“Operational effects of channelized right-turn lanes in urban signalized intersections
for pedestrians and motorized traffic”
By:
José Rafael Unda Venegas
Advisor:
Álvaro Rodríguez Valencia
Universidad de los Andes
School of Engineering
Civil Engineering Department
TABLE OF CONTENTS
Introduction ... 3
Background ... 5
Method ... 9
Intersection’s operational indicator ... 9
Experiment design ... 11
Micro Simulation ... 16
Results ... 18
Pedestrian delay and vehicle delay for different right-turn treatments ... 18
Optimal intersection based on TAD ... 19
Other results ... 20
Conclusions ... 22
INTRODUCTION
For decades, transport planning and engineering focused on vehicular traffic, with the objective of achieving higher speeds and higher vehicle capacity. Banister (2008) states that the conventional paradigm of transport led to the increase of travel distances and travel speeds, which is the base of unsustainable systems of urban transportation, due to its high dependency on motorized traffic. In response, the sustainable mobility paradigm emerged. Transportation is no longer focused exclusively in motorized traffic, but on the contrary, all modes of transportation are hierarchized with pedestrians and cyclists at the top and the car users at the bottom (Banister, 2008). According to the sustainable mobility paradigm, in walkable and multi-modal cities, the design of urban intersections and road networks should be based in multi-modal criteria and in prioritization of pedestrians.
Intersections are a characteristic element of urban networks. Most of the travel delays in urban areas accumulate in intersections and, therefore, it is a topic that has attracted a great portion of traffic engineering research. They are critical points for safety and traffic operation. For transportation engineers and designers to be able to make rational decisions in regard to pedestrian safety at urban intersections, more needs to be known in order to develop better and more coherent design tools.
Traditional urban at-grade signalized intersections are common in urban networks. Channelized right-turn lanes (CRTL) are frequent in intersecions with high right-turning vehicle volumes (Al-kaisy & Roefaro, 2010) and in intersections where the geometry requires larger turning radii. In intersections with no CRTL, turning vehicles need to reduce their travel speed while they
approach to the turn and the speed reduction increases delay for approaching vehicles and reduces the intersection’s capacity. Figure 1 shows the different interaction between pedestrians and right-turning vehicles in a intersection with CRTL and in one with no CRTL (Bogotá, Colombia). CRTL might have also effects on the walking mode, but the operation of pedestrian flows is not frequently considered for deciding its implementation (Al-kaisy & Roefaro, 2010). So far, no research, manual, or guideline was found that provides a tool to make a rational decision of implementing or not a CRTL based on a trade-off between right-turning vehicles and crossing pedestrian delays. A trade-off between crossing pedestrians and right-turning vehicles should be made to improve the service provided for the majority of users.
Figure 1: Left: calle 72 with carrera 11 in Bogotá (no CRTL). Right: calle 72 with carrera 7 in Bogotá (with
CRTL).
Based on controlled simulation experiments I aimed to understand the operational effects of CRTL in signalized intersections for pedestrians and motorized traffic, and thus, develop a method that indicates the best right-turn treatment with the objective of reducing delays for all users. The research was made with particular attention in the inclusion and importance of pedestrians in the intersection’s design. It is proposed an alternative indicator for measuring an intersection’s operation, taking into account the delay of crossing pedestrians and motorized traffic.
BACKGROUND
There is consensus in regard to the operational improvement for motorized traffic in signalized intersections where CRTL have been implemented (e.g. Dixon et. al. (2000), Al-Kaisy and Roefaro (2010), NCHRP (2011)). CRTL allows bigger turn radii, higher turning speeds, and avoids “unnecessary” stops, reducing vehicle delay and increasing the intersection’s capacity. However, high turning speeds have raised the concern in regard to road safety for pedestrian and bicycles (Ling & Li, 2013). Also, in urban areas with high pedestrian and vehicle volumes, operational improvements for vehicles are debatable because pedestrians and vehicle interfere each other and traffic controls end up being included in the channelized lane.
CRTL have been predominantly studied for motorized traffic and typically focused on road safety for motorists, e.g. Dixon, Hibbard, & Nyman (2000), Fitzpatrick & Schneider (2005), Autey, Sayed, & Zaki (2012). Vehicular safety and operation has been widely studied, while no so much is known about pedestrians. The most complete research dealing with CRTL is the design guide of the National Cooperative Highway Research Program (NCHRP) published in 2011. The design issues related to CRTL are presented according to traffic operational and safety considerations for motor vehicles and pedestrians (Potts et al., 2011).
The traffic operational analysis was conducted with micro-simulation models and was focused on three main issues of CRTL: (1) impact of providing CRTL on motorized traffic delay at different traffic vehicular volumes, (2) impact of pedestrians on the delay of right-turn movements and (3) impact of key design features on the operational performance of the CRTL. Some of the most relevant operational considerations included in the NCHRP guide are:
• Intersections with CRTL with yield control reduce right-turn delay to vehicles by 25 to 75
percent in comparison to conventional right turn-lanes. Delay reduction for vehicles is observed up to a pedestrian crossing volume of 200 ped/h.
• A similar delay reduction is observed in CRTL with no traffic control.
• Signalized CRTL produce a similar right-turn delay than conventional right-turn lanes
where right-turn-on-red is permitted. This delay is higher than the one observed for a yield-controlled CRTL.
• “Where a signal is provided for pedestrians to cross a channelized right-turn lane on a cycle
coordinated with the primary signal at the intersection, vehicle delay with the CRTL is generally greater than vehicle delay for conventional right-turn lanes and for yield- controlled channelized right-turn lanes.” (Potts et al., 2011)
For the safety analysis of CRTL, Potts et al. (2011) collected vehicle and pedestrian crash and volume data from 1999 to 2005 for 103 four-leg intersections in Toronto, Ontario, Canada. Three different intersection approaches were compared: (1) shared through/right-turn lane, (2) conventional right-turn lane, and (3) CRTL. The safety considerations that were obtained from this analysis are:
• Motorized traffic safety is very similar between conventional right-turn lanes, shared
through/right-turn lanes and CRTL. This means that there is no evidence that CRTL improve vehicle safety.
• Pedestrian crash frequency is higher (70 to 80 percent) for conventional right-turn lanes
that for shared through/right-turn lanes and CRTL. This might be due to that conventional right-turn lanes produce longer crossing distances.
• CRTL create a refuge island for pedestrians that provides the possibility to cross in two
stages.
• Design agencies are more likely to provide CRTL in intersections with low pedestrian
volumes: “Caution should be exercised in using CRTL where pedestrian crossing volumes are high (i.e., greater than 1,000 ped/day).” (Potts et al., 2011)
• In general, CRTL are not wide, and traffic approaches for a single direction, making it
relatively easy for most pedestrians to cross.
From the considerations presented above, it is clear that CRTL effects on pedestrians are further studied by (Potts et al., 2011) than in other research. Even though, the analysis in regard to pedestrians is limited to cualitaive analysis, while for motorized traffic is technical, accurate and quantified (measured by delay).
Motivated by the lack of guidance in the use of CRTL (specifically in the U.S.), Al-Kaisy and Roefaro (2010) studied the actual reasons why designers consider to choose CRTL in the practice. The methodology was to survey designers from different agencies in the U.S. to know which considerations they took to include a CRTL and to decide which type of traffic control to use in the lane. They found that vehicular traffic operation was the most prevalent consideration for implementing CRTL and that traffic controls are included commonly due to safety considerations (e.g to control pedestrian flows in the CRTL). Another conclusion is that there are poor guidelines to determine wheather a CRTL is convenient or not, and what type of control to use (Al-kaisy & Roefaro, 2010).
Dixon et. al. (2000) in the article “Right-Turn Treatment for Signalized Intersections”, analyze the crash data history of different types of right-turn strategies and configurations of CRTL from Cobb Country, Georgia. The objective was to identify possible correlations between the right-turn treatment and accidenality. Because this study was limited to vehicular safety, no conclusions about pedestrian’s safety are presented, but they found that the inclusion of a triangular island appears to reduce right turn crashes and that exclusive right turn lanes appear to correspond to higher sideswipe crashes (Dixon et. al., 2000).
In relation to safety in intersections with CRTL, equations for speed prediction in the beginning and in the middle of right-turn lanes were established by Fitzpatrick and Schneider (2005). In both equations, the variables that influence the turning speed are: (1) channelization present at site, (2) corner radius, (3) length of right-turn lane and (4) width of right-turn lane at start of right turn. Speed at the right-turn increases with higher corner radius, inclusion of raised islands, and wider lanes. Higher turning speeds represent less safety for pedestrians. Fitzpatrick and Schneider (2005) claim that “…survival rates of pedestrians struck by motor vehicles are much higher if vehicles speed are reduced. Eighty percent of pedestrians are killed when struck by motor vehicles traveling 35 to 45 mph; only 5 percent are killed at speeds of 18 mph.” (Fitzpatrick & Schneider, 2005). In this research they found that in Georgia the configurations with highest crash rates include islands (channelized right-turns). Same as previous research (e.g. Dixon et. al. (2000)), Fitzpatrick and Schneider (2004) didn’t study the effects of traffic in pedestrian operations in the right-turn lanes. They encourage further research in this area.
of CRTL for motorized traffic, but the effect on pedestrians seems to be underestimated. While CRTL might reduce delays for motorized traffic, the effect on pedestrians is unknow. Depending on the type of control, the CRTL may lead to two-stage crossings for pedestrians. That would represent higher overall crossing times, namely higher delays. In addition, the decision of implementing a CRTL lacks guidance. More and better research must be developed for allowing transport engineers and designers to make better decisions that provide more safety and efficiency to all users. This paper studies CRTL with special attention in its effects on pedestrians and proposes an indicator that will help to measure the operation of intersections taking into account the pedestrians that use it.
METHOD
Intersection’s operational indicator
Delay is defined as “the additional travel time experienced by a driver, passenger, pedestrian” (Transportation Research Board, 2000) or the difference between the real travel time (with obstructions, stops, interactions, etc.) and the theoretical travel time with no “interruptions” (“Getting Started : VISSIM,” 2015). Delay is a common indicator for the quantification of an intersection’s level of service for motorized vehicles, but the development of level of service methodologies for other modes led to the use of delay for pedestrians as well. Most recent HCM guidelines provide multi-modal level of service methodologies, allowing interactions between pedestrian LOS model and motorized traffic LOS model, but there is no clear mechanism to find design improvements besides scenario comparison.
pedestrians is not independent (Transport For London, 2010). For example, a traffic signal plan aiming to minimize traffic delay for one mode, might end up increasing the delay for the other mode, and the other way around. Although there is no evidence that the improvement of the delays of one mode will always negatively affect the other mode, it is reasonable to expecrt an influence.
I propose an indicator that combines pedestrian and motorized vehicle traffic delay. The Total Average Delay (TAD) is a weighted arithmetic mean that considers both modes delays equally and is defined as shown in the equation (1).
𝑇𝐴𝐷 =#*'+) - #&'()#&'() ∗ 𝑃𝐴𝐷 +#*'+) - #&'()#*'+) ∗ 𝑉𝐴𝐷 (1)
TAD: Total Average Delay
#peds: number of crossing pedestrians #vehs: number of right-turning vehicles
PAD: Pedestrians Average Delay (per pedestrian) VAD: Vehicles Average Delay (per vehicle)
The TAD is a person-weighted indicator delay of an intersection. As previously mentioned, Pedestrian Average Delay (PAD) and Vehicle Average Delay (VAD) might affect to each other. The principle behind this indicator is that both drivers and pedestrians are equaly importat actors and that the goal is to reduce the overall delay of all actors, and not the delay of a group. In fact, this is the rationale that triggered all the transit signal priority since the 70s in Germany, where the reduction in the dealys of all passengers in buses or trams justifies to modify the signal plan in favor of transit.
Deciding whether a CRTL is convenient or not, based on overall delay minimization is a complex problem. The reason is that many variables stongly affect the delays of each mode separately or
both together. Certainly, geometric design (e.g. CRTL) and the traffic control type influences each mode delay. On the contrary, vehicular demand (or pedestrian demand) influences the traffic signal design (e.g green time and red time) and the combination of green-red times affects the delays in the intersection. Aditionally, road type, number of lanes, turn radii, among others, are variables that also affect delay. But since the objective of this research is to quantify the operational effects of CRTL at signalized intersections, it is necessary that some of those variables that affect delay are remained constant. Variables as lane width, approaching speed, or vehicle composition are easy to held constant because in normal conditions they don’t depend on any of the explanatory variables of the TAD (PAD and VAD). Meanwhile, an intersection’s geometry and signal control are first designed based in the vehicular traffic flow volume. Afterwards, pedestrian’s volumes are accommodated in the previously stablished design, eventually generating changes in phases to accomodate incompatible movements. That means that the geometric and signal design depend on the explanatory variables of the indicator that is being measured. Due to the complexity of the problem, it was necessary to make some simplifications and assumptions to design an experiment that allows to measure and compare the TAD of different right-turn treatments under a series of scenarios of traffic and pedestrian volumes. Using micro simulation, the explanatory variables are systematically varied to measure the effect on the dependent variable (TAD).
Experiment design
I approached the previously presented problem by means of microsimulation using PTV-VISSIM and the specialized module for pedestrian simulation VISWALK. The objective is to evaluate the TAD under the combination of different right turn treatments and different traffic contols for each treatment.
Four different cases of right-turn treatments were evaluated in the experiment. As it can be observed in Figure 2, in each of the cases it was evaluated the pedestrian crosswalk that is parallel to the approaching vehicles’ link and interferes with the right-turning vehicles. Case 1 is of no CRTL, with no right-turn on red. In this case, right turning vehicles yield to pedestrians due to their low turning speed. Case 2 is of CRTL with center crosswalk and traffic control synchronized with the main traffic signal of the intersection. That means that the signal in the channel for the turning vehicles is part of the same signal group of the signal for the non turning vehicles. Case 3 and Case 4 have CRTL with center crosswalk and no signal control in the channel. In Case 3, right-turning vehicles yield to crossing pedestrians. In Case 4 vehicles don’t yield to pedestrians.
Figure 2: Types of right-turn treatments evaluated
For each of the types of right-turn treatments presented in Figure 2, the other explanatory variables (traffic volume and crossing pedestrians) were systematically varied and the behavior of the dependent variables studied (vehicles average delay, pedestrian average delay and TAD). For each of the combinations of crossing pedestrians and traffic volume in each of the types of right-turn treatment, the TAD was calculated, obtaining a three dimensional surface that represents the operation efficiency and capacity of the intersection.
In the experimental design, some assumptions were considered and some variables were held constant. Since many of the analysis are carried out in equivalent vehicles, it was assumed that only cars compose the traffic. Also, given that the conflict between right-turning vehicles and crossing pedestrians is the main source of delay and the main subject of this study, the right-turn proportion of the approaching vehicles was set to a medium-high and constant value of 25%.
Finally, for the experiment, the traffic light cycle and green times were held constant (2-phase signal of 90 seconds with 50/50 split) because, as seen in Figure 3, the VAD for the three traffic volumes evaluated (250, 500 and 750) is very similar. In this way, it is possible to obtain the effects of the geometric design in the delay of pedestrians and vehicles, because the VAD produced by the traffic light with a green time of 45 seconds does not vary between the different approaching traffic volumes evaluated.
Figure 3: VAD for a 90 seconds cycle traffic light and different combinations of green-red times.
Similarly, as shown in Figure 4, the PAD is also very similar between the pedestrian volumes evaluated for a green time of 45 seconds. Due to the characteristics of pedestrian flow (high acceleration and deceleration), when traffic lights turn green, the flow of accumulated pedestrians (whishing to cross) starts almost immediately, regardless of the volume of the pedestrian flow. Because of that, it is expected that with a constant green time, the PAD does not vary between the different pedestrian volumes.
0 20 40 60 80 100 120 140 160 180 200
0 10 20 30 40 50 60 70 80 90
V
ehi
cl
e
A
ve
ra
ge
D
el
ay
(s
)
Green time (s)
Figure 4: PAD for a 90 seconds cycle traffic light and different combinations of green-red times.
It is not necessary to change the traffic light design between scenarios to compare the delays (VAD, PAD and TAD) between them. Further simplifications, assumptions and controlled variables of the experiment are presented in Table 1.
0 20 40 60 80 100 120 140 160 180 200
0 10 20 30 40 50 60 70 80 90
Pe
de
st
ri
an
A
ve
ra
ge
D
el
ay
(s
)
Green time (s)
Table 1: Simplifications and controlled variables of the traffic simulation experiment
Simplifications/Assumptions Condition(s)
Signal 2-phase signal of 90 secs with 50/50 split
Lane width 3.6 m
Vehicle approach speed 50 km/h (30mph) Vehicle composition 100% cars Conflict areas Red/Red Pedestrians direction 50/50
Turn radius 5 m when no CRTL and 15 m when CRTL Peds walking behavior Social force model (Viswalk default) Vehs turning speed 15km/h (no CRTL) and 30km/h (CRTL) Right-turn proportion 25%
Controlled Range
Geometric design (4)
No channelized right-turn lane (Case 1)
Channelized right-turn lane with signal control (Case 2)
Channelized right-turn lane with no signal control, vehicles yield to pedestrians (Case 3) Channelized right-turn lane with no signal control, vehicles don’t yield pedestrians (Case 4) Traffic volume (3) 250-500-750
Pedestrian volume (4) 100-250-500-750
Micro Simulation
The systematic variation of motorized traffic volume and parallel pedestrian volume under the four different types of right-turn treatments result in a total of 48 scenarios. I adopted the micro simulation software VISSIM and its complement VISWALK to run the simulations to calculate the TAD using the Equation (1). Since the experiment is done in generic intersections, there are three procedures that are necessary for designing the simulation process: the determination of the simulation time, the warming-up period and the number of runs (R).
simulation runs, the network starts to receive vehicles and other simulation inputs. Since in reality vehicles do not start flowing in a moment, it is necessary to leave a warming-up period, when all the inputs are in the network but no results are being evaluated. The warming-up period is usually of 15 minutes, but there are methods to calculate it for each particular simulation model. It depends essentially of the network size (Transport For London, 2010). Because the simulation consisted of a single intersection the network was small and a warming-up period of 15 minutes (900 seconds) was enough. After the warming-up period, the network stabilizes and the measures obtain are more presentative of reality. The period of time obtaining information from the simulation was determined as one (1) hour (3600 seconds), so in total the simulation lasts 4500 seconds with the warming-up period.
The micro simulation models have a stochastic component that allows taking into account the randomness of traffic variables. That means that running each scenario ones is not enough to conclude anything, because running it again would probably result in different values. A number of repetitive runs minimizes variability according to the confidence (interval) and percentage error allowed by the modeler. (Hollander & Liu, 2008) present a formula for calculating the number of runs:
𝑅 = ).4∝/7
8.9 :
(2)
R: required number of runs
s: standard deviation of the examined traffic measure x: mean of the traffic measure
ε: the required accuracy, as a fraction of x
t∝/2: critical value of Student’s t-test at confidence level ∝
5%, after three iterations R converge to 9 runs. Every scenario was run 9 times.
RESULTS
Pedestrian delay and vehicle delay for different right-turn treatments
Figure 5: PAD and VAD with constant vehicle traffic (750 vehs/h) while pedestrian volume is varied
0 5 10 15 20 25 30 35 40 45 50
0 100 200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Crossing pedestrian volume (peds/h) Case 1 0 5 10 15 20 25 30 35 40 45 50
0 100 200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Crossing pedestrian volume (peds/h) Case 2 0 5 10 15 20 25 30 35 40 45 50
0 100 200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Crossing pedestrian volume (peds/h) Case 3 0 5 10 15 20 25 30 35 40 45 50
0 100 200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Crossing pedestrian volume (peds/h) Case 4
Figure 6: PAD and VAD with constant crossing pedestrians volume (750 peds/h) while traffic volume is varied
Optimal intersection based on TAD
Table 2: Optimal right-turn treatment between Case 1, 2, 3 and 4 based on TAD
Optimal right-turn treatment based on TAD
Traffic volume aproching the intersection (vehs/h)
250 500 750
Cr os si n g p ed es tr ia n vol u m e (p ed s/ h
) 100 Case 3/Case 4 Case 3/Case 4 Case 3/Case 4
250 Case 3/Case 4 Case 3/Case 4 Case 3/Case 4
500 Case 3/Case 4 Case 3/Case 4 Case 3/Case 4
750 Case 1 Case 3/Case 4 Case 3/Case 4
0 5 10 15 20 25 30 35 40 45 50
200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Traffic volume aproaching the intersection (vehs/h)
Case 1 0 5 10 15 20 25 30 35 40 45 50
200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Traffic volume aproaching the intersection (vehs/h)
Case 2 0 5 10 15 20 25 30 35 40 45 50
200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Traffic volume aproaching the intersection (vehs/h)
Case 3 0 5 10 15 20 25 30 35 40 45 50
200 300 400 500 600 700 800
A ve ra ge de la y (s ec onds )
Traffic volume aproaching the intersection (vehs/h)
Other results
The operational analysis developed with VISSIM and VISWALK, that allowed to estimate de Vehicle Average Delay (VAD), the Pedestrian Average Delay (PAD) and the Total Average Delay (TAD), led to the following results about channelized right-turn lanes (CRTL) in urban signalized intersections:
• When there is no CRTL, pedestrians delay and vehicles delay are not independent. The
conflict between right-turning vehicles and crossing pedestrians causes that the decrease of one’s delay generates the increase of the other’s delay. In Figure 5 it can be observed that when ther is no CRTL (Case 1) the VAD increases considerable with the increase of the pedestrian volume crossing the intersection. This is due to the priority of the pedestrian volume in the conflict with turning vehicles. When the pedestrian volume increases, it becomes difficult for the turning vehicles to find a gap between pedestrians and the VAD increases as seen in Figure 5.
• In a similar way, in intersections whith no CRTL (Case 1) and high pedestrian volume,
when vehicle volume increases, the VAD increases considerably but the PAD maintains constant, as seen in Figure 6.
• With no CRTL (Case 1) it is easier for pedestrians to find a gap between vehicles that for
vehicles to find a gap between pedestrians. When pedestrians have priority and vehicles turn at low speeds, the VAD increases considerably with the incrementation of the pedestrian volume (Figure 5). Meanwhile, in the same case, the PAD does not increase considerable with the incrementation of the traffic volume (Figure 6).
• The case with no CRTL (Case 1) is the right-turn treatment that produces less PAD for all
of the scenarios simulated. The case with CRTL, no signal control and priority for vehicles (Case 4) is the righ-turn treatment that produces less VAD.
• CRTL increase pedestrian delay and decreases vehicles delay. All the right-turn treatments
with CRTL (Case 2, 3 and 4) increase the PAD and reduces the VAD for every evaluated scenario in comparison to no CRTL (Case 1). That means that if the operational indicator of an intersection was exclusively the PAD, the optimal right-turn treatment will always be with no CRTL (Case 1). Instead, if only the VAD was take into account, Case 1 will always be the worst right-turn treatment on terms of operation for motorized traffic.
• In intersections with CRTL with signal control (Case 2), the signal control determines in
great measure the delay for pedestrians and vehicles. In Figure 5 and Figure 6 is shown that in Case 2 the PAD and VAD varies slightly when traffic volume or pedestrian volume are increased. That also proves that a traffic signal desigened to benefit one mode might result in the magnification of the delay for the other mode.
• It was proved that CRTL with signal control (Case 2) is the case of greatest PAD, because
when there is a signal control in the channel, pedestrians cannot cross the intersection in one phase. They have to cross in two phases, increasing the PAD up to 235% in
comparison to no CRTL (Case 1).
• The PAD, VAD and TAD for Case 3 and Case 4 are very similar for equivalent scenarios.
It can be observed in Figure 5 and Figure 6 that VAD and PAD vary in a very similar way for Case 3 and Case 4. These two right-turn treatments have very similar operation for motorized traffic and pedestrians.
• As seen in Table 2, no CRTL (Case 1) is the right-turn treatment with less TAD in the
scenario of lowest traffic volume and highest pedestrian volume. CRTL with no signal control (Case 3 and Case 4) is the right-turn treatment with less TAD in the majority of scenarios simulated.
CONCLUSIONS
CRTL in urban signalized intersections have effects for both vehicle and pedestrian. Due to its characteristics, the pedestrian delay is quite constant in the variation of pedestrian volume, but there are measurable differences between right-turn treatments with and without CRTL. I confirmed that CRTL improve delays for vehicles but also have effects on pedestrian flows that should be considered. The Total Average Delay (TAD) is an alternative indicator that considers in equality vehicles and pedestrians, allowing to make a trade-off between them and to select the best right-turn treatment for the majority of users.
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