saturation flow at traffic signal using transyt: a case study in

Saturation Flow at Traffic Signal Using TRANSYT: A Case Study in Johor Bahru, Malaysia

ARASH MORADKHANI ROSHANDEH

Department of Geotechnics and Transportation Universiti Teknologi Malaysia

81310, Skudai, Johor MALAYSIA

[email protected]

Abstract: - The study was done at Jalan Pendidikan – Jalan Perdagangan, Taman Universiti, Skudai in Malaysia. The purpose of the study is to evaluate the performance and efficiency of traffic signal setting at signalized intersection. This study only involves traffic count, actual green and saturation flow rate measurement data during the survey. The data from the site then being analyzed, using manual calculation and computer programs TRANSYT 13. As a result the test signalized intersection has acceptable headway, saturation and lost time. The major arm of the intersection has LOS C while minor arm has LOS D, which was still acceptable. The existing traffic demand is still less than the intersection capacity, which means that the flow in this intersection is not oversaturated yet. Therefore, no upgrading is needed for this intersection. Key-Words: - Traffic signal; Actual green; Saturation flow; Cycle time; Level of service 1 Introduction The study was done at Jalan Pendidikan – Jalan Perdagangan, Taman Universiti, Skudai. Taman Universiti is a university town near Johor Bahru City in Malaysia. It is located between Skudai and Pulai. It was given town status in 2002. Universiti Teknologi Malaysia (UTM) is 5 minute drive away from Taman Universiti, hence the name of the town. The town is dominated by lecturers, office workers and students from UTM. There are ten main areas in Taman Universiti, with each area are labeled with a name Pertanian, Penyiaran, Perubatan, Perdagangan, Kebangsaan, Kejayaan, Kebudayaan, Kemajuan, Kemuliaan, and Pendidikan. Taman Universiti is a small place consists of shops, banks, restaurants, shopping complex and residential [1].

Since it is a strategic place between residential areas and business areas, it is expected to have an increase of traffic level. Jalan Pendidikan is a major road with many intersections. There are three signalized intersections at the site, which are Jalan Universiti‐Jalan Pendidikan, Jalan Pendidikan‐ Jalan Perdagangan and Jalan Perdagangan‐Jusco entrance. The distance between first and second intersections is around 300m while distance between second and third intersections is around 100 m.

The short distance between those intersections make those intersections to be not isolated to each other. Another point is short distance between those two intersections contributes to vehicle queuing. The existence of shopping complex, JUSCO, near the intersection did influence to increase the flow at the test

signalized intersection. Jalan Pendidikan is a major roadway that connects Jalan Universiti to run through Taman Universiti. It serves as the main connection which flows more than 10000 vehicles per day. It forms the backbone of the town’s road system. The existence of intersections along the roadway has greatly influenced the traffic flow desiring to access to Taman Universiti. Traffic queues onto the roadway are a common occurrence during peak hour periods.

The assessment or evaluation for the road and intersection improvements need to be done since the increasing traffic demand on Jalan Pendidikan and that intersection will only worsen the congestion currently present during peak period. Besides, the evaluation of the signal setting on that intersection is needed to ensure that it can serve the traffic demand smoothly. 1.1 Aim and Objectives of Study The purpose of the study is to evaluate the performance and efficiency of traffic signal setting at signalized intersection of Jalan Pendidikan – Jalan Perdagangan at Taman Universiti, Skudai. The main objectives of the study are determination of saturation headway, flow and lost time at the specified signalized intersection; estimation of delay and queue at the specified signalized intersection; determination of reserve capacity and level of service (LOS) of the specified signalized intersection; and determination of optimization settings of the specified signalized intersection using TRANSYT 13 software.

SENSORS, SIGNALS, VISUALIZATION, IMAGING, SIMULATION AND MATERIALS

ISSN: 1790-5117 167 ISBN: 978-960-474-135-9

1.2 Study Area The study area is at the signalized intersection of Jalan Pendidikan‐Jalan Perdagangan, Skudai. This intersection was selected since it is the intermediate intersections that located along main road through Taman Universiti. Besides, the intersections also located along the main road between offices, shops and shopping complex to residential areas.

One intersection was selected located in Taman Universiti for the collection of data. The geometry measurement of the road and other general site description was not being noted. 2 Methodology This study only involves traffic count, actual green and saturation flow rate measurement data during the survey. The data from the site then being analyzed, using manual calculation and computer programs TRANSYT 13.

The data were collected on 5th March 2009 during good weather. Peak hour was taken generally from 8.30 a.m to 9.30 a.m and 5.30 p.m to 6.30 p.m, when the civil servants going to and back from office. The time and day was selected such that they are responsive to the working days morning and evening peak hour. 3 Results and Analysis Saturation and demand flow and turning proportion for each turning movement at the test signalized intersection were counted.

From data in Table 1, the calculation for the saturation headway, flow rate and lost time have been done.

Table 1. T3 and T13

Since the traffic demand in this intersection does not exceed 90% of capacity, the delay is calculated based on steady‐state queuing theory using the equation below.

(1) Where: d = average delay per vehicle; c = cycle time; x = degree of saturation; s = saturation flow; q = flow; λ = proportion of effective green to cycle time

Meanwhile, Table 2 summarizes the result of effective green, proportion of effective green to cycle time, degree of saturation and delay for each arm during morning and evening observation. Table 2. Effective green, g/c, Degree of saturation and delay

3.1 Estimated Results • Optimum Cycle Time and Actual Green

Table 3 shows the traffic flows and y values for each stage.

• Delay Table 4 shows the estimated effective green/cycle time, degree of saturation and delay for each arm.

• Queue The estimation of queue length at unsaturated period can be obtained using “Equation 2”.

Nu = q × r (2) Where: Nu = initial queue at the beginning of an unsaturated green period; q = flow; r = effective red period

Table 5 shows the result of queue estimation for each arm.

Table 3. Traffic flows and y values

Table 4. Estimation of results


ISSN: 1790-5117 168 ISBN: 978-960-474-135-9

Table 5. Number of vehicles queue

3.2 Staging and Timing Diagram

• Observed Staging and Timing Diagram Fig. 1 shows the staging diagram and Fig. 2 and Fig. 3 show the timing diagram for observed cycle time.

• Estimated Staging and Timing Diagram Fig. 4 shows the staging diagram and Fig. 5 shows the timing diagram for estimated cycle time.

Figure 1. Observed staging diagram

Figure 2. Observed timing diagram (A.M)

Figure 3. Observed timing diagram (P.M)

Figure 4. Estimated staging diagram

Figure 5. Estimated timing diagram

3.3 TRANSYT Optimisation Results In TRANSYT, link numbers references are North‐East; South‐North; East‐South; South‐East North‐South and East‐North

• Staging Diagram Fig. 7 shows the optimization staging diagram for this intersection.

• Timing Diagram Fig. 8 and Fig. 9 show the optimization timing diagram for this intersection.

• Stops and Delays Table 6 shows the optimization link result for A.M and P.M stops and delays meanwhile Table 7 shows the optimization network result for both A.M and P.M stops and delays.

Figure 6. Network diagram


ISSN: 1790-5117 169 ISBN: 978-960-474-135-9

Figure 7. Optimization staging diagram

Figure 8. Optimization timing diagram A.M

Figure 9. Optimization timing diagram P.M

Table 6. Link stops and delays

Table 7. Network stops and delays

3.4 Observed‐Estimated Relationship After applying the chi‐squared analysis for morning and evening observation with estimated results the observed‐estimated relationship of main terms of study are shown in Fig. 10 to Fig. 14.

Figure 10. Observed‐estimated actual green relationship

Figure 11. Observed‐estimated effective green

relationship

Figure 12. Observed‐estimated g/c relationship

Figure 13. Observed‐estimated degree of saturation

relationship


ISSN: 1790-5117 170 ISBN: 978-960-474-135-9

Figure 14. Observed‐estimated delay relationship

4 Discussion The traffic flow through the intersection during morning observation is lower than evening observation. Since the observation was done between 8.30 a.m to 9.30 a.m, there are small number of shops and shopping complex around the survey area that opened during the survey period. Most of the shops and shopping complex in that area only start their business hours at 10.30 a.m. During evening observation, the traffic flow through the intersection is high because workers going back from offices to residential areas and shopping complex. Besides, the intersection is located near shops and JUSCO. This will increase the number of buses and lorries to utilize the roadway and intersection for goods distribution.

The mean of south‐east headway A.M is 1.83 sec and headway P.M is 2.17 sec. The headway for mixed traffic is 6 m. Therefore, during the initial discharge, the vehicle speed A.M is around 12 km/hr and vehicle speed P.M is around 10 km/hr.

The mean of south‐east saturation flow A.M is 1990 pcu/hr which is greater than estimated right turn saturation flow of 1800 pcu/hr. Meanwhile, the mean of south‐east saturation flow P.M is 1690 pcu/hr which is lesser than estimated right turn saturation flow of 1800 pcu/hr. This is expected to happen since the effective green A.M is lesser than effective green P.M. Saturation flow is inversely proportional to effective green but directly proportional to cycle time.

The mean of south‐east lost time A.M is 2.60 sec while lost time P.M is 1.50 sec. The standard (estimated) lost time due to starting delays is 2 sec. Lost time A.M is higher than the standard value. Since the lost time A.M is higher and lost time P.M is lower than standard value, the saturation flow A.M was expected to be lower and saturation flow P.M to be higher than estimated saturation flow. However, the result shows the contra situation. It might caused by the leading drivers were not aware waiting for green time in the morning since there was not much vehicle during that period. However, in the evening, when people are in the way of going home,

they were more aware waiting for green time and minimize the lost time.

The mean for effective green for north arm A.M is 25 sec while effective green P.M is 33sec. The mean for effective green for south arm A.M is 31 sec while effective green P.M is 37 sec. The mean for effective green for east arm A.M is 10 sec while effective green P.M is 18 sec. The estimated effective green for north, south and east arms are 18, 24 and 15 sec respectively. The effective green A.M is lower than effective green P.M. This result supports the actual green statement below.

The mean for actual green for north arm A.M is 24 sec while actual green P.M is 32 sec. The mean for actual green for south arm A.M is 30 sec while actual green P.M is 36 sec. The mean for actual green for east arm A.M is 9 sec while actual green P.M is 17 sec. The estimated actual green for north, south and east arms are 17, 23 and 14 sec respectively. As similar to effective green, the actual green A.M is lower than actual green P.M. This is because effective and actual green are directly proportioned.

The actual green for north and south arms is higher than east arm because they are major arms. East arm is a minor arm. Therefore, more actual green is given to major arms because the traffic demand from those two arms is higher than east arm. Since this signalized intersection is using sensor or vehicle‐actuated, the signal timing is based on traffic demand on the arm. Another point is, since there is higher traffic demand from those major arms, more actual green is given to avoid long queue and delay to vehicles on those arms.

The mean cycle time A.M is 78 sec while cycle time P.M is 99 sec. The estimated cycle time is 65 sec. The observed cycle time is higher than estimated cycle time. The cycle time A.M is lower than cycle time P.M. This is directly influenced by low traffic flow through the intersection during morning observation. Since the traffic flow is low, the cycle time is short. When the cycle time is shorter, with standard starting delay of 2 sec and lost time due to intergreen period, the available effective green for the driver is shorter. Another point is, shorter cycle time might cause the signal control become inefficient because it leads to lengthy delays. Delay is influenced directly proportional by cycle time.

The mean of effective green/cycle time (g/c) for north arm A.M is 0.342 while g/c P.M is 0.330 sec. The mean for g/c for south arm A.M is 0.397 while g/c P.M is 0.365. The mean for g/c for east arm A.M is 0.131 while g/c P.M is 0.180. The estimated g/c for north, south and east arms are 0.277, 0.369 and 0.231. The observed g/c for north and south arms is higher than estimated g/c. The g/c for two arms are higher because their effective green is higher compared to effective


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green for east arm. While, the observed g/c for east arm is lower than estimated g/c.

The mean for north‐south degree of saturation A.M is 0.547 and degree of saturation P.M is 0.540. The mean for north‐east degree of saturation A.M is 0.175 and degree of saturation P.M is 0.170. The mean for south‐ north degree of saturation A.M is 0.225 and degree of saturation P.M is 0.240. The mean for south‐east degree of saturation A.M is 0.197 and degree of saturation P.M is 0.190. The mean for east‐north degree of saturation A.M is 0.386 and degree of saturation P.M is 0.265. The mean for east‐south degree of saturation A.M is 0.236 and degree of saturation P.M is 0.165. Those values show that the degree of saturation A.M is higher than degree of saturation P.M. This is unexpected since the traffic flow A.M is lower than P.M. The degree of saturation P.M was supposed to be higher than A.M.

The delay A.M is lower than delay P.M. This is expected since the cycle time A.M is lower than cycle time P.M. The observed delay is higher than estimated delay. There is less difference in observed and estimated delay for south and north arm. There are more delays at east arm compared to two major arms. This is because east arm is a minor arm which is given less green time. Another point is, the east arm is connected with the third intersection which the distance of 100 m between both intersections is very small. The small distance between them, make them become unisolated signalized intersection. This is contra to the first intersection which there is lengthy distance between first and second intersections. The far distance between those intersections make them become isolated and the signal settings are not correlated to each other. Since there are fewer delays in north and south arms, less vehicle queuing in those arms. Delay is affected by cycle time, g/c, degree of saturation and traffic demand. Delay is directly proportional to cycle time and degree of saturation, inversely proportional to g/c and demand flow. This was supported by the pattern of the delay‐cycle time, delay degree of saturation and delay‐g/c graphs. The higher the degree of saturation, more delays are expecting to occur. The same condition happened when the cycle time is longer. Longer cycle time will increase the vehicle delay. However, when g/c increases, the delay is getting lower. For those graphs having R2 more than 0.8, it was concluded that the relationship of delay and the parameter is in excellent agreement.

The estimated LOS for north and east arms is LOS C while south arm is LOS B. The observed LOS for N‐S A.M is LOS C and P.M is LOS D. The observed LOS for N‐E A.M and P.M is LOS C. The observed LOS for S‐N and S‐E for both A.M and P.M is LOS C. The observed LOS for E‐N and E‐S for both A.M and P.M is

LOS D. Therefore, observed for north and east arms is LOS D while south arm is LOS C. The estimated LOS is better than the observed LOS for all arms. It was found that the major arms have better LOS compared to minor arms. This is because of less green period was given to minor arm. Therefore, the vehicles in minor arm have higher delay which reduces the LOS of that arm.

Table 8. Level of service (LOS) ratio

The capacity for all arms of the intersection is less than saturation flow. The traffic flow at the intersection is lower than the capacity; therefore, the intersection still can sustain the demand from that area. This was supported by reserve capacity value. The reserve capacity of the intersection is 183%. This shows that the intersection still does not reached it maximum capacity. The performance of this intersection is still better. This was supported by the LOS of each arm of this intersection. The LOS for this intersection is still acceptable. Therefore, no improvement or upgrading is needed for this intersection for this time being.

X2 analysis for A.M shows almost observed and estimated of actual green, effective green, g/c, degree of saturation and delay results is valid and reliable except for delay for east arm. X2 analysis for P.M shows almost observed and estimated of actual green, effective green, g/c, degree of saturation and delay results is valid and reliable except for delay for east arm and actual and effective green for south arm.

For A.M results of actual green, almost all X2 lies between 1.642 and 3.841. This means that there is 5% to 20% confidence in those results. However, there is only 1% confidence level for P.M results of actual green. The same condition goes to A.M and P.M results of effective green where there are 5% to 20% confidence in A.M results of effective green and only 1% confidence level for P.M results of effective green.

For A.M and P.M results of g/c and degree of saturation, almost all X2 lies below 0.455. This means that there is more 50% confidence in those results which shows that the result is better and more reliable and accurate. The same condition goes to A.M results of


ISSN: 1790-5117 172 ISBN: 978-960-474-135-9

delay for north and south arm where there are more 50% confidence level. However, there are 25% confidence level in P.M results for north arm delay and 10% confidence level in P.M results for south arm delay. The A.M and P.M results for east arm delay is 1% confidence level. The larger the confidence level, more reliable and accurate the results are. Therefore, based on significance level, delay for east arm less reliable and less accurate.

Based on observed‐estimation relationships, it was found that the most of the results lies below the median line (45° line) and not in excellent agreement. The actual and effective green appeared mostly to be underestimated while the g/c was overestimated. The relationship between observed and estimated degree of saturated seems to be in excellent agreement with R2 more than 0.8.

In optimization of traffic signal settings, the important parameter that being considered are vehicle stops and delays. The TRANSYT optimization signal setting for this intersection is using 2 stages. The intersection has actual 3 stages. For optimization result, since it has fewer stages than actual, the mean delay for each arm is less compared to observed delay. Less delay give more benefit to the drivers because there is less vehicle queuing. When there is less delay and less vehicle queuing, the intersection performance is better where the LOS is high. When using 2 stages, most arms has LOS A which mean delay is less than 5 sec/pcu except for south‐north arm. Only maximum 9 pcus is expecting to queue when using 2 stages and also 3 stages.

It was found that estimated number of vehicles queuing (3 stages) is more than optimization number of vehicles queuing (2 stages). Since the estimated cycle time is shorter than observed cycle time that being used in TRANSYT optimization, it is expected to have less number of vehicles queuing. Short cycle time influenced the intersections to have low delays and low vehicles queuing.

Although 2 stages is a better approach for this intersection, but in Malaysia, number of stages is usually depends on number of arms exist in the intersection, since this intersection have 3 arms, the approach used was 3 stages. The existences of flare on north going to east arm and from east to south arm helps to increase the traffic flow movements.

Overall, the factors that influenced the saturation flow in the intersection are the turning movements, number of lanes, type of area and percentage of heavy vehicles. For the time being, no improvement is needed for that intersection because of acceptable LOS and high reserve capacity.

5 Conclusion and Recommendation As a conclusion, the test signalized intersection has acceptable headway, saturation and lost time. The major arm of the intersection has LOS C while minor arm has LOS D, which was still acceptable. The existing traffic demand is still less than the intersection capacity, which means that the flow in this intersection is still not oversaturated yet. Therefore, no upgrading is needed for this intersection for this time being. However, since minor arm has high delay, attention need to be given to this arm since it was connected to the nearest third intersection to reduce the probability of getting worst LOS and delay.

For future studies, it was recommended to measure headway, lost time and saturation flow rate for all arms of this intersection. Besides, survey should be done to all three intersections to determine the correlation signal settings and control for all intersections. This is essential to ensure that these three intersections perform efficiently, which directly decrease the delay and increase the safety at these intersections.

Acknowledgment The author is thankful to MOSTI through RMC of Universiti Teknologi Malaysia (UTM) and UTM for providing financial aid to carry out this research. References: [1]. www.wikipedia.org [2].Chapter 16: Highway Capacity Manual. TRB, National Research Council, Washington, D.C., 2000. [3]. Salter, R. J., and Hounsell, N. B. Highway Traffic Analysis and Design, New York,1996. [4]. Public Works Department Malaysia. A Guide to the Design of Traffic Signals. Arahan Teknik Jalan 13/87. Malaysia: Jabatan Kerja Raya (JKR), 1985. [5]. Fred, L. M., and Walter, P. K., Principles of Highway Engineering and Traffic Analysis, New York, 1998.


ISSN: 1790-5117 173 ISBN: 978-960-474-135-9

saturation flow at traffic signal using transyt: a case study in

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