Method to schedule intelligent traffic lights in real time based on digital infochemicals

Abstract

A method to schedule intelligent traffic lights in real time based on digital infochemicals (DIs) is disclosed. The method takes advantage of DIs as medium to both predicate traffic flow and smooth the green/Cycle (g/C) ratio. First collect DIs, then update DIs by three actions including aggregation, evaporation, and propagation. After that, adjust the g/C ratio of the traffic light. DIs have the function of prediction due to the propagation that allows DIs reach the traffic earlier than the real traffic flow. On the other hand, DIs have the function of memory due to the evaporation that remembers the information of the historical traffic flow. The prediction and memory of DIs, as the reason why DIs are superior to the pure traffic flow, give the DI-based intelligent traffic light compelling advantages over the pure traffic based intelligent traffic light.

Claims

1. A method to schedule intelligent traffic lights in real time based on digital infochemicals, DIs, wherein comprising the following steps: step 1, collect digital infochemicals according to the target requirements, a road is split into several cells; at time tick t, the traffic light system automatically collects the DIs generated by the traffic flow in each cell, and then updates the DIs through three processes, i.e., aggregation, evaporation, and propagation; said aggregation refers to the accumulation of DIs generated by different vehicles within the same cell;
.sub.i,t=.sub.i,t1+n.sub.i,t(1) where, .sub.i,t1 is number of DIs in the ith cell at time t1; n.sub.i,t is the number of vehicles in the ith cell at time t; .sub.i,t is the updated number of DIs in the ith cell at time t; said evaporation refers to the gradual deduction of DIs along with time going:
.sub.i,t.sup.=(1.sub.v).sub.i,t(2) where, .sub.i,t is the number of DIs in the ith cell at time t; .sub.v is the evaporation rate; .sub.i,t.sup.is the number of DIs left after evaporation; said propagation refers to that the DIs propagate to the neighboring areas along with the driving direction of vehicles:
.sub.i,t.sup.=(1.sub.p).sub.i,t.sup.(3) where, .sub.i,t.sup.is the number of DIs left after evaporation; .sub. is the propagation rate, i.e., the percentage of DIs propagated to the neighboring areas; .sub.i,t.sup.the number of DIs left after propagation; under synchronized update, the DIs in all the cells propagate simultaneously, and then receive the DIs propagated from other cells: $\begin{array}{cc}{}_{i,t}^{}={}_{i,t}^{}+\underset{j}{.Math.}{}_{j,t}^p& \left(4\right)\end{array}$ where, is the set of upstream cells whose DIs are propagated to the ith cell; .sub.j,t.sup. is the DIs propagated from the jth cell and sprayed to the passed cells evenly; $\begin{array}{cc}{}_{j,t}^p=\frac{{}_p{}_{j,t}^{}}{v/C_s}& \left(5\right)\end{array}$ where, .sub.j,t.sup.is the DIs left after evaporation; .sub..sub.j,t.sup.is the total DIs propagated to the neighboring areas; v is the speed for propagation; is the unit time length; v is the length that the DIs are able to propagate within time ; C.sub.S is the length of cell; v/C.sub.S is the number of cells that the DIs pass during propagation within time ; step 2, adjust Green/Cycle, g/C, ratio assume t to be the beginning time of a signal cycle, i.e., mod(t,T.sub.c)=0, then the traffic signal light adjusts the g/C ratio for the next signal cycle according to the number of DIs on the adjacent roads of an intersection in the current cycle: $\begin{array}{cc}{T}_i^G=\frac{D_i}{\underset{j}{.Math.}{D}_j}{T}_C& \left(7\right)\end{array}$ where, T.sub.i.sup.G is the green duration of the ith phase; D.sub.i is the number of DIs on the roads corresponding to the ith phase; .sub.jD.sub.j is the total number of DIs on all the roads of an intersection; T.sub.C is the cycle length; if t is not the beginning time of a signal cycle, then follow Step 1 to collect the DIs for the t+1 time; such a process forms an infinite loop and keep updating.

2. The method to schedule intelligent traffic lights in real time based on digital infochemicals according to claim 1, wherein the transportation simulation model utilizes discrete time strategy with 1 second as time step and 1 meter as the length of each cell; Equation 5 is simplified as: $\begin{array}{cc}{}_{j,t}^p=\frac{{}_p{}_{j,t}^{}}{v}.& \left(6\right)\end{array}$

Description

DESCRIPTIONS OF THE DRAWINGS

(1) FIG. 1 The framework of the traffic light based on Dis.

(2) FIG. 2 The real-time scheduling flow chart of the DIs-based traffic light.

(3) FIG. 3 The illustration of DIs on the road.

(4) FIG. 4 The illustration of DIs at the intersection.

(5) FIG. 5 The traffic changes on a main road.

(6) FIG. 6 The comparison of three traffic signaling strategies; (a) Boxplot of average waiting time, (b) Boxplot of average queuing length.

DETAILED DESCRIPTION

(7) Have a two-way three-lane road as an example, shown in FIG. 3. The DIs are generated by the passing vehicles. Discrete time simulation is applied to exactly track the trajectory of vehicles, that is, updating the positions of vehicles in a specified time interval. Without loss of generality, the time interval is one second, that is, updating the positions of vehicles every second. Considering the fact that the nearby DIs have similar impacts on the traffic light, a road is split into cells with the same length, in which the DIs aggregate as a whole. Such a discrete strategy is beneficial to reduce computing workloads. The length of a cell in the following example is 10 meters.

(8) Assume there are 2 vehicles in cell C.sub.S,1 at time 0, then the DIs .sub.S,1 is 2.

(9) Firstly, consider evaporation with the evaporation rate .sub.v of 0.2/s that indicates 20% of DIs are evaporated every one second. Then .sub.S,1 changes to 1.6.

(10) Next, consider propagation with the propagation rate .sub. of 0.3/s that indicates 30% of DIs diffuse to the downstream road. Then .sub.S,1 changes to 1.12.

(11) Assume that the propagation speed is the same as the vehicles' traveling speed, i.e., 100 km/hr=28 m/s, which means the DIs propagate by 28 meters every second that is equivalent to 3 cells. The DIs propagated spray into the adjacent 3 cells evenly, i.e., C.sub.4,1, C.sub.3,1, C.sub.2,1, and the DIs in each cell are increased by 1.6*0.3/3=0.16.

(12) Cell C.sub.5,1 also accepts the DIs propagated from the upstream 3 cells. Assuming the DIs propagated from cell C.sub.6,1, C.sub.7,1, C.sub.8,1 are 0.1, 0.21, 0.08, respectively, .sub.5,1. finally changes to 1.12+0.1+0.21+0.08=1.51 at time 0.

(13) Assuming there are 3 vehicles in cell C.sub.5,1 at the next time, i.e., time 1, the DIs in the cell increase from the base 1.51 by 3, that is 4.51.

(14) Firstly, consider evaporation with the evaporation rate .sub.v of 0.2/s that indicates 20% of DIs are evaporated every one second. Then .sub.S,1 changes to 3.608.

(15) Next, consider propagation with the propagation rate .sub. of 0.3/s that indicates 30% of DIs diffuse to the downstream road. Then .sub.S,1 changes to 2.5256. The DIs propagated spray into the adjacent 3 cells evenly, i.e., a, C.sub.4,1, C.sub.3,1, C.sub.2,1, and the DIs in each cell are increased by 3.608*0.3/3=0.3608.

(16) From what described above, the DIs on the road follow the same rule, that is, unlimitedly iterate aggregation, evaporation, and propagation, during which the number of DIs is updated dynamically with the real-time traffic flow. The intelligent traffic light introduced in this invention adjusts the phase duration of the traffic light based on the updated DIs so as to reduce congestion.

(17) Considering the intersection as shown in FIG. 4, .sub.1, .sub.2, .sub.3, .sub.4 are the DIs on the four adjacent roads of the intersection. To simplify computing complexity, here only vehicles that move straight are taken into account. According to Eq. 7, we can compute the green phase duration for the west-east road is

(18) $T_G^{\mathrm{WE}}=T_R^{\mathrm{NS}}=\frac{{}_2+{}_4}{{}_1+{}_2+{}_3+{}_4}{T}_C,$
where, T.sub.G.sup.WE and T.sub.R.sup.NS are the green phase duration for the west-east and red phase duration for the north-south road, respectively. T.sub.C is a controlling cycle of the traffic light. The green phase duration for the north-south road is

(19) $T_G^{\mathrm{NS}}=T_R^{\mathrm{WE}}=\frac{{}_1+{}_2}{{}_1+{}_2+{}_3+{}_4}{T}_C.$

(20) To evaluate the performance of the DIs-based traffic light, compare it to the traffic light controlled by fixed scheduling strategy and by trigger-based strategy. Fixed scheduling strategy predefine the phase durations according to historical traffic data, and keeps the phase duration unchanged once set up. The trigger-based strategy means that the traffic light on the main stream road keeps green during a signaling cycle until there are vehicles waiting on the road with relatively lower traffic. Then the traffic light on the road with relatively lower traffic changes to green for a certain period. The trigger-based strategy is designed to prioritize the traffic on the main stream road.

(21) To compare these three traffic light scheduling strategies, the real traffic demand with peak hours is used as the testing data, as shown in FIG. 5. Each scheduling strategy is run 10 times, and then compare the generated average waiting time and average queuing length, as shown in FIG. 6. From the figure it is easy to observe that the DI-based scheduling strategy leads to shorter waiting time and short queuing length than the other two scheduling strategies.