1. University Bus Systems: Network Flow Demand Analysis By Craig Yannes University of Connecticut October 21, 2008

2. Introduction  University bus systems are an important form of transportation around university campuses  Research has shown that these systems generate more ridership than their counterparts (Daggett and Gutkowski, 2005)  University enrollment has also been expanding

3. Problem  The sharp increase in demand has put a strain on university resources to provide an effective bus system  Many routing design decisions have been made subjectively  This results in an inefficient system, which leaves demand centers unidentified, underserved or unserved

4. Solution  Network flow theory, in conjunction with spatial analysis (GIS), can help remove the subjectivity from university bus system design  Focus of this project is the selection of optimal stopping locations considering operational cost while serving the maximum passengers (demand)

5. Goals  Create a simple and efficient model framework to analyze the coverage of a university bus system  Analyze the effects of stopping service areas (walk distance to stop) on the selection of optimal stopping locations

6. Objectives  Collect and generate transportation link and transit demand data  Generate and analyze demand data to create centers which will serve as potential bus stops  Create a network flow model representation and use an appropriate solution technique, yielding the optimal demand centers to be served by the bus system at differing service areas

7. Background  The following have utilized network flow algorithms and theory to solve transit design (routing, scheduling, frequency, etc.) problems: Ceder and Wilson (1986) Chu and Hobeika (1979) Ranjithan, Singh and Van Oudheusden (1987) LeBlanc (1988) Kocur and Hendrickson (1982) Kuah and Perl (1985)

8. Background  Overall transit design involves two interest groups (passenger and operator)  Depending on the component being designed, the focus shifts between these groups  This proposed research will focus solely on operator costs while attempting to serve the maximum amount of passengers

9. Background  Furth, Mekuria and SanClemente (2007) created and used GIS applications to analyze the spacing of transit stops based on the street network and parcel data  The study evaluated walking, riding and operating costs when stops were reconfigured from the existing placement  Similar to this research except that no network flow theory was used

10. Network Representation The following design was used to create a network representation of the bus system: Arcs leading to accessible nodes based on current location Cost on Links is a function of distance and demand Nodes representing potential stopping locations Supply Node (Bus Depot) Supply = Number of demand nodes Destination nodes which are spread throughout the exterior of the network to pull flow in all directions Demand = 1 for each node

11. Data  Connecticut Department of Environmental Protection: Connecticut Street Network Shapefile (1:100,000)  2006 UConn personal geodatabase which included street, building and parking lot feature classes

12. Transportation Network

13. Demand  Calculated using ITE Trip Generation Manual  Produces auto trips based on the building/area purpose and attributes such as area, number of seats and number of units  Although this research focuses on transit trips, the auto trips can be used to determined relative demand between locations

14. Building and Parking Lot Demand

15. Potential Stopping Locations  32 Locations were selected at points along the roadway near key intersections and large generators  The demand at each one of these stops is equal to the sum of demand of the buildings and parking lots within a particular distance (1/8, 1/4, 1/2 mile) of the stopping location  5 destination locations were also selected such that the flow would be spread around the network evenly

16. Potential Stopping Locations

17. Link Generation between Stops  Links represent the transportation path between two stops though it does not follow street layout directly  The following rules were used to create the links between the stops: Links must proceed in a forward progression (must be getting closer to a destination) Links cannot pass through stops Stops on the exterior must connect with sink locations

18. Link Generation

19. Link Cost  Combination of two factors Distance between stops Demand at the ending stop  Because higher demand should incur less cost the inverse demand was used  This requires a scaling factor so that demand values are comparable in magnitude to distance 

20. Network Representation

21. Solution Technique  A geometric network was created in GIS weighted with the calculated link cost  The Network analyst toolset in ArcGIS was used to find the shortest path between the source node and each of the 5 sink nodes  The nodes that lie on these shortest paths are the optimal stopping locations

22. 1/8 Mile Service Area

23. 1/4 Mile Service Area

24. 1/2 Mile Service Area

25. Results Path 1/8 mile1/4 mile1/2 mile Stops Distance (miles) Stops Distance (miles) Stops Distance (miles) 13-52.543-52.543-52.54 213-12-11-81.1413-12-11-220.9913-29-100.79 313-12-11-220.9913-12-11-220.9913-12-11-220.99 430-23-32-201.3230-23-32-201.3230-23-32-201.32 530-23-280.9930-23-280.9930-23-280.99 Total 17 stops (12 unique) 6.98 17 stops (11 unique) 6.83 16 stops (13 unique) 6.63

26. Conclusions  A model framework has been created which analyzes a bus network yielding optimal stopping locations  Increasing the service area, reduces the distance traveled and increases that amount of unique stops served by the system  Planners must be cautious when trying to balance ridership and efficiency  Analyzing the system for different service areas can help quantify this relationship and create a more efficient system

27. Future Research  Expand the analysis area to include other locations surrounding the campus  Acquire or generate more accurate demand data  Comparison / application to the existing bus system  Incorporate the effect of larger service areas on demand  Create similar network frameworks that focus on the other aspects of bus system design

28. Comments / Questions?

29. References  Daggett J. and Gutkowski R. (2003). University Transportation Survey: Transportation in University Communities. Colorado State University.  Sutton J. C. GIS Applications in Transit Planning and Operations: A Review of Current Practice, Effective Applications and Challeneges in the USA. Transportation Planning and Technology, Vol. 28, 2005, pp. 237-250.  Furth P. G., Mekuria M. and SanClemente J. Stop-spacing Analysis Using GIS Tools with Parcel and Street Network Data. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.  Ceder A. and Wilson N. H. M.. Bus Network Design. Transportation Research Part B, Vol. 20B, 1986, pp. 331-344.  Chu C. and A. G. Hobeika. In Transportation Research Record: Journal of the Transportation Research Board, No.730, Transportation Research Board of the National Academies, Washington, D.C., 1979, pp. 7-13.  Institute of Transportation Engineers (ITE). Trip Generation, 6th ed., Washington, D.C., 2003.  Kocur G. and Hendrickson C. Design of Local Bus Service with Demand Equilibrium. Transportation Science, Vol. 16, 1982, pp. 149-170.  Kuah G. K. and Perl J. A methodology for feeder bus network design. In Transportation Research Record: Journal of the Transportation Research Board, No.1120, Transportation Research Board of the National Academies, Washington, D.C., 1985, pp. 40–51.  LeBlanc L. J. (1988). Transit system network design. Transportation Research Part B, Vol. 22B, 1988, pp. 383-390.  Ranjithan S., Singh K. N., and Van Oudheusden D. L. The Design of Bus Route Systems – An Interactive Location-Allocation Approach. Transportation, Vol. 14, 1987, pp. 253-270.

30. References  GIS Data Connecticut Department of Environmental Protection http://www.ct.gov/dep/cwp/view.asp?a=2698&q=3228 98 http://www.ct.gov/dep/cwp/view.asp?a=2698&q=3228 98 Richard Mrozinski, University of Connecticut Department of Geography  Images Title: http://www.park.uconn.edu/http://www.park.uconn.edu/ Problem: http://www.news.com.au/dailytelegraph/story/0,22049,2 1265300-5011906,00.html http://www.news.com.au/dailytelegraph/story/0,22049,2 1265300-5011906,00.html Background: www.caliper.com/UK/transcad.htmwww.caliper.com/UK/transcad.htm Questions: http://www.pritchettcartoons.com/newcar2.htm http://home.fuse.net/ard/jandress/transfuture3.jpg http://www.pritchettcartoons.com/newcar2.htm http://home.fuse.net/ard/jandress/transfuture3.jpg