Traffic performance of shared lanes at signalized intersections based on cellular automata modeling

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1 JOURNAL OF ADVANCED TRANSPORTATION J. Adv. Transp. 2014; 48: Published online 6 August 2013 in Wiley Online Library (wileyonlinelibrary.com) Traffic performance of shared lanes at signalized intersections based on cellular automata modeling Chen Chai and Yiik Diew Wong* School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore SUMMARY Shared lanes at signalized intersections are designed for use by vehicles of different movement directions. Shared lane usage increases the flexibility of assigning lane grouping to accommodate variable traffic volume by direction. However, a shared lane is not always beneficial as it can at time result in blockage that leads to both capacity and safety constraints. This paper establishes a cellular automata model to simulate traffic movements at signalized intersections with shared lanes. Several simulation experiments are carried out both for a single shared lane and for an approach with a shared lane. Simulation of a single shared lane used by straight-through and right-turn (as similar to left-turn in the USA) vehicles suggests that the largest travel delay occurs when traffic volumes (vehicles/lane) of the two movement streams along the shared lane are at about the same level. For a trial lane-group with a shared lane, when traffic volumes of the two movement streams are quite different, the shared lane usage is not efficient in terms of reduction in traffic delay. The simulation results are able to produce the threshold traffic volume to arrange a shared lane along an approach. Copyright 2013 John Wiley & Sons, Ltd. KEY WORDS: signalized intersection; shared lane; cellular automata; traffic delay 1. INTRODUCTION Cities around the world are looking for new answers to deal with the perennial road traffic problems, such as traffic congestion and safety. In recent years, much attention is being paid to road intersections controlled by signal lights, as signalized intersections form one of the most common bottlenecks in the urban traffic system. For an urban environment as Singapore, there are more than 1400 signalized intersections while also noting that motorists drive on the left side of the road as similar to UK s driving convention. One of the important issues that have seldom been studied is the design of right-turn lane, especially the usage of shared straight-through and right-turn lanes that is common in Singapore. According to an observation survey of 154 cross-intersections spread over the island state, about 46% approaches do not have a shared lane, 33% of them consist of exclusive and shared lanes, and the remaining 20% approaches do not have exclusive lanes. Among all the shared lanes, those shared by straight-through and right-turn movements is the most common type (63%), which is arranged in addition to the exclusive right-turn lane when right-turn traffic volume is heavy as occurring for some periods of the day. The arrangement of shared lane is usually based on traffic volumes of the two movement streams, especially right-turn traffic volume (left-turn in right-hand driving). Having a shared lane can help to increase right-turn capacity and to balance vehicle flows of diverging movements at an approach [1]. In the case where right-turn traffic volumes along opposite approaches are not evenly matched, *Correspondence to: Yiik Diew Wong, School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore. cydwong@ntu.edu.sg Copyright 2013 John Wiley & Sons, Ltd.

2 1052 C. CHAI AND Y. D. WONG one of the approaches may be installed with a shared straight-through and right-turn lane to complement the exclusive right-turn lane so that signal phasing can be well matched for both approaches [2,3]. However, the capacity of a shared lane is not as high as the lane capacity for exclusive movements. A shared lane can cause severe reduction of intersection capacity and vehicle blockage, thus leading to an increase of traffic delay [4]. As protected right-turn signal control is mostly applied at intersections with high traffic volume, a right-turn vehicle can block following straight-through vehicle during straight-through green phase and straight-through vehicles can also block following turning vehicles during protected right-turn green arrow phase. Furthermore, when blockage at shared lane occurs, some queuing vehicles will change to exclusive lanes [5]. This ad hoc lane-changing near to the stop-line (which is permitted in Singapore) may cause safety problem to vehicles in the vicinity. Therefore, one should be very careful whenever deciding to install a shared lane at signalized intersections. Some analytical models have been developed to study the capacity as well as the blockage effect of shared lane. Akçelik [6] proposed a direct method to calculate the capacity of shared lane that takes account of blockage effect and mixed traffic f low. Wu [7,4] has conducted a series of studies into shared lanes. One of them estimated the capacity of short shared lane by calculating each movement stream individually. In another study, blockage probability at shared lane was estimated [7,4]. Zhou and Zhuang [8] estimated the traffic delay at shared lane influenced by the different proportion of left-turn vehicles and signal timing under right-hand driving rules. In most current analytical models, the impact of shared lane is seldom considered as part of the lane group at an intersection approach. As vehicles might change lane along the approach, analytical models are not very adaptable to different intersection layouts. Moreover, vehicle interactions and conflicts have not been modeled in a microscopic way. With increasing computation technology, cellular automata (CA) models, which require massive computing, are becoming popular for modeling and simulating complex scenarios [9,10]. On the basis of flexible transition rules, it is becoming easier to use CA models to simulate microscopic traffic behavior accurately while leveraging on parallel CA computation [11]. Compared with traditional simulation methods and analytical models, CA model is found to have higher computational efficiency and flexibility in accommodating different traffic movements. This research establishes a composite CA model for signalized intersections with shared lanes. Using CA modeling technique, the capacity reduction and blocking effects between movements in vehicle streams within a shared lane are estimated through microscopic simulation. The simulation results are useful to identify problems of existing design and to make better decisions toward enhancing intersection design and operations. 2. MODEL DEVELOPMENT The selected intersection for case study used in this simulation is a typical cross-intersection with signal control in Singapore (Jurong Town Hall Road and Jurong East Avenue 1). The chosen site is part of a dense network with Jurong Town Hall Road connecting the two major road corridors, the Pan Island Expressway to the north and the Boon Lay Way to the south. The intersection configuration and layout is shown in Figure 1. East-bound approach along Jurong East Avenue 1 intersecting Jurong Town Hall Road is studied, comprising one short exclusive left-turn lane adjoining a slip road, one exclusive straight-through lane, one shared straight-through and right-turn lane, and one short exclusive right-turn lane. Vehicles coming from upstream have a long approach distance ( 200 m). As traffic delay at peak periods is always much higher than off-peak periods, on-site observation is undertaken during evening peak period on a weekday from 6 PM to 7 PM. In this study, vehicles are generated at each time step according to a calibrated negative binomial distribution at each 10-second interval based on observed traffic volume. For simplified computation, to represent mixed traffic flow, vehicles are converted to cars according to passenger car equivalent calibrated in Singapore. As the study is focused on interactions between straight-through and right-turn vehicles at signalized intersection, this simplification should not affect the studied issues significantly. According to observation, the traffic volume of the studied approach is around 900 pcu/hour during evening peak periods constituting 100 pcu/hour left-turn, 300 pcu/hour straight-through, and 500 pcu/hour right-turn.

3 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1053 Figure 1. Configuration of case junction (driving is on left side of the road). For each simulation scenario in this study, proportions of straight-through and right-turn vehicles using the shared lane are pre-assigned as traffic arrival. The proportions show the initial intent of drivers to use the shared lane. However, during respective green phase, if there is enough gap provided in neighboring exclusive lane, then some vehicles queuing in shared lane will change to exclusive lane on the basis of multi-lane NaSch model. The lane-changing probability is assigned as 0.29 according to the on-site observation of a stream of 100 queuing vehicles. As for speed profiles of individual vehicles, the observed average and the 95th percentage speeds observed at similar sites for three locations are, respectively, 20.7 km/hour and 58.9 km/hour for vehicles at approach, 21.3 km/hour and 56.4 km/hour for straight-through vehicles at intersection-box area, and 16.7 km/hour and 32.5 km/hour for right-turning vehicles within intersection-box area. Observed traffic signal timing during 6 7 PM weekday is summarized in Figure 2. The studied approach has a 30 straight-through green phase and 30 seconds right-turn green phase with cycle length equals to 132 seconds. As dynamic signal timing is applied in the studied intersection, the average length of each Figure 2. Average signal timings at evening peak period (weekday, 6 7 PM).

4 1054 C. CHAI AND Y. D. WONG signal phase is used in simulation. During the studied period (6 7 PM), the maximum standard deviation of each signal phase is 0.75 seconds. Therefore, it is acceptable to use average values [12]. In this model, only east approach along Jurong East Avenue 1 is simulated. The CA model is developed as shown in Figure 3. Larger cells (7 3.5 m) are used along approach and departure lanes. Smaller cells ( m) are used within intersection-box area. In the studied approach, exclusive right-turn lane is a short lane. Simulated length of the shared lane is chosen as 10 larger cells (70 m) according to field observation. According to simulation results, the maximum queue length at shared lane in all the scenarios is eight vehicles (eight larger cells) which is shorter than the length of exclusive right-turn lane. The blockage effect can be neglected in this study. Observed traffic flow characteristics, such as vehicle speed, arrival distribution, and acceleration rate are used to define the simulation inputs as well as the rules of vehicle movement. The model is validated both in macroscopic (traffic delay per vehicle) and microscopic levels (speed profile). 3. RESULTS AND DISCUSSIONS Simulation results can be used to test if the shared lane is a proper arrangement at the approach under certain observed traffic volume. Several simulation experiments were conducted to estimate traffic performance at the shared lane. Traffic performance, in terms of traffic delay of both vehicle movements, is estimated under various traffic volumes [13]. The net effect of traffic delay caused by a shared lane D sh sh is defined as the difference between average travel time in a shared lane and in an exclusive lane within the same flow-density. D sh ¼ T sh T 0 Where T sh is the average travel time of vehicles in a shared lane and T 0 is the average travel time of vehicles in an exclusive lane, for the given movement. The model has been validated by simulation under observed traffic condition (traffic volume, signal plan, and proportion of vehicles using the shared lane). Comparison of traffic delay from simulation and field data is shown in Table I. The results of traffic delay show very good agreement. Higher error at lane 1 (left-turn lane) is caused by the non-inclusion of a zebra pedestrian crossing for modeling. Figure 3. Designated paths for movements according to lane grouping (no. 1: exclusive left-turn, no. 2: exclusive straight-through, no. 3: straight-through right-turn shared lane, and no. 4 exclusive right-turn).

5 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1055 Table I. Comparison of traffic delay per vehicle (seconds/veh) from cellular automata simulation and field data. Lane 1 Lane 2 Lane 3 (shared lane) Lane 4 Left-turn Through Through Right-turn Both movements Right-turn Field data CA simulation Error 7.49% 0.88% 0.30% 1.49% 0.77% 0.55% CA, cellular automata. The CA model developed for shared lane is confirmed to be able to replicate realistic signalized intersection traffic at the macroscopic level. For the simulation, first of all, a single shared lane CA model in isolation of other lanes at the approach is established. A series of simulation have been conducted to estimate the blockage effect within the shared lane. Under the same total traffic volume within the shared lane, the effect of vehicle proportion along the shared lane on the performance of both vehicle movements is analyzed. Secondly, the whole approach is simulated. A lane group CA model at studied intersection approach (one exclusive left-turn lane, one exclusive straight-through lane, one straight-through right-turn shared lane, and one exclusive right-turn lane) is established. Last but not the least, traffic performance of shared lane is tested under other lane grouping arrangements Blockage effect along shared lane due to vehicle proportions Several scenarios are created for micro-simulation to assess the blockage effect of a shared lane by computing the average traffic delay of the given vehicle movement. As blockage may occur, vehicles along a shared lane will always have a larger delay than along an exclusive lane [7]. Preliminary simulation involves only the single shared lane used by straight-through and right-turn vehicles, in isolation of other lanes at the approach. Capacity of shared lane is calculated as 304 pcu/hour (152 pcu/hour for each traffic movement) according to an analytical model proposed by Akçelik [6] when green time assigned for each movement direction is 30 seconds for straight-through green phase and 30 seconds for right-turn green phase with cycle length at 132 seconds (as per observation), and straight-through and right-turn vehicles are equally matched (1:1). In simulation, the total traffic volume is kept as 300 pcu/hour and green time assigned for each movement direction is 30 seconds for straight-through green phase and 30 seconds for right-turn green phase (as per observation). The simulation runs for 30 signal cycles, approximately 1 hour. Delay for straight-through and right-turn movements of vehicles is calculated according to the average results of five runs as suggested by Zheng et al. [14]. For each set of runs, a specified proportion of straightthrough vehicles along shared lane is simulated at 0.1 step interval from 0 to 1. In this way, estimated travel time of total vehicles on the shared lane is computed for varying proportions of straight-through vehicles as shown in Figure 4. When the proportion of straight-through vehicles α T = 0 or 1, the travel time is effectively that of the exclusive right-turn or straight-through lane. Other scenarios in different Figure 4. Estimated travel time for all vehicles along shared lane in different signal settings.

6 1056 C. CHAI AND Y. D. WONG signal settings are also created as results shown in dashed lines. The degree of saturation is therefore calculated for each scenario. It is found that signal timing has some effect on blockage effect along shared lane. And when the degree of saturation of the two vehicle movements are about equal, blockage effect reaches to maximum values. However, from simulation results, the maximum blockage does not occur when degrees of saturation are exactly equal. It happens between evenly matched split to equal degrees of saturation. This is mainly due to random arrival at shared lane. Moreover, according to Figure 5(a and b), it is found that no matter the traffic proportion of whichever vehicle movement is higher, the distribution of traffic delay is fairly symmetrical. This would suggest that there would be a tendency for vehicles along a shared lane to be skewed in favor of either movement type, under conditions where there is adequate room (enough capacity at lane group) for lane switching Traffic performance of a lane group with a shared lane Proportion choosing to enter a shared lane In this part, a lane group that is a combination of different types of lane as shown in Figure 3 is created according to the lane-markings of the studied approach. The simulation that is based on CA model runs for 30 signal cycles according to signal phases observed in the field. Proportions of straight-through or right-turn vehicle choosing the shared lane varied from 0 to 0.5, whereas the traffic volumeisfixed as shown in Table II. It is noted that the maximum relative proportion of either movement shall not exceed 0.5 on the rationale that given a choice of two lanes (exclusive and shared), the split is at most 50% along the shared lane. Four scenarios are created under different traffic conditions as shown in Table II [15]. Simulation results show the change of traffic delay due to shared lane usage under a certain traffic condition. Saturation flow of an exclusive straight-through lane with observed signal timing is 381 pcu/hour. Therefore, in this study, as there are two exclusive lanes and one shared lane, low traffic volume is chosen as 300 pcu/hour and high traffic volume is chosen as 600 pcu/hour. Figure 5. Traffic delay for (a) straight-through and (b) right-turn vehicles along a single shared lane.

7 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1057 Table II. Simulation scenarios with different traffic volumes. Scenario Straight-through traffic volume a (pcu/hour) Right-turn traffic volume b (pcu/hour) 1 low (300) low (300) 2 (observed) low (300) high (600) 3 high (600) low (300) 4 high (600) high (600) a Straight-through traffic volume: traffic volume on exclusive straight-through lane and on shared lane that make straight-through route decision; b Right-turn traffic volume: traffic volume on exclusive right-turn lane and on shared lane that make right-turn route decision. Scenario 1: Low straight-through traffic volume and low right-turn traffic volume In this scenario, simulation is conducted under observed signal timing (30 seconds each for both straight-through and right-turn). Figure 6(a and b) shows the estimated traffic delay for all right-turn and straight-through vehicles in the system. The bottom X and Y axes are proportions of straightthrough and right-turn vehicles choosing the shared lane. A series of data points (shown as dots in Figure 6(a and b) were generated for various combinations of vehicle proportions, and Lowess method (locally weighted smoothing linear regression) was used to generate the surface. According to simulation results, higher traffic delay occurs when there is 1:1 split along the shared lane (shown as the semi-transparent plane). This is consistent with the simulation results of the single Figure 6. (a) Estimated traffic delay of right-turn vehicles (Scenario 1, R-square: ) and (b) estimated traffic delay of straight-through vehicles (Scenario 1, R-square: ).

8 1058 C. CHAI AND Y. D. WONG shared lane that the maximum average traffic delay as well as the maximum blockage effect occurs when the two vehicle movements along the shared lane are evenly matched. The results indicate that when either of relative proportion of either straight-through or right-turn vehicles is below 20%, the average delay is the lowest. In reality, one can expect traffic proportions along shared lane will be interchangeable with either (but not both) movement to predominate. Therefore, when there is enough capacity along exclusive lanes, the traffic performance of a lane group is affected by the blockage effect along shared lane. In addition, higher traffic delay for right-turn vehicles is a result of lower speed during turning movement. Scenario 2: Low straight-through traffic volume and high right-turn traffic volume (as observed) Figure 7 shows the average traffic delay for all vehicles due to relative proportion of two vehicle movements using shared lane. The lowest average traffic delay occurs at two vehicle proportions. The first one is when 50% of right-turn and 0% of straight-through vehicles are using shared lane. This situation is very extreme. In reality, as competition between the two vehicle movements exists, this situation cannot be achieved as straight-through vehicles will also enter the shared lane. The second low point is when 30% of right-turn vehicles and 27% of straight-through vehicles are using the shared lane, which is close to observed proportion (0.33, 0.28). This indicates, as a self-organized system, traffic of the whole approach itself tends to the minimum overall traffic delay. To study the impact of signal timing on shared lane performance, simulation is conducted for two sets of signal settings, one for same signal timing as Scenario 1 and the other for an adjusted signal timing based on Webster s method according to traffic volumes. In the adjusted signal timing, the green time for straight-through and right-turn is 23 seconds and 46 seconds, respectively. Figure 8(a d) shows the estimated traffic delay for all right-turn and straight-through vehicles in the system with two signal timings. In this case, as shown by the plane surface in Figure 8(a and b), when traffic volume of the two vehicle movements within the shared lane are evenly matched, average traffic delay for all vehicles in the approach is not the maximum. It indicates, for the whole approach under higher traffic volume, larger traffic delay caused by the usage of shared lane is not only due to the blockage effect, but also to different traffic volume and the proportion of different vehicle movements using the shared lane. According to Figure 8a, the lowest average traffic delay per vehicle of right-turn vehicles occurs when more of right-turn vehicles and none of straight-through vehicles chose the shared lane. One possible reason is that observed traffic volume of right-turn vehicles is much higher than straightthrough vehicles. When straight-through vehicles in the shared lane block more right-turn vehicles, the queue length will increase rapidly as well as the vehicles travel time. Therefore, if the blockers (straight-through vehicles) are removed, then the average delay for all vehicles will decrease. On the other hand, the lowest traffic delay of straight-through vehicles occurs when none of straightthrough vehicles or right-turn vehicles chose the shared lane (Figure 8b). The simulation results indicate that under certain conditions, such as when right-turn volume is much higher than straight-through Figure 7. Estimated traffic delay of all vehicles (Scenario 2, R-square = ).

9 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1059 Figure 8. (a) Estimated traffic delay of right-turn vehicles (Scenario 2, observed signal timing, R-square: ), (b) estimated traffic delay of straight-through vehicles (Scenario 2, observed signal timing, R-square: ), (c) estimated traffic delay of right-turn vehicles (Scenario 2, adjusted signal timing, R-square: ), and (d) estimated traffic delay of straight-through vehicles (Scenario 2, adjusted signal timing, R-square: ). volume, even though the shared lane increases the overall capacity of right-turn vehicles, the usage of shared lane is not beneficial to straight-through vehicles. When straight-through vehicles enter a shared lane, blockage by right-turn vehicles will occur. This will result in a larger travel time and produces an increase in travel delay, relative to observed signal setting. Reduction of traffic delay per right-turn and straight-through vehicle in two signal settings (relative to observed signal timing) are calculated and summarized in Tables III and IV. In both Tables III and IV, a positive value represents reduction of traffic delay and a negative value represents increase of traffic delay. According to Figure 8c and Table III, adjusted signal timing has reduced traffic delay for right-turn vehicles in several simulation scenarios as more green time is given for right-turn vehicles. The reduction is larger in scenarios when more vehicles of both movements are using the exclusive lanes instead of shared lane. This is due to right-turn capacity of the studied approach being increased as more green Table III. Reduction of delay per right-turn vehicle in adjusted signal timing ST b RT a % 28.12% 35.21% 12.84% 13.38% 22.83% % 15.50% 7.99% 36.97% 17.90% 3.41% % 17.89% 3.51% 7.52% 7.58% 6.57% % 1.24% 3.91% 5.19% 26.49% 11.90% % 3.22% 8.05% 9.16% 16.06% 26.26% % 4.60% 4.87% 2.04% 26.76% 15.83% a RT = Relative proportion of right-turn vehicles using shared lane. b ST = Relative proportion of straight-through vehicles using shared lane.

10 1060 C. CHAI AND Y. D. WONG Table IV. Reduction of delay per straight-through vehicle in adjusted signal timing. ST b RT a % 17.40% 19.06% 15.22% 12.93% 21.86% % 23.62% 0.18% 7.80% 22.38% 19.13% % 16.16% 21.30% 18.86% 29.49% 35.95% % 17.69% 16.37% 8.46% 31.90% 35.25% % 21.33% 13.99% 19.22% 19.39% 29.43% % 18.52% 39.54% 42.08% 25.99% 28.31% a RT = Relative proportion of right-turn vehicles using shared lane. b ST = Relative proportion of straight-through vehicles using shared lane. time is given for right-turn vehicles. However, when relative proportion of the two movement streams using the shared lane is increased, blockage effect along shared lane will lead to larger traffic delay. Moreover, in the adjusted signal timing, green time for straight-through vehicles is reduced and right-turn vehicles are more likely to be blocked along the shared lane at right-turn green phase. In simulation scenarios with higher relative proportions of the two movement streams, delays per right-turn vehicle are larger in adjusted signal timing. In Figure 8d and Table IV, delay per straight-through is generally increased in all scenarios. This is due to straight-through capacity being reduced because of the shorter straight-through green phase. Therefore, even though signal timing is adjusted to meet the heavy right-turn traffic volume, blockage effect along shared lane will still reduce the capacity of the lane-group significantly especially when more vehicles are using shared lane. Simulation results of the two signal timings indicate that larger traffic delay will occur when a higher proportion of right-turn vehicles is using the shared lane. Therefore, apart from adjusting signal timing, one of the possible upgrade plans of the studied approach is to change the shared lane into an exclusive right-turn lane to remove the blockage. Before-after study of changing shared lane to exclusive lanes under observed traffic volume (light straight-through and heavy right-turn) According to the simulation results, under observed traffic volume, even though the shared lane increases the capacity of right-turn vehicles, straight-through vehicles are suffering from extra blockages because of the shared lane. The results suggest that changing the shared lane to an exclusive right-turn lane can optimize this lane grouping. Simulation is performed when the shared lane is changed to an exclusive straight-through or a right-turn lane. Table V shows the comparison of estimated traffic delay for straight-through and right-turn vehicles. Changing the shared lane into an exclusive right-turn lane produces the lowest overall traffic delay. This result confirms the conclusion of Scenario 2 in which the shared lane at studied approach is not making any contribution to straight-through vehicles under this traffic volume condition. The experiment shows that shared lane usage will produce higher traffic delay for vehicles in some situations as a result of extra blockages. Especially when traffic volumes of different moving directions are not evenly matched, the arrangement of one exclusive lane for each moving direction and supplemented with one shared lane might not be efficient. Table V. Comparison of estimated traffic delay (seconds/vehicle) of all vehicles. a D th b D rt c D all Before (shared lane) After (exclusive straight-through) After (exclusive right-turn) a D th = Delay per straight-through vehicle. b D rt = Delay per right-turn vehicle. c D all = Delay per vehicle for both movement streams.

11 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1061 Scenario 3: High straight-through traffic volume and low right-turn traffic volume Figure 9(a d) is the result of Scenario 3. Figure 9(a and b) is the result with observed signal timing. Figure 9(c and d) are the results with adjusted signal timing according to traffic volume (46 seconds for straight-through and 23 seconds for right-turn). According to Figure 9a, the lowest average traffic delay of right-turn vehicles occurs when none of right-turn vehicles or none of straight-through vehicles chose the shared lane. The lowest traffic delay of straight-through vehicles occurs when 50% of straight-through vehicles and none of right-turn vehicles chose the shared lane (Figure 9b). The result of straight-through vehicles, which is the majority of vehicles, is similar with right-turn vehicles in Scenario 2. And right-turn vehicles, which are the minority, are similar with straight-through vehicles in Scenario 2. Figure 9(c and d) shows the same trend as results in Scenario 2 with adjusted signal timing. Delay for straight-through vehicles, which are the majority of traffic flow, was significantly reduced when fewer right-turn vehicles are using shared lane. As delays with higher vehicle proportion using shared lane are not significantly reduced, the adjusted signal timing will not be able to increase lane-group capacity when more vehicles are using shared lane. Scenario 4: High straight-through traffic volume and high right-turn traffic volume In this scenario, traffic volumes of both streams are very high (600 pcu/hour for each vehicle movement), with observed signal timing (30 seconds for both straight-through and right-turn). In this scenario, signal timing is not adjusted because of balanced traffic volume for both movements. The simulation result shows that traffic delay of two types of vehicles is not significantly influenced by proportion of vehicles using shared lane (Figure 10(a and b)). This is because adding a shared lane gives both streams some extra space as well as causing blockages. Compared with Scenario 1, higher traffic delay is not observed in evenly matched split along shared lane according to simulation results in other three scenarios. It indicates that when at least one of traffic Figure 9. (a) Estimated traffic delay of right-turn vehicles (Scenario 3, observed signal timing, R-square: ), (b) estimated traffic delay of straight-through vehicles (Scenario 3, observed signal timing, R-square: ), (c) estimated traffic delay of right-turn vehicles (Scenario 3, adjusted signal timing, R-square: ), and (d) estimated traffic delay of straight-through vehicles (Scenario 3, adjusted signal timing, R-square: ).

12 1062 C. CHAI AND Y. D. WONG Figure 10. (a) Estimated traffic delay of right-turn vehicles (Scenario 4, R-square: ), and (b) estimated traffic delay of straight-through vehicles (Scenario 4, R-square: ). volume is heavy, there will not be enough capacity for exclusive lane to allow vehicles to occupy. Even though blockage effect is lower when one traffic movement is the majority, vehicles in exclusive lane will suffer from a longer queue because of heavy traffic volume and thus results in a higher overall delay. Table VI. Summary of simulation results. Scenario 1 Scenario 2 Scenario 3 Scenario 4 Traffic condition Low straight-through traffic volume and low right-turn traffic volume Low straight-through traffic volume and high right-turn traffic volume High straight-through traffic volume and low right-turn traffic volume High straight-through traffic volume and high right-turn traffic volume Conclusions Under light traffic condition, performance of shared lane is mainly affected by blockage effect. The maximum blockage occurs when the traffic volume of two movements are evenly matched. The shared lane is not beneficial for straight-through vehicles. An upgrade plan of changing the shared lane to an exclusive right-turn lane is suggested. The shared lane is not beneficial for rightturn vehicles. An upgrade plan of changing the shared lane to an exclusive straight-through lane is suggested. The shared lane affects similarly two movements. Under heavy traffic condition, performance of shared lane is not significantly affected by blockage effect.

13 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1063 Simulation results and conclusions are summarized in Table VI. The difference of simulation results under the four scenarios shows clearly that the performance of shared lane in the approach is affected by the traffic volume of two movements. Therefore, when making decisions on shared lane usage, traffic volume of the both streams should be considered instead of the traffic volume of right-turn vehicles only. Apart from the four simulated scenarios, the simulation model also allows road designers to input observed traffic volume in two movement directions and test the performance of shared lane. If the results are similar to Scenario 2 or 3, then upgrading will be necessary because the shared lane is not beneficial for either one of the vehicle movements. Figure 11. Typical 4-lane approach with shared lane. Figure 12. (a) Estimated traffic delay of right-turn vehicles (4-lane approach, R-square: ), and (b) estimated traffic delay of right-turn vehicles (4-lane approach, R-square: )

14 1064 C. CHAI AND Y. D. WONG 3.3. Traffic performance in other lane group arrangements In Singapore s context, apart from the lane configuration as studied 3-lane approach (33% of 49 surveyed approaches consist of exclusive and shared lane), another very typical shared lane arrangement is the 4-lane approach (Figure 11) with two exclusive straight-through lane, one shared straight-through and right-turn lane, and one exclusive right-turn lane (43% out of 49). Traffic delay with relative proportions of straight-through and right-turn vehicles using shared lane under heavy straight-through traffic volume (1000 pcu/hour) and heavy right-turn traffic volume (600 pcu/hour) is estimated through simulation. As capacity for an exclusive straight-through lane with observed signal timing is 381 pcu/hour, passenger car units per lane for both movements in this experiment are the same with Scenario 4 of preceding 3-lane configuration. From Figure 12(a and b), in such 4-lane configuration with heavy straight-through and right-turn traffic volumes, the lowest traffic delay for both movements occurs when around 15% straight-through and 35% of right-turn vehicles use the shared lane. Compared with Scenario 3 of studied lane configuration, both maximum and average traffic delay in this situation is lower for the same passenger car units per lane. The results show that 4-lane configuration will help to reduce the blockage problem within the shared lane by increasing the capacity for straight-through vehicles. 4. CONCLUSIONS AND POLICY IMPLICATIONS This paper developed a microscopic CA model for signalized intersections accounting for shared-lane usage and blockage. The CA model is applied to estimate traffic performance of a selected intersection. Simulation results allow traffic engineers to see the impact of shared lane under different traffic volume and usage of the shared lane. To study the blockage effect within shared lane, a shared lane is analyzed in isolation. Simulation results show that the blockage effect is related to the usage of different vehicle movements within the shared lane, and the highest traffic delay occurs when the traffic volume of two movement streams is about evenly matched. Later on, traffic performance of the shared lane is estimated in the lane group of intersection approach. For a particular lane configuration with a shared lane, the traffic delay of all vehicles for a lane grouping of one shared lane, one exclusive through lane, and one exclusive rightturn lane, simulation is conducted in different scenarios. Simulation results under observed traffic volume (light straight-through and heavy right-turn) suggest that for the whole approach, when one of the traffic volumes of two moving directions is particularly heavy, shared lane usage could increase the traffic delay. According to the simulation conducted with adjusted signal timing (larger green time for heavier vehicle movement), even though the capacity of the exclusive lane is improved, blockage effect along shared lane will still reduce the capacity of lane-group significantly especially when more vehicles are using shared lane. The CA simulation also shows that the relative proportion between traffic volumes of the two streams will affect the utility of shared lane. Although shared lane is arranged because of heavy right-turn traffic volume, straight-through traffic volume should also be examined carefully, as the shared lane will not function efficiently if straight-through volume is relatively low. The simulation results will be able to help traffic engineers to make decisions about whether to arrange a shared lane. By using observed or planned traffic volume for the two vehicle movements, as well as signal plan (fixed or dynamic), the traffic performance of shared lane in a planned lane-group can be estimated by running simulations for various scenarios. For example, if the simulation results approximate to Scenario 2, then the shared lane will be functioning well for right-turn vehicles but not for straight-through vehicles. If the simulation results are similar as Scenario 3, then the shared lane will not be functioning well for right-turn vehicles. However, when simulation results are like Scenario 4, the shared lane will be beneficial for both movement directions. By varying the simulated traffic volumes, the proposed model can also be used to produce the threshold of traffic volumes to decide whether the shared lane is beneficial. The intersection simulated in this study is using signal sequence of straightthrough green phase followed with right-turn green phase with no filtering allowed. For other sequences, the proposed model is still valid. However, the conclusions are only for the simulated signal sequence. Among the four scenarios for the different traffic conditions, traffic performance of the shared lane is quite different due to different traffic volume of the two vehicle movements. Therefore, as traffic volume

15 TRAFFIC PERFORMANCE OF SHARED LANES BY CELLULAR AUTOMATA 1065 changes during different times of a day, the shared lane will only be beneficial during particular hours. For road traffic authorities, one of the solutions is to make the lane markings changeable, by means of dynamic lane markings. For example, a digital board could be used ahead of the approach area to display real-time lane arrangement optimized for detected traffic volume. Light Emitting Diode (LED) road markers placed on road surface can also help to change the channelization of approaches. These technologies are being studied and designed in several countries including Australia, UK, and the Netherland [16]. Although CA model is not yet very popular among traffic engineers due to the lack of user friendly software, it is widely used in academic research and producing very valuable results in helping the engineers to make decisions. There are several advantages to use the CA model to estimate shared lane performance. First, the CA models allow local calibration on several aspects including car-following, lane-changing, and interaction between vehicles. Especially, for signalized junctions, queuing behavior and amber running behavior can also be simulated and adjusted. Specialized junction layout can also be defined in CA model. With user-defined traffic characteristics, the proposed CA model can be more flexible and accurate than analytical models. Furthermore, as vehicle s speed and position are discrete values, simulations by CA models are very efficient compared with other simulation packages. The CA model developed in this paper would be able to help authorities to make decisions on whether to involve shared lane. Land Transport Authority of Singapore is also generally cautious in arranging shared lanes. Most shared lanes in Singapore are arranged to save land usage while accommodating vehicles for both movements. Among the intersection improvement projects from 2010 to 2011, over 90% newly added lanes are exclusive and two shared lanes have been changed to exclusive lanes. Apart from calculating the capacity of shared lane according to quantitative models [17], microscopic simulation would help engineers to assess the traffic performance of their design in various traffic conditions and signal timings. REFERENCES 1. Liu Y, Yu J, Chang GL, Rahwanji S. A lane-group based macroscopic model for signalized intersections account for shared lanes and blockages. Transaction of IEEE Intelligent Transportation Systems 2008; Chen P, Nakamura H, Asano M. Lane utilization analysis of shared left-turn lane based on saturation flow rate modeling. Procedia Social and Behavioral Sciences 2012; 43: Creasey FT, Stamatiadis N, Viele K. Right-turn-on-red volume estimation and incremental capacity models for shared lanes at signalized intersections. Transportation Research Record 2011; 2257: Wu N. Modelling blockage probability and capacity of shared lanes at signalized intersections. Procedia Social and Behavioral Sciences 2011; 16: Tian ZZ, Wu N. Probabilistic model for signalized intersection capacity with a short right-turn lane. ASCE: Journal of Transportation Engineering 2006; 132: Akçelik R. Capacity of a shared lane. Proceedings of the 14th ARRB Conference 1988; 14(2): Wu N. Capacity of shared-short lanes at unsignalized intersections. Transportation Research Part A: Policy and Practice 1999; 33(3 4): Zhou Y, Zhuang H. Traffic performance in signalized intersection with shared lane and left-turn waiting area established. ASCE: Journal of Transportation Engineering 2012; 138(7): Lu WL, Hua WY, Li P, Wang Y. Research on Cellular Automaton Model for Evacuation Under Passenger Station. International Conference on Electronics, Communications and Control (ICECC) 2011; Mallikarjuna C, Rao KR. Cellular automata model for heterogeneous traffic. Journal of Advanced Transportation 2009; 43(3): Clarridge A, Salomaa K. Analysis of a cellular automaton model for car traffic with a slow-to-stop rule. Theoretical Computer Science 2010; 411(38 39): Yang J, Zhou H. Integrating left-turn lane geometric design with signal timing. ASCE: Journal of Transportation Engineering 2011; 137(11): Ross TF, Ceder A, Dressler O. Signalized intersections with variable flow rates. II. A model for delay estimation. Journal of Advanced Transportation 1989; 23(1): Zheng J, Suzuki K, Fujita M. Modelling a vehicle s speed fluctuation with a cellular automata model. WIT Transactions on the Built Environment 2012; 128: Brooks BM. Influence of vehicular interaction on PCU values. Proceedings of the Institution of Civil Engineers Transport 2010; 163(3): UK Government. ITS radar helpdesk query: dynamic road markings/variable road studs 2006; nationalarchives.gov.uk/+/ 17. Xu J, Yang X, Lao Y. Study on the capacity of left-through shared lane with permitted left-turn phasing. International Conference on Intelligent Computation Technology and Automation (ICICTA) 2008;