Simulation Test Setups

6.1.1. Test Intersection

A hypothetical four-leg intersection, as shown in Figure 25, was setup to evaluate the performance of the SMINP model. Three routes were setup for different testing

scenarios. Route No. 1 enters from the eastbound approach, encountering a nearside bus stop at about 60 meters (196 feet) from the stop bar. Route No. 2 enters from the

northbound approach and a bus stop locates roughly 80 meters (261 feet) from the stop bar. Route No.3 travels northbound and exits westwards without any bus stops. It is assumed that the intersection is equipped with wireless communication equipment that can detect the presence of the approaching bus and obtain relevant bus data, see Table 4 for details.

* _{Part of this section is reprinted with permission from “A Real-Time Transit Signal Priority Control}

Model Considering Stochastic Bus Arrival Time” by X. Zeng, Y. Zhang, K. Balke and K. Yin, 2014. IEEE Transactions on Intelligent Transportation Systems, volume 15(4), p1657-1666. Copyright 2014 IEEE.

118 f 3f 8 f 5 f 2 f 7 f 4 f 1 f 6 60 m (196 ft) Not to Scale Bus Route: 1 Speed: 60kpm (40mph)

Location: 150m (492ft) from stop bar Dwell Distribution: 20s (0.33), 30s (0.33), 40s (0.33) Optimal Timing: AM Pattern: f1-23, f2-34,… f8-20 PM Pattern: f1-17, f2-40,… f8-18 Bus Route: 2 Speed: 50kpm (35mph)

Location: 120m (393ft) from stop bar Dwell Distribution: 20s (0.33), 30s (0.33), 40s (0.33) 8 0 m ( 2 6 1 f t) Bus Route: 3 Speed: 50kpm (35mph)

Location: 80m (262ft) from stop bar

Communication Range of 150 meter f 4 f 1 f 2 f 7 f 8 f 5 f 6 f 3

Figure 25: Hypothetical Intersection.

6.1.2. Traffic Conditions

Table 5 shows the setup of three congestion levels represented by the volume-to- capacity (V/C) ratios. The cycle length, 110 seconds, is optimal for the v/c = 0.9 level, and it is not optimal for other two levels. Using one common cycle length rather than one in each volume level is to test the ability of the control models to give priorities

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under various v/c levels. Without fixing the cycle length, any reasonable offline optimization models will produce a cycle length by attempting to achieve a v/c level at around 0.9. By fixing this cycle length, all splits are optimized in SYNCHRO [71] with the respective volume levels. The dwell time is assumed to be discretely uniformly distributed with possible outcomes of 20, 30 and 40 seconds for each bus line with a near-side bus stop.

Table 5: Parameter Setup for Simulation Evaluations.

Background Timing: Cycle Length = 110 sec

Dwell Time Distribution: 20 sec (0.333), 30 sec (0.333), 40 sec (0.333)

Phase f1 f2 f3 f4 f5 f6 f7 f8 # of lanes 1 2 1 2 1 2 1 2 V/C = 0.5 Volume (vph) 112 616 90 381 78 784 101 280 Opt. splits (s) 23 40 20 27 19 44 21 26 V/C = 0.7 Volume (vph) 156 858 125 530 109 1092 140 390 Opt. splits (s) 22 44 17 27 16 50 19 25 V/C = 0.9 Volume (vph) 200 1100 160 680 140 1400 180 500 Opt. splits (s) 21 46 15 28 14 53 17 26

6.1.3. Signal Control Models for TSP

Signal control models dictate how a transit priority is granted. Many state-of-the-art models are too complicated to be solved in real-time, have stringent requirements, such as high market penetration rates of specialized vehicles, or cannot handle stochastic arrivals. For all practical purposes, the SMINP model is designed to be a fast solvable

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and easily implementable model. Therefore, it is more suited to compare the SMINP against some state-of-the-practice methods of providing transit signal priority.

6.1.3.1. Fixed Time Control

The fixed time control model simply implements the offline optimized green splits for each of the v/c levels. Both passenger car and bus delays generated from this control model are considered as the benchmarks for all other models to be compared with. The fixed time control do not consider bus arrival rates or actual bus arrival time in any way. So it can be think of an optimized signal control without TSP. So for any other models with a TSP component, it is expected their passenger car delays will be higher than that observed in this control model, especially when the level of congestion is closer to saturation (e.g. v/c = 0.9).

6.1.3.2. RBC-TSP Control

The Ring Barrier Controller (RBC) in VISSIM [49] is a unified signal control emulator, which has implemented many of the most significant features of a real-world signal controller. Therefore, although it is not developed to exactly replicate the interface of a certain signal control model, its features are realistic enough to represent the existing functionalities of a typical modern signal controller.

The RBC uses a pair of check-in and check-out detectors to enable its TSP feature, namely RBC-TSP control model. Upon the detection of a bus at the check-in detector, a constant travel time with a constant slack time is applied to estimate its arrival time

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interval at the stop bar and performs either green extension or red truncation. With a nearside bus stop, the check-in detector is recommended to be placed at the exit of the bus stop [49] or to be coupled with a detector for door closing. This way, the need to account for the random dwell time is eliminated. In fact, there is no control parameter to allow a wider range of arrival time than a few seconds. So putting the check-in detector before the near-side bus stop will almost guarantee a failed TSP implementation. Therefore, in the comparison study, there is no choice but to place the check-in detector at the exit of the bus stop.

It is possible to enable the fully actuated control module within the RBC controller. But we are interested in the ability and limitation of the check-in-and-check-out TSP strategy furnished by the RBC controller, not its performance in actuated control. So as not to confusticate the comparison, we used the RBC controller in a fixed-time mode by setting max-recalls on all phases.

6.1.3.3. SMINP Control

The SMINP model is implemented in the simulation testbed as described in section 5 and the flow of signal control is completely illustrated in Figure 21. In the preliminary study, as in section 6.2, four variations of the SMINP model were developed but one is selected to compare with the fixed-time and RBC-TSP control models in section 6.3. In both cases, a uniform distribution was observed for bus dwell time. The optimization performed once when a bus come into the range of the intersection. But if there is more than one bus within the communications range, the most recently entered bus will be the

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one which initiate an optimization session that includes all buses. The new timing will be carried out until the end of the planning horizon or when another bus comes into range. The SMINP control in section 6.4 is exactly the same except the dwell time distribution is different.