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Table 17. Input parameters for simulation scenarios.
Run-Specific Attributes
Treatment Functionality Pedestrians Drivers
(Assume 100% Yield
50 Sighted Pedestrians per 50 Blind Pedestrians per 300 Vehicles
Detection)
Hour Hour per Hour
P(C) P(A) P(R) P(C) P(A) P(R) P(Y)
NC No Information n/a n/a n/a n/a n/a n/a 0%
UA Unassisted Crossing 5 90 5 10 70 20 20%
YS Yield Sign for Drivers 5 90 5 10 70 20 50%
Vehicle Detect for
VD 5 90 5 0 90 10 20%
Pedestrians
Yield Sign and
YSVD 5 90 5 0 90 10 50%
Vehicle Detect
Perfect Information,
PI 0 100 0 0 100 0 100%
Everybody Yields
P(C) Probability of conservative pedestrian crossing behavior. Pedestrian will accept gaps of 12 s or more.
P(A) Probability of average pedestrian crossing behavior. Pedestrian will accept gaps of 6 s or more.
P(R) Probability of risky pedestrian crossing behavior. Pedestrian will accept gaps of 3 s or more.
P(Y) Probability of drivers yielding to pedestrians (percentage of potential yielders).
attributes (Table 17). For illustrative purposes the implemen- gests challenges to estimating the required model input of
tation was tested and executed in the VISSIM simulation potential yielders [P(Y)] from field observations of actual
package (PTV 2005), but the approach should be applicable yielders.
to other simulation tools as well. This sample analysis shows that it is possible to use micro-
It is assumed that the typical pedestrian has a critical lag of simulation models to extract conflict and delay data for
6 s, which is considered safe compared to the actual crossing pedestrianvehicle interaction as a function of run-specific
time of about 5 s at a walking speed of 4 ft/s. Accordingly, con- attributes of the two groups. The approach describes the inter-
servative pedestrians are assigned a longer critical lag value action of the two modes in terms of four probability param-
(12 s) and risky pedestrians have a short critical lag of only eters: the likelihood of crossable gap occurrence [P(G)], the
3 s. The resulting delay and risk measures of effectiveness likelihood of gap detection [P(GD)], the likelihood of driver
(MOEs) from 10 simulation replications per scenario are yielding [P(Y)], and the likelihood of yield detection [P(YD)].
shown in Table 18. From a preliminary analysis, it appears that the delay and
The tables suggest that an increased likelihood of drivers conflict estimates produced by the model in fact follow expec-
yielding (case YS) decreases the percentage of conflicts. Improv- tations. For further information the reader is referred to the
ing VD for pedestrians appears to slightly increase observed paper included in Appendix I.
conflicts compared to the unassisted case. Looking at the large
standard deviations of the risk estimates, it cannot be stated
Simulation-Based Analysis
if this is a real effect at the given sample size. This suggests the
of Signalized Crosswalks
need for large sample sizes in the model repetitions to show
significant effects when evaluating actual treatments. The aforementioned approach for describing pedestrian
In comparison, the delay MOEs suggest that as drivers vehicle interaction in a microsimulation environment applies
yield more, delay for pedestrians decreases while driver delay to all unsignalized crosswalks, where the interaction is gov-
increases. The table also indicates that the percent of actual erned by the four assumed probability parameters. For sig-
driver yields is considerably less than the specified percent of nalized crossings, simulation tools already incorporate algo-
theoretical yielders. This finding is expected at low pedes- rithms to replicate the way real-world traffic signals function
trian volumes since the majority of drivers do not encounter and operate. Consequently, these built-in algorithms should
a pedestrian waiting at the crosswalk. This observation sug- be used when a signalized crosswalk is to be evaluated.
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Table 18. Measures of effectiveness from simulation.
Measures of Effectiveness (Average of 10 VISSIM Runs)
Treatment
Functionality (Assume Actual Driver Pedestrian Risk Pedestrian Risk Pedestrian Vehicle Delay
100% Yield Detection) Yield % Yield Lead, % Lag, % Delay (s) (s)
Avg. Std. Avg. Std. Avg. Std. Avg. Std. Avg. Std.
Dev. Dev. Dev. Dev. Dev.
0.0% 0.00% 27.0% 5.20% 19.3% 2.40% 0.0 0.00 2.4
NC No Control
Unassisted 3.8% 0.99% 2.1% 0.70% 0.5% 0.70% 4.4 0.28 3.1 0.32
UA
Crossing
Yield Sign for 9.3% 1.16% 1.0% 0.80% 0.2% 0.70% 4.1 0.20 4.2 0.29
YS
Drivers
Vehicle 3.7% 0.84% 2.7% 1.40% 0.2% 0.70% 4.3 0.37 3.1 0.27
VD Detect for
Pedestrians
Yield Sign 9.0% 1.33% 1.0% 1.00% 0.2% 0.70% 3.9 0.27 4.2 0.31
YSVD and Vehicle
Detect
Perfect 15.0% 2.00% 0.0% 0.00% 0.0% 0.00% 3.5 0.30 5.4 0.41
Information,
PI
Everybody
Yields
Depending on the specific signal strategy (i.e., a conven- With these considerations in mind, simulation tools can
tional signal versus a pedestrian hybrid beacon), it may be nec- readily be used to estimate the effect of signals on pedestrian
essary to customize the signal control logic to some extent. and vehicle delay. Even without fully capturing the behav-
The analyst should have a thorough understanding of how the ioral aspects related to the signal, a simulation-based analy-
signal is or will be implemented in the field before attempting sis is a great tool for a relative comparison of different signal
to represent it in simulation. Particular attention should be strategies.
paid to whether the signal operates in "free" operation or
whether it is in some way coordinated with other pedestrian
Pedestrian Signals at Roundabouts
signals (two-stage crossing) or with the vehicle signal at the
main intersection (for channelized turn lanes). This section summarizes a detailed sensitivity analysis of
The analyst should further consider whether actual driver pedestrian signalization options for modern roundabouts
and pedestrian behavior is consistent with the way it is intended performed in simulation. The discussion is based on work
by the signal. For example, it was observed at the PHB installa- published in Schroeder et al. (2008), which is included in
tion in this project that some pedestrians crossed before the Appendix L for quick reference.
"Walk" phase came on while others waited until the "Flashing The objective of this sensitivity analysis is to explore the
Don't Walk" before they felt comfortable crossing. In other pedestrian-induced impacts of different signalization strategies
words, pedestrians used the signal as a crossing aid, but by no at modern roundabouts in a simulation environment. The
means as the sole means of determination for stepping into the analysis focuses on six analysis dimensions:
roadway. Similarly, some drivers were observed to proceed
despite a red signal indication. For modeling the vehicular 1. Roundabout geometry: The analysis includes a single-
impact of the PHB signal, it is of particular importance to ade- lane and a two-lane roundabout.
quately represent driver behavior. That signalization strategy is 2. Crosswalk location: The analysis includes three alterna-
intended to result in more efficient vehicle operations by allow- tive crosswalk geometries. The proximal crossing is the stan-
ing drivers to proceed during the "Flashing Red" phase if no dard crosswalk location set back from the circulating lane
pedestrian is in the crosswalk. Clearly, the estimated vehicle by one vehicle length (20 ft). The zigzag configuration
delay for this strategy is principally tied to the level of under- moves the exit portion of the crosswalk to a distance of
standing of and compliance with this phasing scheme. three vehicle lengths (60 ft) from the circulating lane to
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Table 19. Test matrix of treatment combinations The table demonstrates that some of the combinations
(source: Schroeder et al. 2008). were not tested because they were considered impractical. For
example, a two-stage crossing at a single-lane roundabout
Crosswalk Crosswalk Single-Lane Two-Lane
Location Staging Roundabout Roundabout
proximal crosswalk is expected to result in low compliance
Proximal One stage Yes Yes
and therefore wasn't tested. Similarly, a one-stage crossing was
Crossing Two stage No Yes not tested for the zigzag configuration since the elongated
Zigzag One stage No No splitter island provides a natural separation between the two
Crossing Two stage Yes Yes stages of the crossing. For each of the checked cells, the analysis
Distal One stage Yes No considered all combinations of the remaining three dimen-
Crossing Two stage No Yes sions (signalization strategy, vehicle volumes, and pedestrian
volumes). In addition, the analysis included an additional vol-
ume sensitivity that was intended to capture the effect of even
provide additional queue storage on the exit leg. The distal higher pedestrian flows of up to 300 pedestrians/hour. The
crossing location moves the entire crosswalk to a distance analysis used the average results from 10 simulation replica-
of five vehicle lengths (100 ft) from the circulating lane. tions in each scenario. All runs evaluated the effect of one sig-
3. Signal staging: The analysis includes single-stage and two- nalized crosswalk being installed at the busiest approach to the
stage phasing schemes as appropriate. roundabout.
4. Signalization strategy: The analysis includes a conven- The analysis results provide a quantitative comparison of
tional pedestrian signal and a pedestrian hybrid beacon (i.e., different signalization options for pedestrian crossings at
HAWK signal). The analysis assumes full understanding one-lane and two-lane roundabouts, all of which intended to
of and compliance with the signal phases, which is reason- improve access for blind pedestrians. Table 20 highlights a
able for a relative comparison. For an absolute assessment subset of the results for the case of 50 pedestrians/hour cross-
of the delay impact, some variation in behavior should be ing at the signalized two-lane roundabout crosswalk. Results
considered. are shown for below-capacity and at-capacity vehicle vol-
5. Vehicle volumes: The analysis considers a range of vehi- umes. These two-lane roundabout scenarios were selected
cle volumes, categorized as below capacity, at capacity, because they directly relate to the most likely application of
and slightly above capacity. roundabout pedestrian signals. Additional results are pro-
6. Pedestrian volumes: The analysis considers two levels of vided in Appendix L.
pedestrian volumes (10 and 50 pedestrians per hour) rel- The results indicate that innovative signalization treat-
ative to the baseline of no pedestrians. ments, including the PHB and two-stage crossings, can sig-
nificantly decrease vehicle delay. With 50 pedestrians/hour at
Appendix L provides a more detailed description of the dif- the two-lane roundabout, a proximal single-stage pedestrian-
ferent model scenarios. Table 19 summarizes the tested com- actuated signal resulted in pedestrian-induced vehicle delays
binations of the dimensions of roundabout geometry, cross- of 14.2 s per vehicle in the below-capacity scenario and 68.4 s
walk location, and signal staging. for the at-capacity case. The use of a PHB at the same location
Table 20. Sample results of roundabout signalization sensitivity analysis.
Two-lane Roundabout, 50
peds/hour Below Capacity At Capacity
Crosswalk Signal Signal Delay per % Change Delay per % Change
Location Staging Strategy Vehicle (s) over Base Vehicle (s) over Base
Single Ped. signal 14.2 Base 68.4 Base
stage PHB 6.3 56% 39.4 42%
Proximal
Two Ped. signal 4.1 71% 24.4 64%
stage PHB 1.5 89% 5.5 92%
Two Ped. signal 3.9 73% 23.4 66%
Zigzag
stage PHB 1.3 91% 7.0 90%
Two Ped. signal 2.8 80% 5.9 91%
Distal
stage PHB 1.2 92% 0.0* 100%
* This scenario actually resulted in a net decrease of the total roundabout delay, explained by the fact
that the signal was metering demand on a busy approach. Number was limited to a positive range for
this table.
