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Measuring the Changes in Aggregate Cycling Patterns between 2003 and 2012 from a Space Syntax Perspective.

Law S, Sakr FL, Martinez M - Behav Sci (Basel) (2014)

Bottom Line: More importantly, results also suggest that higher cyclist movement were observed along routes with greater convenience and continuity-over and above route segregation from vehicular traffic.Further research is needed into validating the results and examining this relationship at an individual basis on route choice.These results help us better understand the trade off between cycling safety and cycling legibility which could help inform cycling route design in the future.

View Article: PubMed Central - PubMed

Affiliation: Bartlett School of Graduate Studies, University College London, 132 Hampstead Road, London, NW1 2BX, UK; E-Mails: fesakr@gmail.com (F.L.S.); m.martinez@spacesyntax.com (M.M.) ; Space Syntax Limited, 21 Brownlow Mews, London, WC1N 2LG, UK.

ABSTRACT
There has been a world-wide surge of interest in cycling over the last 10 years of which London has seen a continuous growth in cyclists and investment in infrastructure that has resulted in the introduction of the Barclays Cycle Superhighway and Barclays Cycling Hiring Scheme. Despite the investment in cycling infrastructure, there has been little understanding of cycling activity patterns in general and the effect of spatial configuration on cycling route choices. This research aims at measuring the impact of cycling infrastructure and spatial configuration on aggregate cyclist movement over two time periods. To do so, this paper presents a spatial-based cyclist movement statistical model that regress cyclist movement flows with measure of spatial configuration, safety and infrastructure and urban character attributes. Using Elephant and Castle, a Central London location, as a case study, the authors analyze cycling movement data sets from 2003 and 2012 to compare the change in cycling behaviour and the impact that the Cycling Superhighway 07, introduced in 2011, has had on cycling patterns. Findings confirm the growth of cycling in London with a 1000% increase in cyclists along some routes in comparison to a 10% increase in population at the same time. More importantly, results also suggest that higher cyclist movement were observed along routes with greater convenience and continuity-over and above route segregation from vehicular traffic. The relationship between spatial configuration and aggregate cyclists movement is consistent between 2003 and 2012 where spatial configuration have remained the same while changes were observed in both modal split and cycling infrastructure. This result is in line with previous research wherein aggregate higher cyclists movement are observed on major routes offering direct connections than less direct routes. From a spatial cognition perspective, this research enriches our understanding on how the external built environment as measured by the spatial configuration measure relates to aggregated cyclists movement overtime and in identifying key potential factors in influencing cyclist wayfinding. Further research is needed into validating the results and examining this relationship at an individual basis on route choice. These results help us better understand the trade off between cycling safety and cycling legibility which could help inform cycling route design in the future.

No MeSH data available.


Related in: MedlinePlus

Cyclist movement distribution across the time comparison.
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behavsci-04-00278-f010: Cyclist movement distribution across the time comparison.

Mentions: Figure 10 shows cycling movement distribution across time where the X axis shows the time period and Y axis shows the average cyclist per hour. The red line show the Elephant and Castle route, the blue line show Elliott’s Row on CS7, the green line shows average cyclist movement for all gates. Qualitatively, faster commuter cyclists were observed more on Elephant and Castle whilst slower non commuter cyclists were observed on CS7. The difference between the most accessible route over the safer designated CS7 route persist throughout the day.


Measuring the Changes in Aggregate Cycling Patterns between 2003 and 2012 from a Space Syntax Perspective.

Law S, Sakr FL, Martinez M - Behav Sci (Basel) (2014)

Cyclist movement distribution across the time comparison.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4219268&req=5

behavsci-04-00278-f010: Cyclist movement distribution across the time comparison.
Mentions: Figure 10 shows cycling movement distribution across time where the X axis shows the time period and Y axis shows the average cyclist per hour. The red line show the Elephant and Castle route, the blue line show Elliott’s Row on CS7, the green line shows average cyclist movement for all gates. Qualitatively, faster commuter cyclists were observed more on Elephant and Castle whilst slower non commuter cyclists were observed on CS7. The difference between the most accessible route over the safer designated CS7 route persist throughout the day.

Bottom Line: More importantly, results also suggest that higher cyclist movement were observed along routes with greater convenience and continuity-over and above route segregation from vehicular traffic.Further research is needed into validating the results and examining this relationship at an individual basis on route choice.These results help us better understand the trade off between cycling safety and cycling legibility which could help inform cycling route design in the future.

View Article: PubMed Central - PubMed

Affiliation: Bartlett School of Graduate Studies, University College London, 132 Hampstead Road, London, NW1 2BX, UK; E-Mails: fesakr@gmail.com (F.L.S.); m.martinez@spacesyntax.com (M.M.) ; Space Syntax Limited, 21 Brownlow Mews, London, WC1N 2LG, UK.

ABSTRACT
There has been a world-wide surge of interest in cycling over the last 10 years of which London has seen a continuous growth in cyclists and investment in infrastructure that has resulted in the introduction of the Barclays Cycle Superhighway and Barclays Cycling Hiring Scheme. Despite the investment in cycling infrastructure, there has been little understanding of cycling activity patterns in general and the effect of spatial configuration on cycling route choices. This research aims at measuring the impact of cycling infrastructure and spatial configuration on aggregate cyclist movement over two time periods. To do so, this paper presents a spatial-based cyclist movement statistical model that regress cyclist movement flows with measure of spatial configuration, safety and infrastructure and urban character attributes. Using Elephant and Castle, a Central London location, as a case study, the authors analyze cycling movement data sets from 2003 and 2012 to compare the change in cycling behaviour and the impact that the Cycling Superhighway 07, introduced in 2011, has had on cycling patterns. Findings confirm the growth of cycling in London with a 1000% increase in cyclists along some routes in comparison to a 10% increase in population at the same time. More importantly, results also suggest that higher cyclist movement were observed along routes with greater convenience and continuity-over and above route segregation from vehicular traffic. The relationship between spatial configuration and aggregate cyclists movement is consistent between 2003 and 2012 where spatial configuration have remained the same while changes were observed in both modal split and cycling infrastructure. This result is in line with previous research wherein aggregate higher cyclists movement are observed on major routes offering direct connections than less direct routes. From a spatial cognition perspective, this research enriches our understanding on how the external built environment as measured by the spatial configuration measure relates to aggregated cyclists movement overtime and in identifying key potential factors in influencing cyclist wayfinding. Further research is needed into validating the results and examining this relationship at an individual basis on route choice. These results help us better understand the trade off between cycling safety and cycling legibility which could help inform cycling route design in the future.

No MeSH data available.


Related in: MedlinePlus