A New Approach in the GIS Bikeshed Analysis Considering of Topography, Street Connectivity, and Energy Consumption

Transcription

1 A New Approach in the GIS Bikeshed Analysis Considering of Topography, Street Connectivity, and Energy Consumption ACSP Conference, Cincinnati, OH November 1, 2012 Hiroyuki Iseki, Ph.D. & Matthew Tingstrom National Center for Smart Growth Research and Education Urban Studies and Planning Program School of Architecture, Planning, and Preservation University of Maryland, College Park

2 BACKGROUND

3 Growing Importance of Cycling Cycling has increased its importance as an alternative mode of transportation to: address congestion and environmental problems, promote physical activities and improve public health. Bicycle-sharing programs have been gaining popularity in many European and US cities

4 Use of GIS Analysis in Bicycle Planning Existing methods of GIS-based analysis in bicycle planning, such as heat maps and bike-demand analysis, include factors: land use street types bike facilities demographics of residents transit services

5 Defining Generalized Costs of Travel for Cyclists A GIS analysis uses travel impedance, which is often expressed by travel distance and time. Physical environment influences cyclists efforts and energy required to travel, and therefore route selection and decision whether to travel by bicycle. Topography/terrain Road surface Street density and connectivity Weather Traffic conditions Sources: Wardman, Parkins, and Page 2008; Frazer and Lock 2010

6 Study Area Topography 11 proposed LRT stations in Montgomery County, MD conditions.

7 The objective of this study To develop GIS bikeshed analysis methods that incorporate: distance topography / terrain (street slope) street connectivity (presence of intersections) into estimates of energy consumed to bike in order to determine bicycle sheds.

8 Methodology, Data, and Data Sources FRAMEWORK

9 Examples: Topography s Influence on Bikesheds With the same level of energy consumption, downslope allows a cyclist to travel longer distance. Extent and cross-sectional view of hillside bikeshed with a 1.5 percent slope.

10 Examples: Topography s Influence on Bikesheds The closer the slopes to the origin of trip, the more substantial its effect on the size of bikeshed; the smaller the size gets. Extent and cross-sectional view of near and distant hills with 4 percent slope.

11 Steady-Speed Power Equation W rider = [K A * (V + V W ) 2 + m * g * (s + C R )] * V air resistance slope factor rolling resistance Table 1: Values Used for Variables and Coefficients in the Analysis of Bikesheds

12 Data & Data Sources Data LPA Purple Line station locations National Elevation Dataset 1/9 Arc-Second Street network Source Maryland Transit Administration and Whitman, Requardt & Associates, LLP US Geological Survey StreetMap USA, Esri Inc. WMATA Metrorail systemgis Program, Office of the Chief Technology Officer, District of Columbia

13 Five Different Methods Method Description 1 Bird-fly straight line distance: 7.08 km 2 Distance in the street network: 7.08 km 3 Energy consumption with absolute slope: 50,000 J 4 Energy consumption with slope & direction: 50,000 J (the overlapping area of away and toward bikesheds) 5 Energy consumption with slope & direction + intersection impedance: 50,000 J 50,000 Joules is equivalent to 7.08 km (4.43 mile) on a flat terrain with the previous conditions.

14 Energy Consumption at Intersections Estimated values for energy consumed at intersections are assigned using the ArcGIS Global Turns Evaluator.

15 RESULTS OF ANALYSIS Photo: Georgetown Branch Trail, Maryland

16 Bikeshed Area by Five Methods

17 Toward & Away Bikeshed Areas by Method 4

18 Bikeshed Area by Five Methods

19 Bikeshed Area (Square Kilometers-km 2 ; Log-scale)

20 Total Street Length (Kilometers-km; Log-scale)

21 Street Density in Bikesheds (1/km) Street density decreases as distance from station increases.

22 Two Areas with Different Topography Bethesda Method 1:2:3:4:5 = 100:64:7:17:10 Lyttonsville Method 1:2:3:4:5 = 100:60:2:7:4 A bikeshed is smaller in Lyttonsville where steep slopes in the station s immediate neighborhoods, compared to Bethesda.

23 Bikeshed Slopes Obtained with Method % 7.1% 4.6% 3.1% Bethesda Lyttonsville Bikesheds with steeper average slope also have a larger variance.

24 Conclusion We developed methods to incorporate topography (slopes) and street connectivity (intersections) into travel impedance based on energy consumption to generate bikesheds. When energy consumption of the cyclist was accounted for, the bikeshed size and shape varied greatly depending on topography, presence of intersections, and street network. The geographic distribution of slopes also influence the size and shape of bikeshed, and makes it difficult to predict its effects by any simple indicator.

25 Implications for Bike Planning Common GIS analysis approaches using simple planar distance result in a substantial overestimation of bikesheds and biking demand level where steep slopes and many intersections can be seen. The substantial effects of intersection impedance indicates the importance of preserving kinetic energy for cyclists. 1. the Idaho (or rolling) stop law 2. bike planning to eliminate stops and keep continuity of bike paths