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In the past 50 years, the loops-and-lollipops design has become the basic building block of many urban neighborhoods. In the field of traffic engineering, this combination of cul-de-sacs and loop streets is designed to discourage through traffic and improve road safety, and thus it has the support of many traffic engineers. Perhaps because of its intuitive appeal, few studies have examined the impact of this design on road crashes. The city of Calgary, Alberta, Canada, was used as a case study to examine the effects of neighborhood street patterns on the number of reported crashes. In the study, crashes were converted into equivalent property-damage-only crashes using various weighting factors to check the sensitivity of the finding. Results suggest that currently popular road patterns such as warped parallel, loops, and lollipops are safer than the traditional gridiron pattern. Moreover, this result is quite robust regarding severity weights or aggregation schemes, albeit with some variations in the absolute values of the estimated effects. However, changing the aggregation scheme had a significant effect on some of the control variables used in the model, especially the socioeconomic characteristics, although most of the road features and land use estimates remained robust.

Background: Traffic demand is growing worldwide and the increased carbon emission from transport and travel activities is contributing to greenhouse gas emission and climate change. As the oil and gas capital of Canada, the city of Calgary has a very high carbon footprint per population and the reduction of automobile use is an important policy goal for the city. Walking, a part of active transportation promotes sustainable transportation initiative by reducing greenhouse gas emission. To encourage walking, favorable walking environment should be ensured which largely depends on street pattern and connectivity. However, the effect of street pattern on walking at community level was not explored much in previous studies, particularly at rapidly expanding city such as Calgary’s context. Aims and Objectives: The study identifies the effects of different neighborhood design and planning factors associated with the share of walking in work trips while controlling for differences in social economic characteristics of the neighborhood. Methods: A linear regression model was developed using community-level data from the 2011 census and the road infrastructure data of Calgary. Results: Our study finds that different street patterns and types of land use, length of train tracks, number of train stations and number of schools have significant effect on walking. Conclusion: Thus, different neighbourhood street patterns and land uses should be considered in the development of new communities for promoting active and sustainable transportation.