Daniel I Rubins
Susan Handy
Bicycle Clearance Times: A Case Study of the City of Davis
Daniel I. Rubins
University of California, Davis
Institute of Transportation Studies
Department of Civil and Environmental Engineering
One Shields Avenue
Davis, CA 95616-8762
Phone: 530-752-2570
Fax: 530-752-6572
E-mail: dirubins@ucdavis.edu
Susan Handy
University of California, Davis
Institute of Transportation Studies
Department of Environmental Science and Policy
One Shields Avenue
Davis, CA 95616-8762
Phone: 530-752-5878
Fax: 530-752-3350
E-mail: slhandy@ucdavis.edu
Submitted Date: August 1, 2004
Word Count: 5210
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Daniel I Rubins
Susan Handy
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Abstract
The current state of practice for traffic signal timing does not account for minimum green time or
clearance interval for bicycles. Like pedestrians, bicyclists need sufficient time to cross an
intersection safely. However, this need must be balanced against possible delays for motorist
traffic. Accurate estimates of clearance times for bicyclists are thus essential to the safe and
efficient design of traffic signals. This research project presents data on bicycle clearance times
for different intersection distances near the University of California at Davis Campus and
provides a methodology for measuring bicycle clearance times that other researchers can use. A
total of 10 signalized intersections with varying motor and bicycle traffic volumes were
videotaped for a total of approximately 11 hours. Observed clearance times and calculated
speeds for standing, rolling, and quasi rolling starts are presented in this paper. The importance
of physical design of intersections is also discussed. Important findings are that the clearance
times vary widely for each intersection distance and that the 2nd percentile speeds for each start
type are much slower than the speeds recommended for use in signal design by AASHTO.
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INTRODUCTION
The design of a traffic signal for motor vehicle and bicycle traffic is a trade-off between the
safety of bicyclists and convenience for motor vehicles (1). Like pedestrians, bicyclists need
sufficient time to cross an intersection safely (2). The critical times for bicyclists at signalized
intersections are at the beginning and end of the green periods: a properly designed signal
provides sufficient time for a bicyclist entering an intersection at the end of the green phase and
for a bicyclist starting-up at the beginning of the green phase (3). However, this need must be
balanced against possible delays for motorist traffic: if the green phase is lengthened to
accommodate bicyclists, then the delays for cross traffic may increase. Accurate estimates of
clearance times for bicyclists are thus essential to the safe and efficient design of traffic signals.
Limited guidance and empirical evidence exists for the design of traffic signals to
accommodate bicycles. AASHTO states that 98 percent of bicyclists should be able to clear an
intersection and recommends, in the absence of data on bicyclist speeds, assumptions of 12.7
ft/sec for advanced bicyclists, 12.0 ft/sec for basic bicyclists, and 9.1 ft/sec for children (3).
Several studies consider elements of bicycle clearance time, including comfortable deceleration
and accelerations (4, 5). Other research has shown that the design clearance point is often well
within the limit line, meaning that there is not sufficient clearance time for bicyclist to safely
cross an intersection (4, 6, 7). Dean and Davis note in their review of current bicycle research
that the bicyclist speed distribution studies by Forester (2), Taylor (4), Pein (5), and Opiela et. al.
(8) do not relate bicyclist speed to roadway environment characteristics other than vertical grade
profile. A study by Landis, et. al. uses width of outside lane, intersection distance, volume of
directional traffic and total number of through lanes to determine the perceived hazard of sharedroadway environment through an intersection (9). The Manual of Uniform Traffic Control
Devices (MUTCD) and Highway Capacity Manual (HCM) use motor vehicle equivalents to
incorporate the impedance of bicycle traffic into signal design (10, 11). Allen et. al. highlight the
need for research to quantify the effects of bicycles on the capacity of signalized intersections
(12), a development that would enable the creation of a composite level of service for mixed
flow of intersections and eliminate the use of motor vehicle equivalents for bicyclist (9, 13, 14).
This research project presents data on bicycle clearance times for different intersection
distances near the University of California at Davis Campus and provides a methodology for
measuring bicycle clearance times that other researchers can use. The City of Davis maintains
an integrated system of bike lanes (48.8 miles) and bike paths (49 miles) that serves as the
primary commute mode of transportation for students, faculty and staff living in Davis (15).
Recent city data (1990) indicates bicycles account for approximately 20-25 percent of trips by
city residence (15). The 2000 Census, indicates that 14 percent of Davis residence usually bike
to work (16). The City of Davis has been nationally recognized by the League of American
bicyclist as a “Bicycle Friendly Community” and earned the title of “America’s Best Cycling
City” from the Bicycle Federation of America (15). The City of Davis has also been the subject
of a number of transportation studies beginning in the late 1970s, though none focused on
bicycle clearance times (1, 7, 12, 17, 18). In this project, a total of 10 signalized intersections
with varying motor and bicycle traffic volumes were videotaped for a total of approximately 11
hours. This paper discusses the data collection procedure, results and discussion of
improvements and qualitative observations.
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DATA COLLECTION PROCEDURE
In selecting intersections, we used the following selection criteria, similar to those used in a
study by Opiela, Khasnabis and Datta (8):
 Sufficient bicycle volume.
 A variety of clearance distances.
 An acceptable vantage point for the video recorder (e.g., set back from the intersection).
We identified 14 intersections to be videotaped and ultimately recorded approximately one hour
at each of the 10 signalized intersections near the University of California at Davis Campus. The
observations were made during the morning (7:30-9:30am) and evening (4-6pm) peak periods
using digit video cameras with wide-angle lenses. The weather was mild for all observations and
each intersection had flat approaches. The majority of the observed bicyclists were young adults
because of the proximity of the intersections to the University of California at Davis Campus.
Table 1 summarizes for each intersection the number of observations, range of intersection
distances, range of observed speeds, and distance from campus.
The intersection distance is defined as the distance from the first crosswalk line to the
first line on the other side of the intersection (third line encountered rather than the limit line on
the far side). This definition was chosen because most bicyclists stop at the first crosswalk line
at red lights and because bicyclists are safely out of the path of cross traffic when they cross the
third line. Figure 1 shows an overhead view of the Sycamore and Russell intersection; the
distances of the observed movements and camera location are show as well. Distances for each
movement for each intersection were measured based on intersection diagrams provided by the
City of Davis. For the 10 intersections, distances for through movements ranged from 32 feet to
117 feet while distances for left turn movements ranged from 54 feet to 130 feet. Note that not
all turning movements were observed at all intersections due to obstructions based on the camera
positions at several of the intersections.
To extract clearance times from the videotapes, a team of undergraduate students
manually reviewed the videotapes. Time and resource constraints precluded the use of a
computer-aided video capture and analysis procedure that tracks the vehicle movements and
transforms the positions of vehicles to street coordinates (7). The manual review process
involved manually starting and stopping the videotape for each bicyclist and recording the time
that the bicyclist entered the intersection (crossed the first crosswalk line) and exited the
intersection (crossed into the crosswalk on the far side of the intersection). The process did not
involve dividing the clearance time into acceleration and cruise portions of a bicyclist through an
intersection (5) but did differentiate between three important start types: bicyclists that entered at
full speed were defined as “rolling starts”; bicyclists fully stopped at a red light with at least one
foot on the ground were defined as “standing starts”; and bicyclists stopped at a red light with at
least one foot on the ground several bike lengths from the first crosswalk line were defined as
“quasi starts.” In addition to clearance time and start type, characteristics recorded from the
videotapes included bicycles with trailers, approximate age of bicyclist, and gender of bicyclist.
Special observations about interactions between bicyclists, pedestrians, automobiles and
intersection design were also noted, and most illegal bicycle movements, such as diagonal travel
across the intersection, were excluded from the analysis. Travel speed was calculated for each
observation based on the recorded clearance time and the measured distance for the intersection
movement.
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As a test of the reliability of the method for extracting clearance times from the
videotapes, each student extracted crossing times for the same 10-minute tape sample. This
exercise produced an intraclass correlation coefficient of 0.64 for 9 students and 31 observations,
showing that the clearance times recorded by different students were reasonably consistent.
Probable reasons for differences in recorded clearance times include difficulty in seeing stopping
and starting points and the display of times on the videotape only to the full second with 30
frames per second.
RESULTS
For the overall sample there is a wide variation in speed from the slowest bicyclist at 2.9 ft/sec to
the fastest bicyclist at 33 ft/sec. The slowest observed speed was for a bicyclist who sped up at
the start of the intersection then slowed down on the far side of the intersection in response to the
curb design and a queue of waiting bicycles, illustrating the importance of considering the role of
the roadway environment in determining clearance times. The fastest observed speed was for an
advanced bicyclist on road race bike, illustrating the importance of considering bicyclist ability.
The range of speeds for the entire sample and for each of the ten intersections can be seen in
Figure 2; the grouping of data points at certain speeds for each intersection is an effect of the
rounding of recorded clearance times to full seconds. The descriptive statistics for all
observations and for each start type are summarized in Table 2.
Overall, with outliers, the mean speed is 13.5 ft/sec and the median is 12.5 ft/sec. The
mean is larger than the median because the distribution is skewed to the right (skewness > 0) and
tails are larger than a normal distribution (kurtosis > 0). The relatively small standard error of
the mean, 0.106, generates confidence in the central tendency of the observed speeds. The large
standard deviation, 4.85 ft/sec, and variance, 23.54 ft2/sec2, suggest a broad range for the
observed speeds with 95% of bicyclist falling between 3.79 ft/sec to 23.20 ft/sec. The 85th
percentile for all speed observations is 18.57 ft/sec.
A comparison of mean speeds by start type shows that acceleration for bicyclists is not
instantaneous as is commonly assumed for pedestrians when average speeds of 3-4 ft/sec are
used in signal design (19). Standing starts have the slowest mean, 11.24 ft/sec, while rolling
starts has the fastest mean speed, 16.03 ft/sec. As expected the mean of quasi starts, 11.93 ft/sec,
is slightly faster than for standing starts. Figure 3 shows that the standing and quasi start types
make up a greater share of low speed observations than do rolling starts. The differences
between the mean values for the different start types, including the difference between standing
starts and quasi starts, are statistically significant at the 1 percent significance level. As noted
above, AASHTO states that 98 percent of bicyclists should be able to clear an intersection (3).
For this sample, the 2nd percentile speeds are 5.3 ft/sec, 6.4 ft/sec and 6.7 ft/sec for standing,
rolling, and quasi start type, respectively. These speeds are considerably slower than the
assumed speeds recommended by AASHTO and suggest that longer clearance times should be
used in signal design to ensure that 98 percent of bicyclists will be able to clear an intersection
during the green phase.
The relationship between clearance time and intersection distance was estimated for each
type of start using linear regression. The equations enable an estimation of the expected
clearance time for a given intersection distance for a typical bicyclist and can be interpreted as
consisting of an initial start-up time (the intercept) and an average speed once moving (the
inverse of the coefficient). As the intersection distance increases, the start-up penalty becomes a
smaller portion of the clearance time. Using this interpretation, the average speed for standing
Daniel I Rubins
Susan Handy
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start is 17.7 ft/sec, for rolling start is 23.8 ft/sec, and for quasi start is 12.2 ft/sec, while the time
penalties are 3.1 seconds for standing starts, 2.1 seconds for rolling starts, and 0.5 seconds for
quasi starts. A smaller intercept for quasi starts than rolling starts seem counterintuitive but may
be explained by the few long clearance time outliers for the rolling observations. These
equations were estimated using data for movements between 32 and 139 feet and therefore the
validity of these equations is questionable for smaller or larger movements. For the entire
sample, the adjusted R-square is a modest 0.27; the adjusted R-squares for start types were 0.25
for rolling starts, 0.29 for standing starts, and 0.52 for quasi starts. It is important to note that
there is a large amount of variation in the clearance times for each intersection distance for each
start type.
DISCUSSION
Although the results presented have important limitations and should be replicated through
additional studies, they begin to fill a notable gap in data on bicycle clearance times for
signalized intersections. The data produced in this project can be used to develop guidelines and
estimate clearance times as a function of intersection distance. Given the significant variation in
clearance times, even for a relatively homogeneous sample of bicyclists, a conservative approach
would be to use the 2nd percentile of speed for standing starts of 5.33 ft/sec. Alternatively, the
regression equations presented in this paper can be used to estimate the average clearance time
for an intersection of a specific distance, accounting for the time required for the bicyclist to
accelerate.
Additional research on safely accommodating bicycles in signal design is needed. In this
study, the interaction of the roadway environment on bicyclist was only qualitatively noted.
Future studies should consider the effects of other environmental factors on clearance times:
vehicle flow, lateral bicycle and vehicle lane distances, and the geometric design of the
intersection. In future work, it would be beneficial to use video software to extract the clearance
times with more precision and to differentiate between acceleration and constant speed segments.
In addition, related questions such as helmet use and compliance with traffic control can be
studied using the videotapes produced in this study or in future studies. Such research would
provide an important foundation for improved traffic engineering practice.
ACKNOWLEDGMENTS
This research was supported by a grant from District 6 of the Institute of Transportation
Engineers, through the student chapter data collection project initiated by Randy McCourt, the
President of District 6 of the Institute of Transportation Engineers. Serving as project mentors
were Tim Bustos, Bicycle and Pedestrian Coordinator, City of Davis, Bob Grandy, President of
Grandy & Associates, and David Takemoto-Weerts, Bicycle Program Coordinator, UC Davis.
Sondra Rosenberg, Mike Nicholas, and Chris Congleton provided important oversight of
different phases of the project.
Daniel I Rubins
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REFERENCES
1. Ferrara, T. C., and T. N. Lam. Analysis of Bicycle Delays at Intersections and Crossings
by Computer Simulation. In Transportation Research Record 706, TRB, National
Research Council, 1979, pp. 36-44.
2. Forester, J. Bicycle Transportation: A Handbook for Cycling Transportation Engineers.
2nd ed. Cambridge, Massachusetts: The MIT Press, 1994.
3. American Association of State Highway and Transportation Officials. Guide for the
Development of Bicycle Facilities. AASHTO, U.S. Department of Transportation, 1999.
4. Taylor, D. Analysis of Traffic Signal Clearance Interval Requirements for BicycleAutomobile Mixed Traffic. In Transportation Research Record 1405, TRB, National
Research Council, 1993, pp. 13-20.
5. Pein, W. Bicyclist Performance on a Multiuse Trail. In Transportation Research Record
1578, TRB, National Research Council, 1997, pp. 127-131.
6. Wachtel, A., J. Forester, and D. Pelz. Signal Clearance Timing for Bicyclist. ITE Journal,
Vol. 65, No. 3, 1995, pp. 38-45
7. Raksuntorn, W. and S. I. Khan. Saturation Flow Rate, Start-Up Lost Time, and Capacity
for Bicycles at Signalized Intersection. In Transportation Research Record 1852, TRB,
National Research Council, 2003, pp. 105-113.
8. Opiela, K. S., S. Khasnabis, and T. K. Datta. Determination of the Characteristics of
Bicycle Traffic at Urban Intersections. In Transportation Research Record 743, TRB,
National Research Council, 1980, pp. 30-38.
9. Landis, B. W., et. al. Intersection Level of Service for the Bicycle Through Movement. In
Transportation Research Record 1828, TRB, National Research Council, 2003,
pp. 101-106.
10. Federal Highway Administration. Manual on Uniform Traffic Control Devices: Part 9
Traffic Controls for Bicycle Facilities. FHWA, U.S. Department of Transportation, 2003.
11. Transportation Research Board. Highway Capacity Manual: Chapter 19 Bicycles.
Washington, D.C.: TRB, National Research Council, 2000.
12. Allen, D. et. al. Effect of Bicycles on Capacity of Signalized Intersections. In
Transportation Research Record 1646. TRB, National Research Council, 1998,
pp. 87-95.
13. Taylor, D. and W. J. Davis. Review of Basic Research in Bicycle Traffic Science, Traffic
Operations, and Facility Design. In Transportation Research Record 1674, TRB,
National Research Council, 1999, pp. 102-110.
14. Li, J., Yue, Z. Q., and Wong, S. C., Performance Evaluation of Signalized Urban
Intersections Under Mixed Traffic Conditions by Gray System Theory. Journal of
Transportation Engineering, Vol. 130 No. 1, Jan/Feb 2004, pp. 113-121.
15. Bustos, D. and Ad Hoc Bicycle Task Force. City of Davis Comprehensive Bicycle Plan.
City of Davis, Davis, CA, 2001.
16. U.S. Census Bureau. 2000 Census: Summary File 3. U.S. Census Bureau, Washington
D.C., 2000
17. Homburg, W. S. Capacity of Bus Routes, and of Pedestrian and Bicycle Facilities.
Institute of Transportation Studies, University of California, Berkeley, Feb. 1976.
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18. Ferrara, T. C. A Study of Two-Lane Intersections and Crossings Under Combined Motor
Vehicle and Bicycle Demands. Civil Engineering Department, University of California,
Davis, Dec. 1975.
19. Institute of Transportation Engineers. Traffic Engineering Handbook. 4th ed. Pline, J.L.,
ed. Prentice Hall, New Jersey, 1992.
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LIST OF TABLES AND FIGURES
TABLE 1 Important Intersection Characteristics and Observations.
TABLE 2 Descriptive Statistics of Speed for each Start Type.
FIGURE 1 Overhead View of Sycamore and Russell Intersection.
FIGURE 2 Speed versus Observation Number for each Intersection.
FIGURE 3 Histogram of Speed Frequency of all Observations.
FIGURE 4 Regression of Clearance Times versus Intersection Distance.
FIGURE 5 Regression of Standing Start Clearance Times versus Intersection Distance.
FIGURE 6 Regression of Rolling Start Clearance Times versus Intersection Distance.
FIGURE 7 Regression of Quasi Start Clearance Times versus Intersection Distance.
9
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TABLE 1 Important Intersection Characteristics and Observations.
Street Names (Peak Period)
Time
Recorded
(min)
Cases
(count)
Valid
Cases
(count)
Range of
Speeds
(ft/sec)
257
128
98
44
243
247
80
378
103
389
Range of
Intersection
Distance
(ft)
42-76
66-77
77-105
63-71
88-139
89-139
46-74
90-98
63-102
32-95
6.6-33.0
7.7-25.7
8.1-26.3
7.0-21.0
8.0-29.3
6.7-29.3
22.7-5.1
2.9-30.0
7.0-21.0
2.9-28.3
Distance
from
Campus
Core (miles)
0.29
0.53
0.47
0.77
0.68
0.68
0.79
0.88
1.95
0.56
3rd and B (AM)
3rd and F (PM)
5th and B (PM)
5th and G (AM)
Russell and Anderson (AM)
Russell and Anderson (PM)
Olive and Richard (AM)
Sycamore and Russell (AM)
Sycamore and Covell (AM)
LaRue and Orchard Park
(PM)
LaRue and Hutchinson (AM)
LaRue and Hutchinson (PM)*
*Observations not used
60
48
60
60
60
60
60
60
60
60
291
222
103
51
280
280
97
427
103
412
60
48
139
-----
130
-----
68-70
69-70
5.0-23.3
-----
0.92
0.92
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TABLE 2 Descriptive Statistics of Speed for each Start Type.
Parameter
Total Number of Cases
Valid Number of Cases
Mean (ft/sec)
Median (ft/sec)
Standard Deviation (ft/sec)
Variance (ft2/sec2)
All
2405
2097
13.46
12.50
4.83
23.36
Standing
799
750
11.24
11.00
3.23
10.46
Rolling
1075
910
16.03
16.00
5.37
28.85
Quasi
503
437
11.93
11.82
3.10
9.62
2nd Percentile (ft/sec)
85th Percentile (ft/sec)
Maximum (ft/sec)
Minimum (ft/sec)
95% confidence interval lower bound (ft/sec)
95% confidence interval upper bound (ft/sec)
Skewness (no units)
Kurtosis (no units)
6.40
18.57
33.00
2.91
3.80
23.13
0.931
0.672
5.33
14.17
28.33
2.91
4.77
17.71
0.959
2.581
6.40
22.00
33.00
4.57
5.28
26.77
0.353
-0.434
6.73
15.00
23.75
3.56
5.73
18.13
0.801
1.659
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Sycamore
98ft
N
98ft
96ft
90ft
Russell
Bike Path
C
FIGURE 1 Overhead View of Sycamore and Russell Intersection.
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Speed vs. Observation Number
35
30
Speed (ft/sec)
25
20
15
10
5
0
0
500
1000
1500
2000
Observation Number
Russell and Anderson (PM)
LaRue and Hutchinson (AM)
Russell and Anderson (PM )
3rd and F (PM)
B and 5th (PM)
Olive and Richard (AM)
Sycamore and Covell (AM)
3rd and B (AM)
LaRue and Orchard Park (PM)
G and 5th (AM)
Sycamore and Russell (AM)
FIGURE 2 Speed versus Observation Number for each Intersection.
2500
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Histogram
250
Frequency (count)
200
150
100
50
0
0
2
4
6
8
10
12
14
16
18
20
22
Speed (ft/sec)
Standing
Rolling
Quasi
FIGURE 3 Histogram of Speed Frequency of all Observations.
24
26
28
30
32
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16
y = 0.0563x + 2.0951
R20.2712 =
Clearance Time (sec)
14
12
10
8
6
4
2
0
0
20
40
60
80
100
120
Clearance Distance (ft)
All Clearance Times
Linear (All Clearance Times)
Linear (All Clearance Times)
FIGURE 4 Regression of All Clearance Times versus Intersection Distance.
140
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16
16
14
y = 0.0563x + 3.1251
R20.287 =
Clearance Time (sec)
12
10
8
6
4
2
0
0
20
40
60
80
100
120
140
Clearance Distance (ft)
Standing Clearance Times
Linear (Standing Clearance Times)
FIGURE 5 Regression of Standing Start Clearance Times versus Intersection Distance.
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16
y = 0.042x + 2.0913
R20.2521 =
14
Clearance Time (sec)
12
10
8
6
4
2
0
0
20
40
60
80
100
120
Clearance Distance (ft)
Rolling Clearance Times
Linear (Rolling Clearance Times)
FIGURE 6 Regression of Rolling Start Clearance Times versus Intersection Distance.
140
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18
16
y = 0.0817x + 0.5832
R20.5239 =
14
Clearance Time (sec)
12
10
8
6
4
2
0
0
20
40
60
80
100
120
Clearance Distance (ft)
Quasi Clearance Times
Linear (Quasi Clearance Times)
FIGURE 7 Regression of Quasi Start Clearance Times versus Intersection Distance.
140