Home » 2013 Categories » 2013 - Durham papers » A SAFER ALTERNATIVE? CUL-DE-SACS AND CRIME IN DURHAM, NC





Urban planners and economists often debate the merits of cul-de-sacs, or circular, dead end streets that serve adjacent dwellings. Proponents claim that cul-de-sacs reduce urban congestion, improve community relations and reduce crime. However, economists occasionally challenge such claims, asserting that cul-de-sacs do not provide additional safety benefits or that such benefits are negligible. This research explores the relationship between crime and the existence of cul-de-sacs in the city of Durham, North Carolina. By utilizing Geographical Information Systems (GIS) and publically available crime data, I compare the spatial differences in crime rates between communities built on cul-de-sacs and two-way streets. Though crime in cul-de-sacs appears to be markedly lower than crime on nearby two-way streets, further economic analysis is necessary to separate the spatial effects of cul-de-sacs from other socioeconomic factors.



The cul-de-sac is a hallmark of suburban sprawl. The term itself comes from a French expression that means “the bottom of the bag” (Lonngren). It is a dead end street with only one entrance for vehicle traffic. Further, cul-de-sacs tend to differ from typical dead end streets such that they end in a circular turn-around space that permits vehicles to exit by making a wide U-turn. An aerial view of a typical cul-de-sac is provided in the appendix (figure 1).

Cul-de-sacs have a number of important benefits. For suburban developers, cul-de-sacs allow them to place more homes in oddly shaped tracts of land (Nielsen and Lonngren).  For residents, cul-de-sacs provide privacy and limit the noise from traffic while still remaining a part of the larger suburban community. Their one entrance and exit naturally help to constrain the speed of traffic, as well as the frequency of unknown vehicles passing through. Because of lower traffic, they encourage walking, bicycle use and outdoor activity by children. Unsurprisingly, homebuyers perceive houses surrounding cul-de-sacs to be safer than those located on two-way streets, and are willing to pay a premium for them (Neilsen).

However, others criticize cul-de-sacs. By definition, these communities are not well connected to other streets and they are often far from the central business district (CBD) and other areas of economic activity and community participation (Jagannath). On one hand, they encourage automobile use, as public transportation services are unable to accommodate their select residents. This, in turn, produces urban congestion in other parts of the community as well as a host of environmental problems associated with increased vehicle use. On the other hand, they create a number of inefficiencies with respect to the provision of public goods and services. It is more difficult to sweep streets or plow snow in cul-de-sacs. Further, it is more difficult to patrol cul-de-sacs and emergency vehicle access can sometimes be limited (Lonngren).

Much of the common knowledge regarding the popular appeal of cul-de-sacs is based on the idea of safety. As the logic goes, criminals try to avoid areas that lack easy entrance and exit. Further, if a crime is committed in a cul-de-sac, criminals will have a more difficult time escaping. Since residents of cul-de-sacs tend to be more familiar with each other, they are more likely to report and deter suspicious activity on behalf of their neighbors. Further, since fewer people frequently pass through cul-de-sacs, potential criminals would be unaware of opportunities in those communities. However, as noted by Lonngren, it is more difficult to police cul-de-sacs; these homes may actually provide better targets for criminals. Neilsen further notes that cul-de-sac statistics reveal some of the highest rates of traffic accidents involving young children. According to William Lucy, a professor of environmental studies at the University of Virginia, “the actual research about injuries and deaths to small children under five is that the main cause of death is being backed over, not being driven over forward” (Neilsen).

Little academic research exists regarding criminal activity with relation to the spatial layout of cul-de-sacs, and the majority that does remains inconclusive. As Hillier and others admit, it is difficult to untangle additional socioeconomic variables from the spatial layout of such communities (Hillier). However, it remains a useful exercise to conduct natural experiments that try to minimize such socioeconomic concerns in order to better understand our communities. Though it may not be possible to understand the true magnitude of the additional safety benefit provided by cul-de-sacs, it is certainly feasible to look at direction the answers is pointing. As such, it is possible to evaluate the following question: is living on a cul-de-sac in Durham safer than on a two-way street? To better answer this question, it is worth taking a brief look at recent criminal activity in Durham.



According to FBI statistics, the year 2012 marked an all-time low in violent crime (murder, rape, robbery and aggravated assault) and property crime (burglary, larceny and motor vehicle theft) committed in Durham (Durham Police Department). Crime continued its downward trend from the year 2000; this is shown in the appendix, figure 2. In particular, property crime reached its lowest level since 1988, due to a decrease in larceny and burglaries. Perhaps most striking, property crime is down 44% since the year 2000, with burglaries falling by 15% and larceny by 7% since 2011 (Durham Police Department). Still, larceny and burglary are the two largest contributors to Durham crime, constituting 80% of all criminal activity. These statistics are demonstrated graphically in the appendix, figure 3.

Though criminal activity is at a 23-year low, there were still over 15,000 crimes committed in Durham last year, approximately 80% of which are related to property. Consequently, analyzing the differences in property crime between housing communities on cul-de-sacs and two-way streets may prove useful. Thus far, no specific research exists regarding Durham spatial differences and crime rates. I attempt a first pass at demystifying and exploring these differences below.



I begin by identifying communities in Durham that are built around cul-de-sacs using satellite imaging tools available through Google Maps. I selected 36 suitable cul-de-sacs that are relatively similar with respect to spatial layout. I then pair each of these cul-de-sacs with a nearby two-way street comprised of similarly priced houses. While pairings differ in terms of relative pricing, each pair itself reflects a comparatively equivalent level of housing quality. I then compare each pairing with approximately 15,000 pieces of data regarding criminal activity in the city from the year 2012; such data is publically available from the Durham Police Department and their Geographical Information Systems (GIS) software. I then determine the total number of crimes committed in cul-de-sacs and on adjacent two-way streets. Further, I narrow criminal activity to single-family dwellings to remove possible biases from high traffic commercial properties and high-density apartment complexes. I conclude by separating crimes into three categories: crimes related to larceny, crimes related to assault, and crimes related to burglary/breaking and entering. This provides a more detailed assessment of the common types of crime that occur in cul-de-sacs and on two-way streets.

While the approach is simplistic, it has several advantages. First, pairing cul-de-sacs with nearby (often adjacent) two-way streets removes certain spatial biases: geographically close streets create a sensible natural experiment such that we can assume many spatial variables are held constant. Second, it mitigates socioeconomic biases by evaluating housing communities of similar economic qualities. Third, the approach applies uncomplicated economic principles to thinking about the relationship between criminal activity in cul-de-sacs and two-way streets. It ultimately provides a foundation for more detailed future research.



The data is summarized in the table below (table 1):



Table 1: Summary statistics of crime rates between cul-de-sacs and two-way streets

In total, there were 89 crimes committed within the selected communities, with 74 occurring on properties located on two-way streets and 15 within communities located on cul-de-sacs. This yields a 1-to-4.93 cul-de-sac to two-way street crime ratio. Stated differently, for every crime committed in a community based around a cul-de-sac, there are nearly 5 committed in a related community along a two-way street.

Compared to total Durham crime, this sample reflects less than 1% (approximately .60%) of total crime committed in Durham. However, this appears reasonable. Given a number of generous assumptions such that there are 20-30 homes per selected pairing, and approximately 107,000 total households in Durham County according to the U.S. Census Bureau, assuming that crime is evenly distributed among only households we would expect this to approach a 1% crime rate (30*36/107,000 = 1.01%). Knowing that crime is not evenly distributed and that much criminal activity occurs in highly frequented public spaces, dense residential communities and commercial areas, we can generally infer that this sample appears appropriate to provide a picture of residential criminal activity.

It is important to interpret these results in the context of total Durham crime in 2012 (see appendix, figure 3). While larceny was the largest category of criminal activity, constituting 53% of total Durham crime in 2012, it only comprises 25.83% of crime in the 36 selected communities. There are several notable considerations that may explain the difference. According to the Durham Police Department Annual Report, shoplifting constituted 25% of all larcenies (4). Further, the single largest percentage of larcenies at 40% consisted of the theft of motor vehicles and motor vehicle parts (4). Since this survey only compared single-family homes, and not criminal activity regarding places of commerce or high-density vehicle parks, these results appear more reasonable.

Burglary constitutes the majority of criminal activity in the 36 paired communities at 58%. This again appears intuitively reasonable as the sample reflects only single-family homes that, by their very nature, are more spatial isolated. This isolation and lower population density makes these homes better targets for potential criminals. The final 15.7% of crimes come in the form of assault. This is a bit higher than the Durham average for violent crime. However, approximately 80% of these assault offenses are deemed simple assault, a misdemeanor, and are not captured in the aggravated assault numbers that figure 3 highlights. Thus, aggravated assault rates are actually found to be lower in the 36 selected communities than Durham on the whole.



Though it would appear that cul-de-sacs in Durham are less prone to criminal activity than adjacent two-way streets, taking this result at face value would be misleading and overshadows several notable concerns. First, the relative breakdown of types of crime between two-way streets and cul-de-sacs is not markedly different; larceny, assault and burglary are all proportionally similar. As it looks, there is simply more crime by volume on two-way streets, perhaps pointing to housing volume concern.

I assume that the selected pairings of cul-de-sacs and two-way streets have a relatively similar number of housing units. While a handy approximation, this is most likely not the case. Cul-de-sacs tend to have fewer housing options than comparable two-way streets, given the nature of their short circular design. Additionally, housing on two-way streets may be more densely concentrated with smaller lot sizes. Adjusting for lot size is necessary to smooth out these crime rates. This is a systematic limitation of relying on GIS data; it is not specific enough to determine and adjust for property sizes. However, in order to claim that crime differences are completely negligible between cul-de-sacs and two-way streets purely on the grounds of total housing units, it would be necessary to assume nearly five houses on each two-way street for every one in each cul-de-sac. This seems unlikely, as plot sizes appear comparable and such housing communities were carefully selected. Thus, cul-de-sacs do likely maintain some spatial advantage with respect to criminal activity holding housing volume constant and lot size constant.

Johnson and Bowers raise another relevant point in their study of cul-de-sac safety: it is possible that the type of people who live on cul-de-sacs differ from those who live on two-way streets in ways that might increase their risk of victimization (107). Such people may be of a different socioeconomic status, age, marital status or ethnicity. Perhaps such households predominantly have young children. Given these considerations, it is possible that risk profiles differ among residents and may contribute to a difference in criminal activity exposure that is not linked to the spatial design of such communities.

Spatial permeability is another concern. Johnson and Bowers reference a study by Armitage (2007) that showed crime rates were typically lower in communities built on cul-de-sacs, except when such communities were connected to other streets or public areas by footpaths or trails (107). This is a spatial concern that is directly linked to crime rates and is notably absent from the findings above. Future research would need to account for such connectivity differences in cul-de-sacs; available GIS data is again limiting.

Though cul-de-sacs appear moderately safer than two-way streets, ultimately, correlation does not prove causality. While there appears a strong correlation between lower crime rates and spatial housing layout, one does not dictate the other. Further research is necessary to better evaluate such claims.



It is difficult if not impossible to accurately assess the magnitude that spatial differences play in determining criminal activity. A variety of socioeconomic variables, as well as serendipity, are often present and problematic to untangle from pertinent spatial differences. Others biases may yet be at play. For example, residents of cul-de-sacs tend not to be random; they are self-selecting and seek the benefits and style of living that cul-de-sacs provide. Further, they may also be more affluent. Given two ideal communities that exist ceteris paribus, the one located on a cul-de-sac will command a higher economic premium than the one on a two-way street. Therefore, a comprehensive analysis of spatial differences in crime rates remains illusive. Moreover, even if such an analysis were possible, it would be questionable to extend the findings to communities outside of a given region; local political and socioeconomic differences appear too nuanced to realistically do so.

            However, that is not to say that such research is fruitless. The careful public policy strategist or city planner may continue to utilize GIS data to better understand local spatial differences in order to craft germane policy. Further, such spatial criminal research may be used to identify high-crime communities and lead to better policing of public spaces. A good example comes from the East Weaver Street public housing community. Though East and West Weaver Street are over one mile in length, 6 out of every 7 crimes committed in the area occur in a small public housing community that constitutes a tenth of mile. Insights like this may be useful to help local authorities increase policing and to direct city planners’ time to addressing the causes of criminal activity in the area.






Figure 1: A typical cul-de-sac as shown from Google Maps.




Figure 2: Index Crime Rate per 100,000 Residents by Year for Durham, North Carolina (Durham Police Department).





Figure 3: Crime Breakdown for 2012 in Durham, North Carolina (Durham Police Department).




Figure 4: Durham Crime Mapper Software screenshot. Provides a graphical layout of crime locations as well as police and sheriff tables that detail the exact location of criminal offenses. Red dots indicate police responses while yellow stars indicate sheriff responses.




Durham Police Department. Annual Report: 2012 Durham Police Department. Durham, 2012.             http://durhamnc.gov/ich/op/DPD/Documents/2012AnnualRepor0301FINAL.pdf.


Durham Police Department. Crime Mapper Online Software. Durham, 2012.    http://gisweb.durhamnc.gov/gis_apps/crimedata/dsp_entryform.cfm


Hillier, Bill. “Can Streets Be Made Safer?” Palgrave Macmillan 9.1 (2004): n. pag. ProQuest. Apr. 2004.           Web.    http://proxy.lib.duke.edu/login?url=http://search.proquest.com.proxy.lib.duke.edu/advanc  ed?url=http://search.proquest.com.proxy.lib.duke.edu/docview/194522636?accountid=105            98.


Jagannath, Thejas. “Do We Need Cul-de-sacs?” Urban Times RSS. N.p., 25 Jan. 2013. Web. 01 Apr.             2013. <http://urbantimes.co/2013/01/do-we-need-cul-de-sacs/>.


Johnson, Shane D., and Kate J. Bowers. “Permeability and Burglary Risk: Are Cul-de-Sacs Safer?”    Journal of Quantitative Criminology 26.1 (2010): 89-111. Print.


Lonngren, Betty. “Cul-de-sacs Unproven As Deterrent To Crime.” Chicago Tribune. N.p., 25 Apr.      1993. Web. <http://articles.chicagotribune.com/1993-04-25/business/9304250091_1_sacs-      cul-chicago-neighborhoods>.


Nielsen, John. “Cul-de-Sacs: Suburban Dream or Dead End?” NPR. NPR, 07 June 2006. Web. 07   Apr. 2013. <http://www.npr.org/templates/story/story.php?storyId=5455743>.



  1. Hey Chris,

    I found your analysis of relative safety of cul-de-sacs compared to two-way streets really intriguing. I thought you did a great job of describing the differences in benefits and critiques of cul-de-sacs in past research as well as comparing crime data for Durham as a whole to your findings. Your analysis shows very neat and careful work.

    I thought you have done an incredibly thorough job of describing any possible limitations to the application of your findings and further research to be done. I have just a few suggestions that you may as well choose to ignore as I am no authority in economic research. 🙂 When reading through the description of your methodology I found myself wondering what exactly you meant by “each pair itself reflects a comparatively equivalent level of housing quality.” I think you would have gained from further explaining what you have done in order to ensure that. You say that you have paired houses with similar prices, but there are many factors that house values represent. For example, talking about average house size, lot size, age, and demographics and showing that the houses you have chosen are also similar in those metrics could be a good idea. I am sure you have eliminated houses that are not comparable to each other, but it would be great to talk about it and describe all this work you have already done. Moreover, mentioning some historic background on the neighborhoods you are comparing and whether they are considered safe or not relative to other places in Durham could provide additional information when you talk about what you would expect to see in terms of overall crime rates for these areas.

    Finally, when you talk about possible noise due to differences in volume of houses, I am wondering if maybe separating the two-way streets in batches of the same number of houses as there are on the cul-de-sac you are comparing them to would have helped. Once again, just an idea that you may have considered, but I thought I should mention it. Thank you for a really interesting read and I am looking forward to reading your final project!



  2. Hey Chris,

    Like Katerina, I also enjoyed reading your paper. I thought that your analysis could have perhaps benefitted from a couple of well placed regression analyses, which may have helped you to infer causality rather than simply correlation. I believe that may have been beyond the scope of this class, though, and my paper definitely could have benefitted from this too.

    Overall, I thought your decision to analyze the relationship between cul-de-sacs and crime was very creative and could possibly lead to the readjustment of residential prices in the area.

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