International Journal of Traffic and Transportation Engineering
p-ISSN: 2325-0062 e-ISSN: 2325-0070
2020; 9(2): 25-36
doi:10.5923/j.ijtte.20200902.01

Nikolay Nazaryan, F. Clara Fang
Department of Civil, Environmental and Biomedical Engineering, College of Engineering, Technology and Architecture, University of Hartford, West Hartford, CT, USA
Correspondence to: F. Clara Fang, Department of Civil, Environmental and Biomedical Engineering, College of Engineering, Technology and Architecture, University of Hartford, West Hartford, CT, USA.
| Email: | ![]() |
Copyright © 2020 The Author(s). Published by Scientific & Academic Publishing.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/

This paper reports about an investigation of the effect of the length of an additional approaching lane of a roundabout on the delay. To calculate delay, a mathematical algorithm has been developed, representing dependence of velocity
a traveling vehicle on its traveling distance
The study shows a mathematical algorithm which can supply more accurate and simpler calculations, represented through the sixth-degree polynomial function possessing just three extrema points: a maximum and two minimums. It is shown that application of data collection on existing additional lanes, performed during different periods of time during weekdays will allow us to obtain the family of curves
, where each curve will have its own individual extrema points with the consequent coordinates
and
These curves, obtained on the base of the analytical function and the practical data collection, will allow road engineering experts to design a roundabout’s additional approaching lane and to estimate the proper delay with the very high degree of accuracy.
Keywords: Roundabout geometry, Delay, Mathematical algorithm, Velocity, Traveling distance, Sixth-degree polynomial function, Extrema points, Family of curves
Cite this paper: Nikolay Nazaryan, F. Clara Fang, Quantify the Relationship Between Roundabout Geometry and Delay, International Journal of Traffic and Transportation Engineering, Vol. 9 No. 2, 2020, pp. 25-36. doi: 10.5923/j.ijtte.20200902.01.
ratio to approach or exceed 1.00. Under such conditions, long queues form, and delay increases at roundabouts. Such conditions require modifications to improve performance. Earlier research on roundabout operation was conducted by the United Kingdom–based Transport and Road Research Laboratory (TRRL), where numerous experiments and observations were performed on existing roundabouts. Kimber incorporated findings from the TRRL studies and identified six geometric parameters as having a significant effect on capacity: entry width, approach half-width, effective flare length, flare sharpness, inscribed circle diameter, and entry radius [4,5]. Out of the six parameters, entry width, approach width, and flare length were determined to be the most relevant with regard to capacity.The approach width, typically 12 feet in the United States, is the width of the travelled way in advance of any entry flare; the entry width is the width of the travelled way at the point of entry. FHWA identifies the entry width as the “largest determinant of a roundabout’s capacity” [3]. NCHRP recommends an entry width of 24 to 30 feet for two-lane entry and 36 to 45 feet for three-lane entry. It does not, however, specify how far back the additional lane or flaring should begin. In Europe, where flaring design is more common than an additional lane design, the U.K. Department of Transport Design Manual recommends flare lengths of about 82 feet (25 meters) for widening to effectively increase capacity [6]. Flare lengths greater than about 328 feet (100 meters) result in higher speeds, which undermines the main purpose of the modern roundabout configuration. The configuration of a modern roundabout reduces driver approach speeds to improve safety and enhance traffic flow. Therefore, when increasingly long lane lengths are used, the safety benefit of roundabouts may be forfeited. The 82-foot recommendation by the U.K. Department of Transport Design Manual has not been tested in the United States, but some state agencies follow the overseas guidelines, since data on the additional lane or flare length have not been provided. Interim requirements and guidance on roundabouts by the New York Department of Transportation suggest a flare length of 41 feet (12.5 meters) to 328 feet (100 meters) for urban areas and 66 feet (20 meters) to 325 feet (100 meters) for rural areas [7]. The FHWA used a model developed by Wu [7] in determining the capacity of a roundabout, whereby short length widening at the approach is considered [3,8]. Wu estimated the capacity of an unsignalized crossroad and T-junction intersection by taking into account the length of the turn lanes. Wu later analysed this model at a roundabout intersection and introduced an enhancement/correction factor for determining the capacity of a double-lane entry at a roundabout [9]. Wu was able to identify the effect of entry length, but the effect of the additional lane length at the exit was not mentioned, and it was assumed that the capacities of both lanes were identical and the traffic flow in both lanes at the entry was equally distributed. However, studies conducted on some double-lane roundabouts in the United States show that the right lane is utilized more frequently than the left lane and thus is usually considered to be the critical lane. For instance, one of the double-lane roundabouts in Brattleboro, Vermont, showed that the right lane had about 70 percent of the entry total flow, so capacity in the Wu model appears to have been overestimated [10]. This research examines the effect of the flare/additional lane length on roundabout operation using typical U.S. driving behaviour, where the right lane is considered the critical lane and is utilized more frequently than the left lane. In order to model typical U.S. driving behaviour, VISSIM was used for analysis purposes. VISSIM is a microsimulation software from Germany in which vehicles are modelled using parameters such as driver behaviour, vehicle speeds, and vehicle type [11]. VISSIM has the ability to control gaps and headways on a lane-by-lane basis to accurately replicate vehicle operations at roundabouts. Numerous studies have used VISSIM microsimulations to examine roundabout performance due to their unique ability to mimic real-world traffic operations. Trueblood and Dale considered VISSIM to be a very effective microsimulation software package for roundabout performance analysis and used VISSIM to model existing roundabouts in the state of Missouri [12].Bared and Afshar used VISSIM to model roundabouts for various ranges of circulating and entry traffic volumes [13]. They found that simulation results from VISSIM matched field data more closely than those from the SIDRA analytical and RODEL empirical models. The additional lane lengths that were analysed in VISSIM for both scenarios included 0 feet, 150 feet, 250 feet, 350 feet, 450 feet, and 550 feet. The VISSIM lane closure feature was utilized to make the zero-foot length possible. While reducing the exit and entry lanes on a double-lane roundabout to a single lane is not practical, and study in [14] illustrated that the extent of the delay effects up to zero feet.![]() | Figure 1. The diagram of roundabout with the additional lane length of L |
of vehicle versus to vehicle’s traveling distance
are shown on Figures 2 and 3. ![]() | Figure 2. The diagram of speed of a vehicle when it enters a roundabout without stopping at the “Yield” sign |
![]() | Figure 3. The diagram of speed of a vehicle when before entering a roundabout it stops behind the “Yield” sign |
and
consequently and a maximum in point
and it must satisfy to the first order and first degree differential equation having the following general form: ![]() | (1) |
and
have to be positive
and
and relationship between
and
must be as that the radical of expression
has to be negative, that is
Integration of this differential equation will give the sixth-degree polynomial function, having the following general form: ![]() | (2) |

Because for
the speed of vehicles is
, so constant F in equation (2) will have the value
Therefore equation (2) will obtain the form: ![]() | (3) |
in this function also must be positive
and this function cannot be negative for any values of
. Based on these conditions as well as on some other additional (initial) conditions, the coefficients
and
of function (3) can be found. Using the system of two equation containing the function (3) and its derivative will allow to solve this problem:![]() | (4) |
![]() | (5) |
and
here some other additional conditions must be used. In our solving problem these additional conditions are interpreted clearly on the diagram, presented on Figure 3. From this diagram it is shown that when vehicle’s traveling distance is
then speed of vehicle approaches to its maximum value
and consequently the rate of changing of speed at that point is
Besides that, when a vehicle travels the distance
then it stops behind all of vehicles, queening before “Yield” sign. Obviously that location of the stopping spot
depends on the capacity of the additional lane and it may be relatively close to the entry of that lane or next to the “Yield” sign. Here also for
vehicle’s speed as well as its rate of changing in respect to
become zero, that is
and
The value of distance when speed of a vehicle again becomes equal to the initial speed
will be denoted as
However, this traveling distance can be approximated with very high accuracy as the double of distance
that is
Graphically it implies that coordinate
is located approximately in the midpoint between
and
This kind of approximation is equivalent to the consideration that in the interval
the behavior of the curve
similar to the second order parabolic function. Applying actual field measurements (for 15 min, half an hour, etc.) of traffic flows in the additional lanes of currently existing roundabouts will allow to perform field data collections to design traffic performance models. These observations, performed on the base of certain conditions, can be used for obtaining statistical dependencies between
and
that is, for finding dependence
and
Analogously there can be found statistical dependencies between
and
, that is
. Thus, parameters
and
should have statistical interpretation, based on field data collections. If for the given period of time there have been performed
field measurements then these parameters can be considered as the mean statistical for that period of time, that is
Obviously, that statistical values of q, r, v and c will strongly depend on the observation period of time, performing during the entire weekday. Mainly the observation periods of week.0day time include early morning, noon (before and after) and early evening. Based on above characterizations of these coefficients they practical values (approximately) can be considered to be laid in the following ranges: 
and
where
is the speed limit on the additional lane, having values
On the base of equations (4) and (5) and above-mentioned conditions a system of equation will be found, satisfying these conditions.![]() | (6) |
and is
belonging to this system of equation can be found as: where

Hence, on the base of above calculations the coefficient
and
will depend on from
and
as well as from the statically observed coefficients
that is:
Determining all above coefficients will allow us to find the final version of the general form of the equation (3) representing speed
of a vehicle verses to its traveling distance
. Therefore definition of coefficients in equation (3) shows that for the given length of the additional lane
and for the given value of the initial speed
the current value of speed
will depend on from
and
as well as from the statistically observed values of
and
Consequently, for the given values of
and
and for different values of statistically defined coefficients
and
here could be obtained whole family of diagrams, illustrated on Figure 4.![]() | Figure 4. The family of the analytical diagrams of speed of the vehicles that may take place during the weekday |
from their traveling distance
Moreover, for the given values of
and as well as for the reasonably chosen values of coefficients
and
here can be obtained the similar families of the curves, based just on analytical reasoning. Obviously, that this kind of analytical curves also may have large practical applications in roundabouts entry/exit lines designing. Thus, due to relatedly very short distance of the additional lane and based on this circumstance short-term acceleration-deceleration driving regime of vehicles the dependents of vehicles’ velocity
from their traveling way
can be represented through the sixth-degree polynomial function. Therefore, our derived mathematical algorithm will allow roundabout development specialists to find the delay of the vehicles in the availability of the additional entry lane easily. Here it must be noted that currently the HCM only includes control delay, the delay attributable to the control device. The control delay is the necessary time that a driver spends decelerating to a queue, queueing and then waiting for an acceptable gap in the circulating flow while at the front of the queue and accelerating out of the queue. According to our proposed algorithm of kinematics here the current value of braking distance of a vehicle can be found as a difference between the current values of distances
and
As it shown above these distances corresponding to the minimum
and the maximum
values of the speed: ![]() | (7) |
measurements than statistical average braking distance for that period can be calculated as:![]() | (8) |
![]() | (9) |
![]() | (10) |
braking distance (m ≈10, m≈3.28 ft)
breaking speed (km/h≈3280 ft/h),
acceleration due to gravity (9.81 m/s2≈32.12 ft/s²),
mean coefficient of friction,
roadway grade
the declaration of vehiclesThe declaration adc of vehicles is defined as:![]() | (11) |
![]() | (12) |
vehicle, which is required by the National Cooperative Highway Research Program [2]. The point is that HCM for calculations very often recommends using the 95%-percentile vehicle queue length, applied for a given approaching lane. Authors in [39,40] show how the 95th-percentile queue length varies with the degree of saturation of an approach: ![]() | (13) |
= 95th-percetile queue, veh;
flow rate for moment x; veh/h;
capacity of moment x, veh/h;
analysis time period, h (T=1 for a 1-h analysis,
0.25 for a 15-min analysis);
volume-to-capacity ratio.The volume-to capacity ratio is a comparison of the demand at the roundabout entry to the capacity of the entry and provides a direct assessment of the sufficiency of a given design. For the given lane, that ratio is calculated by dividing the lane’s calculated capacity into its demand flow rate. While the HCM does not define a standard for that ratio, international and domestic experience suggests that value ot that ratio falling in the range 0.85 to 0.90 represents an approximate threshhold for satisfactory operation.Because the capacity of vehicles is one of the key parameters of traffic operations, there are many publications dedicated to this matter. However, Lee Rodegerdts [41] showed U.S.A. universal roundabout capacity model (capacity of moment x) as a function of the circulating flow on the roundabout, follow-up headway, and critical gap through the following general equation. ![]() | (14) |
approach capacity, (veh/h),
circulating flow rate, (veh/h)
critical gap, (sec)
follow-up time, (sec) This equation estimates the capacity of a roundabout’s approach (entry lanes) via input parameters such as circulating conflicting traffic volume
follow-up time
and critical gap
However, earlier studies by Hagring (1996, 1998) found that the critical gap differs between the two entering lanes at a two-lane roundabout. The studies also found that right-turning vehicles in the outer entry lane had significantly smaller critical gaps than those of other turning movements at the same approach. Critical gaps were found to be very similar regardless of which of the two circulating lanes vehicles were entering and it was therefore concluded that both circulating streams impede entering vehicles. Hagring [36,37] related critical gap to the size of the weaving area between two adjacent roundabout approaches with the following equation:![]() | (15) |
= critical gap;
= length of weaving section;
= width of weaving section;
= lane number (outer lane = 1, inner = 2). The circulated flow is calculated for each leg, and the circulating volumes are the sum of all volumes that will conflict with entering vehicles on the subject approach.The average breaking time of
vehicle is the time that a driver spends decelerating to a queue. Using formulas (8) and (9) we will find vehicle’s average breaking time: ![]() | (16) |
vehicle. Application of currently existing high-resolution time-distance measuring video devices (especially designed for queue detectors) will allow roundabout development specialists to solve this problem. Obviously, that before
vehicle there will be a queue with the
vehicles, and video devices will be able to measure each
vehicle’s length
and its gap
We also should mention that average lengths of vehicles are distributed by the lengths of passenger cars, light and heavy vehicles. According to American HCM, as a single unit a car, taxi or pickup is used for expressing transportation flow capacity. Cycle and motorcycle are considered as half a car unit. Buses and trucks are considered as 3 care units. Horse-drawn are 4 units, bullock carts 6 units and large bullock cart 8 units. Hence, the length of queue measures in foots or meters, so the length of
vehicles with their gaps can be expressed as: ![]() | (17) |
is the total number of vehicles in queue, defined by formula (17). However, in [3] it is considered the average queue length or number of vehicles (
vehicles) which can be calculated by Little’s rule: ![]() | (18) |
= entry flow, veh/h; d = average delay, seconds/veh Now let us consider that queue detection technology shows that total merging time of
vehicles with the roundabout circulating traffic is
Hence, in that period of time
vehicle will reach to the end of additional lane or to the “Yield” sign. That time will be considered as a queening time of
vehicle, and its average speed in queuing will be defined as: ![]() | (19) |
counts the time for all of
vehicles, when each of them has to wait for an acceptable gap (sec) to be merged with the circulating flow of roundabout. Obviously that field data collection service will show those waiting times, and they must be differed for each Jth vehicle. So, the total waiting time for al
can be expressed as![]() | (20) |
is the waiting time of the
vehicle. After queueing, the
vehicle will wait for an acceptable gap at the front of queue in order to accelerate and exit the queue. Let as consider that the detected value of waiting time of that vehicle is twQ If the length of
vehicle is lQ then it has to accelerate such way that in the end of the merging cycle it has to be completely located in the circular lane of the roundabout. The speed of that vehicle must be equal (at least) to the roundabout’s circulating speed, showing significant contribution in the merging of vehicles. In [35] it is shown that speed-radius relationship can be calculated by the following formula: ![]() | (21) |
circulating speed (mi/h)
aaverage radius of circulating path of through movement (ft). Radius
can be computed with the equation ![]() | (22) |
inscribed circle diameter (ft)
number of circulating lane(s)
average width of circulating lane(s) (ft). However, because the speed of vehicles associated with
can’t remain constant for all of periods of time during the observation, we came up to the conclusion that equation (18) can be modified to obtain the following form: ![]() | (23) |
is considered as statistical variable, which can be derived from the observation, completed for the given period of time. The value of
may lies in the interval,
where
will respond for the minimum value of speed and the
for the maximum. Obviously, that merging cycle must end at least during the critical gap
defined by equation (15). Based on these circumstances the acceleration could be found as: ![]() | (24) |
vehicle can be estimated as: ![]() | (25) |
vehicle, that is
Thus, we have considered all of components of the control delay of
vehicle. They are: the time that a driver spends decelerating to a queue
queueing time
waiting time
for an acceptable gap in the circulating flow, and the time
needed for accelerating and to be out of the queue. Consequently, according to definition of control delay we can confirm that the sum all of these time intervals is equivalent to the such control delay when an additional lane is considered, that is:![]() | (26) |
due to this lane will be less than the control delay
of the original single lane. Delay
expressed by the well-known formula, represented in [3]: ![]() | (27) |
flow rate for movement x, veh/h
capacity of movement x, veh/h
analysis time period,
for a 15-minute period)
volume-to-capacity ratio Obviously, that in result of adding a lane the ratio
must be less than one (1), that is: ![]() | (28) |
![]() | (29) |
represents the desirable or expectable gain of delay, and
is considered as the control delay of the single-entry lane roundabout. From the above calculations of time components
and
and also from definition of the control delay
it can be seen that formula (26) commonly associated with many of parameters of roundabout, such as its additional lane length
the length of queue
circulating speed
average radius
of circulating path, critical gap
approaching capacity
circulating flow rate
and control delay
of the single-entry lane. Definition of all these parameters are given above. Therefore, for the given values of
and
the value of coefficient
will depend on the length of the additional lane
Application of modern technology of data collection as well as computer modeling of formula (26) will allow to find very accurate graphical dependencies of Coefficient
and delay
from the additional entry lane length
Thus, our proposed method will allow us to find the dependence of vehicles’ velocities
from their traveling distance
and this method will allow to find the delay due to the length
of the additional lane. Despite of the method outlined in [16] where for consideration of operational performance of a double-lane roundabout with additional lane length design have been used and analyzed quite complex and inconvenient Lighthill-Whitham-Richards mathematical model, our proposed method is simple and understandable, it is effective and accurate, and considering those advantages it can achieve promising results. Any roundabout design specialist can use our method without demanding significant or specialized expertise in kinematics and mathematical analysis.