2010 TRB Core Parking Published

1

Impact of On-Street Parking in the Core of a University Campus 1

2

Ryan Fries* 3

Assistant Professor 4

Box 1800, EB2063 5

Department of Civil Engineering, 6

Southern Illinois University Edwardsville, 7

Box 1800, Edwardsville, IL 62026, 8

phone: 618-650-5026, 9

[email protected] 10

11

Anne Dunning 12 Assistant Professor 13

164 Lee Hall 14

Department of Planning and Landscape Architecture 15

Clemson University, Clemson, SC 29634, 16

1-864-656-0151 17


19

Mashrur Chowdhury

20 Associate Professor 21

216 Lowry Hall 22

Department of Civil Engineering 23

Clemson University, Clemson, SC 29634 24

1-864-656-0151 25


27

28

29 *Corresponding Author 30

31 August 1, 2009 32

33 34

35

Word Count 6,585 (4,085 + 1,500 figures and tables) 36

37

TRB 2010 Annual Meeting CD-ROM Paper revised from original submittal.

mailto:[email protected]

mailto:[email protected]

2

ABSTRACT 1

Limited information is available on how removing parking from the center of a university 2

campus will impact the neighboring transportation system. The purpose of this study was to 3

evaluate the mobility impact of relocating such parking. A traffic simulation model was 4

employed to evaluate the transportation system before and after such a change in parking 5

management. The findings suggest that due to the significant number of motorists searching for 6

the high-demand parking in the core of campus, relocating this parking to periphery lots will 7

reduce the average travel time, even when accounting for the increased walking time. 8

9


3

INTRODUCTION 1

Determining the correct design and quantity of parking to provide in pedestrian areas has 2

flummoxed transportation planners for decades. People must have means of entering places 3

where pedestrian life thrives, but creating space for vehicles usually compromises quality of 4

pedestrian vitality. At issue is the conflict between two goals of transportation planning: access 5

and mobility. Most people want unfettered passage directly to their destinations (mobility 6

through supply of vehicle infrastructure) combined with vibrant street life and multiple amenities 7

in close proximity (access through pedestrian infrastructure and provisions. 8

9

University campuses experience this conflict acutely. Parking is often a significant source of 10

town-gown conflict and one of the most emotional issues within any university campus (1). 11

People coming to campus want front-door parking as they rush to classes and offices, but they 12

expect a safe environment for students to mill about. On the vehicle side, delivery trucks must 13

reach loading docks, employees must maintain facilities and grounds, people must access 14

academic buildings (frequently in large numbers at set times throughout the day), and small-scale 15

freight ranging from architectural models and presentation boards to multiple backpacks of 16

books must make it to class intact and in time. On the pedestrian side, hoards of people enter 17

and exit buildings and crosswalks as classes change, bands and demonstrators perform, students 18

with their heads in books, against a cell phone, or between headphones step into streets, and 19

people of all ages and physic all conditions interact. University parking engineers and planners 20

must simultaneously balance competing agendas to avert uproars from the town, students, 21

faculty, or staff. 22

23

Both adding and reducing parking stir volatility into this already-bubbling cauldron. If quantity 24

of supply is difficult to touch, perhaps the provision can be altered in another way. In the quest 25

to find the right balance between vehicle and pedestrian needs on a campus, can design help 26

alleviate this conflict? 27

28

The objective of this paper was to identify through simulation the effects of different parking 29

strategies on campus access and mobility. The rural campus of Clemson University in South 30

Carolina has served as a test bed for micro-simulation of alternatives for parking allocation. 31

TRENDS IN CAMPUS PARKING 32

National trends are changing the character of university campuses and their reliance on core 33

parking. While transportation planning on university campuses has usually focused on 34

automobiles (2), safety concerns are motivating the creation of pedestrian campus cores. To 35

create these pedestrian-friendly areas, several campuses have noted plans to reduce the volume 36

of automobiles in the core campus. These schools include Louisiana State University (3), 37

Cornell University (4), the University of South Carolina (5), the University of New Hampshire 38

(6), the University of Connecticut (7), the University of California schools (8), and Penn State 39

University (9). This list is not meant to be comprehensive, nor does it imply that these campuses 40

have made significant progress towards reducing core campus volumes, rather the list represents 41

a general consensus that the problem exists. 42

43


4

To reduce vehicle circulation in campus cores, some have relocated parking to the periphery of 1

campus (1-5), some have simply removed core campus parking (3), and others are allowing the 2

eventual expansion of buildings to reclaim the core campus parking spaces (4; 5). All of these 3

approaches have met different types and levels of resistance from the campus and local 4

community. 5

6

Providing significant amounts of curb parking promotes motorists searching for parking, 7

particularly when there is little price difference between on-street and off-street parking (10). 8

Such is the case on most university campuses, where parking is allocated by selling annual 9

permits valid for multiple parking locations (2; 11). Searching for parking, or cruising, has long 10

been a topic of study. Due to the difficulties of identifying those who are cruising for parking 11

versus those using the road for mobility, estimates of the percent of cruising vehicles ranges from 12

8 to 74 percent from studies published between 1927 and 2001 (12; 13; 14; 15; 16; 17; 18; 19; 13

20; 21). While these studies are published across several generations, they provide evidence of 14

the significant range that cruising vehicles can represent. Factors influencing these percentages 15

can include the price difference between on- and off-street parking, parking turnover rates, time 16

of day, and special events. Thus, removing on-street parking has the potential to reduce traffic 17

volumes, albeit by an uncertain amount. 18

PREVIOUS WORK 19

Previous efforts examining parking focused on either urban areas or campus cores. Studies 20

focusing on the former compared community vitality to parking, measured the number of 21

motorists cruising for parking, attempted to represent the decision making or routing behavior of 22

drivers searching for parking, and examined the income of parking meters under varying 23

strategies. These studies focusing on urban locations will be presented first. 24

Parking in Urban Areas 25

Several investigations have examined the link between downtown parking and the vibrance of 26

the central business district. Best-practices for downtown parking have included changing 27

parallel parking into diagonal parking and using one agency to manage the often-diverse aspects 28

of parking, such as signing, striping, enforcement, planning, development, and financing (22). 29

Others suggest that reducing parking requirements is a significant factor, finding that cities that 30

provided less parking also used less parking and were, “generally more vibrant (in terms of the 31

number of people around)…” These researchers proposed that the findings could guide planning 32

agencies to remove parking minimums and instead, place maximums on parking spaces provided 33

(23). Similar guidance has been offered when promoting transit oriented development (24), and 34

designing mixed-use parking facilities. Further study on the topic of changing parking codes has 35

predicted that reducing parking minimums will only cause a reduction in parking provided by 36

offices, medical plazas, and retail; having little impact on banks and groceries that usually 37

provide more than minimum local parking requirements (25). 38

39

When on-street parking is provided cheaper than off-street locations, motorists are encouraged to 40

search for on-street parking, or cruise. It is challenging to identify motorists who are cruising as 41

compared to those using the road for throughput. The proportion of motorists cruising is 42

significantly impacted by several factors including the under-pricing of curb parking, the 43


5

overpricing of off-street parking (10), time of day, average parking duration, and special events. 1

While previous estimates of the percent of cruising vehicles ranged from 8 to 74 percent, some 2

argue that properly pricing curb parking is the key to reducing traffic cruising for parking spaces 3

(20). 4

5

Others have used simulation models as tools for evaluating parking metrics. One study focused 6

on the searching time, probability of finding a space, and parking meter revenues. Parking 7

searching time was found linearly related to the parking duration, decreasing at approximately 8

the same rates. Additional findings indicated that with newer parking meters, those that reset 9

and show a zero balance after a vehicle pulls out of the space, parking revenues could increase 10

by approximately 23 percent (26). Other research using simulation to model on-street parking 11

focused on the calibration and accuracy of a new simulation tool (27). 12

Parking on University Campuses 13

Many studies of parking on university campuses have focused on factors impacting travel mode. 14

On a European college campus, researchers found that employees would only change their 15

automobile dependence if a fee was charged for parking (28). While most universities use 16

parking permits to allocate parking (2; 11), recent works have evaluated the efficacy of using 17

access gates and card readers to control parking on the campus of Virginia Polytechnical Institute 18

(29). 19

20

While parking design and planning vary significantly between uses (30), the studies presented 21

illustrate that cost and location of available parking are key factors in vehicle cruising. As 22

universities grow, usurping parking lots for new buildings is a common practice. Additionally, 23

trends towards safer pedestrian-friendly campuses increase pressure to remove parking in the 24

core of campuses. This paper sought to isolate the impact of parking cost and examine the traffic 25

volume changes from parking relocation. 26

METHODOLOGY 27

A traffic simulation model was developed using the software VISSIM. The details of this 28

process and of the core campus parking scenarios are presented in the proceeding sections. 29

Simulation Model Development 30

The researchers conducted a thorough review of available traffic simulation software, focusing 31

on abilities to model local and arterial streets, actuated and coordinated signals, public transit 32

vehicles, pedestrian, parking behaviors, and offering a three dimensional display. The deciding 33

factor was the ability to model detailed parking maneuvers. Based on these characteristics 34

VISSIM was chosen to model the Clemson University campus. 35

36

The model building process began by gathering aerial photographs and scaling them in 37

AutoCAD. The output of this step was one overlay figure containing multiple high-clarity aerial 38

photographs able to be inserted and scaled in the simulation program in a single step. The links, 39

nodes, parking lots, and intersections were created based on this compilation of aerial 40

photographs. The final network contained approximately 20,000 links or connectors and 41

approximately 740 nodes. 42


6

1

Next, traffic control devices and volumes were input into the model. Traffic control included 12 2

traffic signals and approximately 200 stop signs. The volumes were collected from manual 3

counts, video footage, and HiStar traffic counts around campus in fall of 2007. The information 4

from these sources was used to create 44 origin-destination matrices, including one matrix for 5

each hour, for each vehicle class. The 11 different vehicle classes were based on parking 6

privileges and included 1) commuter student, 2) faculty and staff, 3) university service cars, 4) 7

university service medium trucks, 5) handicapped, 6) student residents, 7) non-campus visitors, 8

8) large trucks (tractor or semi-trailers), 9) medium trucks, 10) buses, and 11) motorcycles. The 9

model simulated the 4-hour midday period when parking was most difficult to find and when 10

campus was at its peak occupancy. Pedestrian volumes, also counted during fall 2007, were 11

input at each crosswalk and not included in an origin-destination matrix. Researchers also 12

incorporated the operation of nine bus routes through and around campus, including the number 13

of boarding and alighting passengers based on a 2007 Ridership Count Survey (31). 14

15

Because there were several routes available to travel between each origin and destination, a 16

dynamic assignment approach was taken. This method required the researchers to run the model 17

several times, incrementally increasing volumes, to assign the proper amount of vehicles to each 18

route. After the volumes did not significantly vary between runs, less than a 15 vehicle 19

difference on key links, researchers began calibrating the model based on volumes as suggested 20

by previous studies (34,35,36). During this process, link cost and driver behavior parameters 21

were adjusted to recreate the volumes and speeds observed on campus. After the volumes were 22

within five percent and the speeds were within one mile per hour on key links, the model was 23

considered calibrated. 24

TABLE 1 displays the minor differences between the observed volumes and the simulated 25

volumes on 20 key campus links during the four-hour midday period. Note that no individual 26

link varied by more than five percent of the observed and the total volume was within one 27

percent, thus exceeding standard practice in calibration (34, 35, 36). 28

29

Validation was the final step to ensure the simulation model reflected the real world accurately. 30

Researchers used speeds (32; 33; 34) as the measure of effectiveness to ensure drivers were 31

reacting to the simulated network similarly as the observed drivers reacted to the real built 32

environment around Clemson. These speeds were observed numerically and graphically (in a 33

speed contour map) and compared to measured speeds along those segments. FIGURE 1 34

presents an example of a speed contour map for the Clemson network and aided the researchers 35

in identifying discontinuities in the traffic flow and potential discrepancies with the observed 36

traffic environment. 37

Simulation Scenario Operation 38

The simulation scenarios were designed to capture the impact of removing on-street parking 39

spaces from the core of campus. The base scenario included parking spaces as they were during 40

the fall semester of 2007 and the parking removal was simulated using this same parking 41

demand. Because VISSIM does not recognize the willingness of drivers to travel faster in wider 42

lanes, core campus speeds were not used as a measure of effectiveness; however, the authors do 43

recognize the need for modifying the built environment to maintain low vehicular speeds through 44


7

the core of campus if on-street parking is removed. The key measures of effectiveness were 1

travel time and delay. 2

3

The simulation software modeled parking search based on distance and attractiveness. Within 4

the model, researchers heuristically assigned an attractiveness number to each parking lot based 5

on its proximity to traffic generators, where closer parking spaces were more attractive. When 6

the vehicles traversed the link prior to their destination parking lot, routing decisions were used 7

to reroute them if the lot was full. A new parking lot was chosen based on proximity to the 8

vehicle and the attractiveness; thus, vehicles would choose the next closest parking location in 9

their destination zone. 10

FINDINGS 11

Currently, parking in the core of campus is allowed for faculty and staff, service vehicles, 12

handicapped motorists, and motorcycles. Because of the large amounts of pedestrian traffic, 13

there exist many vehicle-pedestrian conflict areas. Conflicts can be greatly reduced by lowering 14

the vehicular volume through the campus core. One scenario of reducing core-campus volumes 15

is to remove parking spaces. To evaluate this alternative, the simulation model was used. On-16

street parking was removed on Calhoun Drive south of Fort Hill Street and on Fernow Street 17

north of Palmetto Boulevard. It was assumed that this number of parking spaces was added to 18

lots E3 and E4, and the findings accurately indicate the reduction in volumes in the core of 19

campus. Refer to Error! Reference source not found. to located these facilities in and around 20

Clemson’s core campus. 21

22

Table 2 illustrates the findings from the simulation tool with respect to delay. Because there is 23

no overlap in the confidence intervals between the current conditions and the parking removal 24

scenario, there is significant (α >0.05) evidence that delay will be reduced by removing core-25

campus parking. The key route through campus, Calhoun Drive contains many crosswalks and 26

traffic control devices that slow vehicles. Further, there is a lower probability of finding 27

available parking and thus longer search times. Removing this parking can simplify this process 28

for drivers, guiding them directly to lots on the edge of campus where their parking search will 29

be faster. 30

31

The travel time findings were similarly conclusive. Table 3 shows the 95-percent confidence 32

intervals of the vehicle travel times before and after core-campus parking removal. As shown, 33

both the travel time variability and magnitude are less after removing the core campus parking. 34

35

Examining the changes in required walking times from each parking facility provides valuable 36

information to clarify the difference in travel times. Walking times between the existing and 37

proposed parking locations revealed that travelers require approximately 6 minutes, on average, 38

to walk from the proposed lot to the existing core-campus parking location. This additional 39

walking time represents 507 minutes of added travel time, negating the savings from fewer 40

cruising vehicles as shown in Table 4. 41

42

Another factor to consider is the added walking times required for those leaving campus with a 43

vehicle during lunch (or other mid-day commitment). Each motorist that was relocated from 44


8

core-campus parking is further impacted if they must use their vehicle during the day. Each such 1

trip adds another 12 minutes of delay due to the parking relocation. As shown in the last column 2

(to the right) of figure 5, if only half of the motorists that would have parked in the core campus 3

make one trip from campus during the day, the relocated parking is no longer saving Clemson 4

motorists time. 5

6

These findings indicated no significant change in delay, or speeds with the removal of the core 7

campus parking. There was a significant change in the travel times and traffic volumes on 8

several key routes, such as a reduction on Calhoun drive through the core of campus and on 9

facilities turning into to the core of campus from the north. 10

CONCLUSION 11

Pedestrian-friendly campus cores have been goals for many university campuses around the 12

country. Competing concerns of convenient parking and pedestrian safety have not always 13

favored safety. Previous work has continually shown that travel behavior is challenging to alter, 14

at best, and motorists searching for parking can significantly increase the traffic volumes. 15

Removing parking within the core of a university campus might be the most effective method of 16

reducing the number of conflicts between motorists and pedestrians. 17

18

This study used a microscopic, dynamic assignment, traffic simulation model to evaluate the 19

impact of removing core-campus parking spaces at Clemson University, South Carolina. The 20

findings indicated a reduction in network vehicular travel times, likely due to the location of 21

campus parking lots adjacent to arterials at the periphery of campus. Overall, there was no 22

significant change in the total network delay due to the additional walking time required. Instead 23

of frustratingly searching for parking, travelers would enjoy more fresh air if parking was 24

relocated. 25

26

These findings provide justification for the relocation of core-campus parking to periphery 27

parking lots. While safety concerns have always been a motivating factor for this parking 28

change, the findings of this study can provide the extra justification needed to approve such a 29

relocation of parking. Future research can investigate the energy and emissions impacts of 30

relocating parking on university campuses. 31

ACKNOWLEDGEMENT 32

Clemson Parking Services sponsored this study. 33

34


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TABLE 1: Calibrated Volumes Along Key Routes 1

Volumes

Route ID Observed Simulated % Difference

1 1042 1080 4%

2 1141 1151 1%

3 1629 1603 -2%

4 1681 1632 -3%

5 204 207 1%

6 1230 1239 1%

7 1555 1590 2%

8 1395 1347 -3%

9 1786 1745 -2%

10 1255 1257 0%

11 1240 1263 2%

12 1380 1371 -1%

13 1800 1718 -5%

14 926 933 1%

15 741 757 2%

16 623 615 -1%

17 1220 1131 -7%

18 709 696 -2%

19 813 831 2%

20 831 794 -4%

Total 21328 21086 -1%

2

3


12

Table 2: Delay reduction by removing core-campus parking 1

2 3

4

5

6

7

Current ConditionsRemoval of Core Campus

Parking

Average Delay (min) 3862 3035

High 3917 3294

Low 3686 2935

0

500

1000

1500

2000

2500

3000

3500

4000

4500


13

Table 3: Travel Time Comparison 1

2 3

4

Current ConditionsRemoval of Core Campus

Parking

Average Travel Time(min) 20.8 19.7

High (min) 21.4 20.1

Low (min) 20.2 19.3

18.0

18.5

19.0

19.5

20.0

20.5

21.0

21.5

22.0


14

Table 4: Network Delay Estimates Including Increased Walking Times 1

2

Current ConditionsRemoval of Core Campus Parking

Half Core Parkers Leave Campus Once Per Day

Average Delay (min) 3862 3542 4049

High 3917 3801 4308

Low 3686 3442 3948

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000


15

1

2 FIGURE 1 Speed Contour Map Example 3

4


2010 TRB Core Parking Published

Documents

speed contour

rom paper

traffic control

hour midday

traffic simulation

core campus

parking spaces

calhoun drive