Chapter 2 Related Work
2.2 Bus Priority
In[18], it first summarizes how bus priority at traffic signals works within iBUS(an automatic vehicle location system): When a bus is detected on the approach of a signal,
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the bus send its GPS location information to the signal, so that the signal can predict the arriving time of the bus and decide whether to extend current phase for the bus. This paper then explores the effects of GPS locational errors on bus priority benefits, and we can know the impotence of accurately predicting.
In [19],this work also decides whether to extend the current phase after receiving the request of the incoming bus. But it has considered the situation of buses to design a headway-based strategy or a schedule-based strategy. So if two or more buses request the signal different phases, the signal will meet the request with the highest priority (this not considered in [18]).
Unlike [18] and [19], some works[20] adopts a fixed cycle-time plan, it allocates time to split of each phase at the start of the cycle, and it will change its plan after receive request of bus. This method can meet multiple requirements by modifying its original plan, it can not only extend the phase, but also can make the required phase occur more early. If there are two or more requests from different buses conflict, it uses a headway-schedule bus priority to decide what changing should be taken.
In [21], it changes the signal not only based on information of buses but also information of roads and ordinary vehicles. It considers several elements: First, the remaining time until the traveling bus in the current green signal phase arrives at the stop line. Second, the waiting time duration that buses in the next green signal phase stay on red signal. Third, the ratio of the effective green signal time duration to the green signal time duration, where effective green signal time duration means the duration between vehicles arriving the stop line and pass through the stop line. Fourth, the number of vehicles in the link between the intersection and the adjacent downstream intersection, if the high number refers the downstream intersection will be possible to congest. Then it uses a fuzzy method to compare these factors and decide whether to
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extend the current phase.
Some researches focuses on reducing passengers’ waiting time for buses arriving at bus stops instead of passengers’ waiting time for signals on buses. [22] shows that greater regularity benefits could be achieved through a strategy where priority for a bus is based not only on its own headway but also the headway of the bus behind.
However, these works about bus priority have some drawbacks. First, they mostly focus on reducing bus waiting time and can’t concern about features of buses in the same time. Second, they may not consider the impact to ordinary vehicles by control signals for buses. Third, these works usually control signal with a fixed phase sequence which have little flexibility to change to the phase has highest priority due to the more vehicles or delay buses.
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Chapter 3
Adaptive Traffic Signal Control System
In this chapter, we introduce out adaptive traffic signal control system .In section 3.1, we propose our system architecture. In section 3.2 we introduce assumptions of the system.
3.1 System Overview
As shown in figure 2, intersections collect information includes the location and speed of vehicles, headway deviation and schedule delay of buses at the intersection. In order to deal with the real-time changing of traffic flow, we adopted a non-fixed phase sequence [10] at each intersection. For each intersection, when the current phase is over, we will use the information mentioned above to calculate the passenger waiting time per unit of time in the phase, bus schedule delay ratio and bus headway deviation ratio of each phase. And we use a phase demand function to calculate the phase demand value of each phase, and then we will choose the phase with the highest phase demand value and allocate enough time to the phase. When the remaining time of the phase is over, we do the above action again.
9 Headway delay
Bus i arrival time : 7:09 Bus i schedule time : 7:05
Schedule delay
Bus j-1 arrival time:7 :00
Bus i
Bus j Bus j-1
Bus j arrival time:7 :09 Normal headway:5 minutes
Passengers waiting time
Signal control
Figure 2. System architecture
The intersection model is shown in Figure 3. Each intersection has four lanes at each direction (west, east, north and south), two are approaching lanes, and two are leaving lanes. The inside lane is for left-turning vehicles, and the outside lane is for right-turning and straight-going vehicles. We install three detectors such as on each approaching lane, and they are placing in the start, middle and end of roads to detect number and speed of waiting vehicles, leaving vehicles and approaching vehicles. And we divide one lane into two areas: waiting area and forwarding area. We use the vehicles in the waiting area to determine phase length. Then we calculate passenger waiting time will be caused by vehicles has been in the waiting area and vehicles in forwarding area will arrive at waiting area then wait for the red signal. Then we calculate the bus headway deviation ration and bus headway ration of buses in the waiting area. Finally, we can determine phase demand value of each phase.
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: Detector for vehicles leaving : Detector for vehicles waiting : Detector for vehicles entering Waiting area Forwarding area
Phase1 Phase2 Phase3 Phase4
Lane1 Lane2 Lane4
Lane3
Lanr5 Lanr6 Lanr7Lanr8
(Lane1,3) (Lane2,4) (Lane5,7) (Lane6,8)
Figure 3. Intersection model
3.2 System Flow
With a non-fixed phase scheme, we should decide the phase which has higher priority to be the next phase, and allocate time to the phase. The flow chart of the system is shown in Figure 4, when the current phase is over, we will collect traffic information to calculate the necessary time of each phase first. Then we will check whether there is a phase who has not been adopted over a threshold time, and it will be selected as the next phase due to the fairness if there is overtime phase. Otherwise, we will use the information about passengers’ waiting time, headways and schedules of buses to determine the demand of each phase. After we have the demand value of phases, we select the phase has highest priority to be the next switch. Finally, we control the signal switch to the deiced phase. After the phase ends, we will repeat above actions again.
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The current phase ends
Some phase wait over threshold Calculate length of
each phase
Determine demand of each phase
N
Decide the next phase
Y
Switch to the next phase and allocate
time to it System start
Figure 4. System flowchart
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Chapter 4
System Design
We adopt non-fixed phase sequence to deal with the real-time changing of traffic flow and requests of buses, so we have to determine how long each phase should be and which phase should be selected to be next phase. The first one we can use collected data includes location and speed of vehicles to calculate necessary time of each phase, and introduced it more detail in section 4.1.The second one, we have to concern about ordinary vehicles and buses, then we select three factors to design a phase demand function. After we get the allocated time of each phase, we can calculate the first factor:
total passengers waiting time in each unit of time. Then we consider about bus regularity, we calculate the bus schedule delay ratio and bus headway ratio to be the second and third factor. After we calculate the phase demand value of each phase, the phase with highest green demand value will be selected as next phase. Section 4.2 introduces the details of phase demand determination.
4.1 Phase Length Determination
Before determining the length of each phase, we should know number of vehicles in the waiting area. As the intersection model mentioned, vehicles can pass through an
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intersection only two lanes in a phase. First, we calculate the time of dispersing all vehicles in two lanes of a phase, and we define dist( fi, ) as the distance between the stop line and the farthest vehicle in the waiting area in the two lanes of phase f at intersection i. An example of Phase1 is shown as see Figure 5.
Waiting area Forwarding area
Figure 5. Distance between stop line and the farthest vehicle of phase1
After gettingdist( fi, ), we could calculate how long can disperse the all vehicles in the waiting area of phase f . disperse_time(i,f) is defined as the time needed to disperse all vehicles of phase f at intersection i,.Where a means the acceleration of vehicles, and Vmax means the max speed of vehicles. and forwarding a distance at the Vmax speed before it arrive at the stop line ( see Figure 6).
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Travel time Travel time
a
Figure 6. Example of calculating time to disperse vehicles.
We can determine the time should allocate to each phase after we know have phase. If we didn’t set the minimum, the signals may change frequently, and this that is not acceptable for drivers.
4.2 Phase Demand Determination
To decide which phase should be selected, we calculate three factors including passengers’ waiting time, bus schedule delay and bus headway deviation. Then we use a
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phase demand function to determine the demand of each phase. And select the phase with the highest value to be the next phase.
4.2.1 Passengers’ Waiting Time
The first factor is passengers’ waiting time, and it’s also the most evaluated item of traffic signal control systems. We calculate the total passengers’ waiting time of other phases caused if a phase is adopting. We calculate the passengers’ waiting time of two types of vehicles, the first type of vehicles is the vehicle in waiting area, the other type of vehicles is the vehicle in forwarding area and will stop at waiting area for the red signal. To calculate the waiting of the second type, we defined CL(i,l,vj) as the
current location of the jth vehicle on lane l at intersection i, and PL(i,l,vj) as the location of the jth vehicle will be and stop for the red signal on lane l at intersection i.Then we can calculate the TNA(i,l,vj) as the time needed for jth vehicle arrive at vehicles, the current location and the predicted location of the vehicle in the forwarding area is shown as Figure 7. Where V is the current speed of v , and d is the j deceleration of vehicles .
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Figure 7. The current location and predicted location of the vehicle
Then we can calculate the waiting time of each vehicle for a time period.
wait is defined as the total passengers’ waiting time if phase f sustains for the red signal for a time period of T time, and the p(vj) means the number of
An example of passengers’ waiting time cumulated by a lane is shown in Figure 8.
There are i vehicles in waiting area and one vehicle in the forwarding area.
Waiting area Forwarding area location in waiting area
1
t
iAt the end of the red signal
t
0 Figure 8. Passengers’ waiting time cumulated in a lane17 total passengers’ waiting time is not effective relative to the phase has longer length. We defined wait_unit(i,f) as the total passengers’ waiting time in each unit of time if phase f is be assigned the next phase.
The previous work with non-fixed phase sequence only use the number of vehicles to decide which phase will be assigned as the next phase and time .But they don’t concern the waiting time cumulated by other vehicles at the period of allocated time and passengers on each vehicle. In our traffic signal control system, we have concerned these elements in equation (6).
In general, the phase with lower wait_unit(i,f) value will cause lower passengers’
waiting time, and the phase with higher wait_unit(i,f) will cumulate more passengers’ waiting time. If we don’t concern features of buses, we should select the phase with lower wait_unit(i,f) as the next phase, and it should have better performance compare to the previous work.
4.2.2 Bus Schedule Delay
Bus schedule of buses is an important feature, because people can use it to save the
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time at bus stops. The schedule of a bus route is always designed based on an ideal experience of the bus. But because the traffic flow changes at any time, buses always will be influenced and can’t arrive at each bus stop on the scheduled time, they may arrive at bus stops late or early compare to its scheduled time. The buses are late from its bus schedule should be benefited at intersections by control the traffic signal, and the buses is early than its schedule should have lower priority at each intersection to adjust it to close to its bus schedule.
To calculate the schedule delay, we first define schedule_arrive(i,j) as the time bus j should be in phase f at intersection i, and actual_arrive(i, j)as the actual arrival time of bus j in phase f at intersection i. Then we can calculate schedule delay of each bus. schedule_delay(i,f) is defined as the highest schedule delay of buses in phase f at intersection j. There may be more than one bus in the same phase at the intersection, and they may be late or early from its schedule, but the bus with highest schedule delay should be benefited first of all. So we select the highest schedule delay of buses in each phase to be theschedule_delay(i,f) of phase f .
4.2.3 Bus Headway Deviation
In normal situation, each bus can carry the close number of passengers and people will not wait a bus than the headway. Although each bus departures from the first bus stop in a fixed time interval, they may be delay or early than their predefined headway, and it will cause people waste much time at bus stops and make some buses carry many passengers in a delay situation.
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The headway between two buses is using the difference of the arrival time of the current bus and its preceding bus. An example is shown in Figure 9. The difference of arrival time of BusA and BusB is six minutes, and the headway is also six minutes.
Bus Stop
Headway between A and B:
6minutes
Figure 9. The headway between two buses
Buses on different bus routes travel different places, and each bus may have different number of passengers who want to take thus bus. The bus route have more passengers should have more bus travel on this bus route, thus more buses can save the waiting time of passengers at bus stops and passengers are more comfortable on a bus with less passengers. Hence, each bus route should have own headway which is suitable for this bus route.
We defined HDR( fi, ) as the headway deviation ratio of f at intersection i, where PH( j) is the predefined headway of bus j. Because each bus has different predefined schedule, we have to use a ratio to compare headway deviation of a bus with the other one. There may be more than one bus in the same phase at the intersection, and the bus with highest headway deviation ratio should be benefited than buses have lower headway deviation ratio. So we select the highest schedule delay of buses in each phase to be HDR( fi, ) of phase f .
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4.2.4 Phase Demand Function
Now, we define the phase demand function according to the above mentioned passenger waiting time, bus schedule delay ratio and bus headway deviation ratio. The phase demand function is defined as follows:
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At each intersection, if there is an overtime phase, the overtime phase will be selected.
Otherwise, the phase f with the greatest value will be assigned as the next phase.
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Chapter 5 Simulation
In this section, we evaluate the performance of ATCB by using NetLogo simulator [23] (version 4.1.3). We compare ATCB with the traditional predefined fixed-time scheme with bus priority strategy like TDTSP [19] and an adaptive fuzzy logic control (AFLC) [21].Beside bus priority, we also compare ATCB with an actuated traffic control and a non-fixed sequence control scheme [10]. The details of each scheme are described below.
We modify the TDTSP: We use a fixed sequence traffic signal control scheme and we benefit bus by extending the current phase if there is a bus can pass through the intersection by the current phase. If there are two buses on different routes meet in an intersection, we compare the headway deviation and schedule delay to decide which bus will be benefits.
Then, we modify AFLC: Like TDTSP, we also adopt a fixed sequence traffic signal control scheme and decide whether to extend the current phase or switch to next phase.
In our modification, we compare ordinary vehicles and buses of the current phase with ordinary vehicles and buses of the next phase to decide whether to extend the current phase or switch to the next phase.
Actuated traffic control method controls signals by detecting the coming vehicles.
It places sensors at a short distance near the intersection, if the sensor find there are
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vehicles will cross the intersection in a short period, it will extend the current phase until reach its maximum green time.
In a non-fixed sequence scheme, when the current phase is going to end, it will find the most suitable phase from all phases, the original scheme consider many factors, in our modification, we only focus on the number of vehicles, the phase has the biggest number of vehicles will be selected as the next phase.
We analyze the simulation results of total waiting time of vehicles, total waiting time of buses, total passengers’ waiting time, average bus schedule deviation and average bus headway deviation.
5.1 Simulation Environment
As shown in Figure 10, we perform the simulation on a network of 8×8 traditional four-direction intersections, and the length of roads is 500 meters. The length of the waiting area on each road is 200 meters, and each road has four lanes, two are approaching lanes, and two are leaving lanes. We generate the ordinary vehicles on the edge roads of the network in a rate of 10 vehicles/minutes. Each vehicle are created with a speed of 14m/s. The acceleration of vehicles is assigned as 2m/s2, it means that each vehicle will reach its limit speed in 7 second. The deceleration of vehicles is 4m/ s2. Each vehicle will keep a safe distance when it is driven. And we adopt each vehicle carry average two passengers. In this network, we set five bus routes (RouteA, RouteB, RouteC, RouteD and RouteE), each bus on different bus routes enter this map with different frequencies (predefined headway). And we let them meet at an intersection to generate a pivot intersection, the bus routes is shown in Figures 10. And passengers on each bus is assigned in a range from 10~20. We run each simulation in 2 hours. The
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detail parameter of simulation is shown in TABLE 1.
detail parameter of simulation is shown in TABLE 1.