles

    Appl Geogr

    (2012)
  • D. Cauchon

    Cities turn off streetlights to save money

    U. S. A Today

    (2009)
  • C. Christoff

    “Half of Detroit's streetlights may go out as city shrinks

    Bloomberg

    (2012)
  • R.L. Church

    The planar maximal covering location problem

    J Reg Sci

    (1984)
  • R.L. Church et al.

    Location modeling utilizing maximum service distance criteria

    Geogr Anal

    (1979)
  • R.L. Church et al.

    Business site section, location analysis and GIS

    (2009)
  • City of Phoenix

    City of Phoenix streetlighting layout guidelines

    (2013)
  • City of San Diego

    Street lighting

    (2015)
  • R.G. Cromley et al.

    Evaluating representation and scale error in the maximal covering location problem using GIS and intelligent areal interpolation

    Int J Geogr Inf Sci

    (2012)
  • J. Current et al.

    Locating emergency warning sirens

    Decis Sci

    (1992)
  • M. Davey

    Darker nights as some cities turn off the lights

    N. Y Times

    (2011)
  • D. DiLaura et al.

    Lighting handbook

    (2009)
  • Cited by (32)

    • Study and optimization of lens shape affecting light patterns of light-emitting surface based LED street lighting

      2022, Optik
      Citation Excerpt :

      Thus, optical design of the street lighting becomes very important apart from the mechanical design. The types of LEDs, circuit route, and secondary optic/lens are amongst the few parameters to be taken into consideration in the process of optimising street lighting performance, which can be accessed via average road surface brightness, brightness uniformity, longitudinal brightness uniformity, and threshold increment, commonly known as the glare factor [3–5,22]. With the advancement in science and technology, a light emitting surface (LES) configuration has been developed to replace the traditional LED design with encapsulation.

    • Intelligent control and energy saving evaluation of highway tunnel lighting: Based on three-dimensional simulation and long short-term memory optimization algorithm

      2021, Tunnelling and Underground Space Technology
      Citation Excerpt :

      The energy consumed by lighting accounts for a small proportion of the world's electricity consumption, but the possibility and necessity of energy savings are great (Lobao et al., 2015; Mokey Coureaux and Manzano, 2013). Researchers all over the world are very concerned about the energy saving of lighting systems (Murray and Feng, 2016), and they estimate the load demand and energy cost of the lighting system through luminance fitting curve (Yang et al., 2011) and photo radiometer verification (Cantisani et al., 2018), etc. Besides, the simulation experiments of tunnel lighting control based on software are quite promising (Fan et al., 2011).

    • Contemporary optimization application through geographic information systems

      2021, Omega (United Kingdom)
      Citation Excerpt :

      Suitable service is structured and imposed in constraints (11). As with previously discussed optimization models, the LSCP has been applied in a range of contexts to support management planning (see [5,31,34,61,64]). This is known as the maximal covering location problem (MCLP), originally formulated in [13].

    • IoT for energy efficient green highway lighting systems: Challenges and issues

      2020, Journal of Network and Computer Applications
      Citation Excerpt :

      Call for protocol: The exterior lighting standards tend to differ from zone to zone. An open protocol for control and automation of various type of road lighting would create more possibilities towards reliable and cost effective lighting (Das et al., 2015; Murray and Feng, 2016). Study of lamp power consumption: As the rated and measured power consumption of light varies hugely for one brand to another therefore how this phenomena can affect the cost analysis should be studied.

    View all citing articles on Scopus

    Alan Murray (BS, MA, PhD UC Santa Barbara) is Professor in the Department of Geography at the University of California at Santa Barbara. He formerly held appointments at Drexel University, Arizona State University and Ohio State University. He is currently an editor of International Regional Science Review, associate editor for Socio-Economic Planning Sciences and Annals of the Association of American Geographers, and former editor of Geographical Analysis. His research and teaching interests include: geographic information science; health informatics; land use planning; urban, regional, and natural resource planning and development; quantitative methods; infrastructure and transportation systems; spatial optimization; location modeling; databases and data structures; spatial representation; and techniques to support interactive planning and decision making. He is the author of two books and over 200 research articles, book chapters and proceedings papers.

    Xin Feng is a Ph.D. student in the College of Computing and Informatics at Drexel University. She completed her B.S. and M.S. in Geographical Information System at Wuhan University and Peking University, respectively. Her current research interests include geographic information science; urban, regional, and natural resource planning and development; spatial optimization; and remote sensing.

    View full text