Disclosure of Invention
The invention provides an intelligent control method of a crossroad traffic signal lamp based on a time-varying domain, which comprises the following steps:
step S1: collecting required traffic data by using a detector at an intersection;
step S2: evaluating the congestion degree of the intersection by using the obtained data and taking the maximum queuing length in the phase of the current green light direction and the queuing length data in each phase of the current red light direction as the basis to obtain the domain of cycle length under the current traffic flow condition;
step S3: listing a dynamic fuzzy rule by taking the current period length as a domain of discourse, taking the maximum queuing length on the current green light direction phase and the average parking times of each vehicle as input, and taking the green light time length distributed by the current green light direction phase as output;
step S4: performing clearness calculation by using a gravity center method to obtain the duration of a green light;
step S5: and judging the obtained green light time length, setting constraint conditions and finishing the timing scheme.
Wherein the step S1 is further: the required traffic data comprises the maximum queue length gL in the phase of the current green light direction and the queue length rL in each phase of the current red light direction
jAnd average number of stops per vehicle
The average stopping times of each vehicle are the average times of the vehicles which exit the intersection in the current green light direction phase and meet the red light.
Wherein the step S2 further comprises the steps of:
step S21: the proper range of the period length c is 40-180 s, the domain of the period length is set to be omega (t), and the domain of the period length c under the time-varying domain is divided into continuous time-varying domain sequences: { omegak(t)},(k∈N),Ωk(t)=[0,40+20k]Wherein k is 1, 2.. 6, 7;
step S22: and evaluating the congestion degree of the intersection according to the average queuing length item in red light in the level-4 service level suggested by the Beijing city planning and design institute. According to its proposed level 4 service level, a queue length L at red light of less than 50 meters is unobstructed VS, between 50 meters and 100 meters is unobstructed NS, between 100 meters and 150 meters is congested NJ, over 150 meters is congested VJ; the obtained gL and rLjThe digital form of the data, according to the proposed level 4 service level, is converted into the form of words VS, NS, NJ, VJ;
step S23: and obtaining the discourse domain of the cycle length under the current traffic flow condition according to the combination condition of the base words.
Wherein the step S3 further comprises the steps of:
step S31: the input gL,
Output quantity T
lFuzzification;
step S32: the cycle length discourse domain is a continuous time-varying discourse domain sequence: { omega
k(t) }, (k ∈ N), a membership function that defines a fuzzy set over the domain of interest as it changes over timeAlso, changes occur with time, respectively at each omega
k(t) input quantities gL and rL are set
jAnd an output amount
Membership function corresponding to each linguistic value;
step S33: considering all possible cases, listing the argument field of the period length to be omega under the time-varying argument fieldkDynamic fuzzy rule R at (t)k。
Wherein the step S4 further comprises the steps of:
step S41: solving a fuzzy relation matrix R by a dynamic fuzzy ruleiThe overall fuzzy rule is R;
step S42: obtaining a fuzzy set corresponding to the output variable according to the total fuzzy relation and the reasoning and synthesizing rule;
step S43: and converting the fuzzy quantity obtained by fuzzy reasoning into a clear quantity in the current theoretical domain, and carrying out clear calculation to obtain the green light duration.
Wherein the step S5 further comprises the steps of:
step S51: comprehensively considering intersection traffic flow and driver traffic safety, relieving traffic jam and reducing red light running phenomena, setting reminding, and if the red light duration of a certain phase exceeds 130s, receiving reminding 1 by a system;
step S52: when the system receives the prompt 1, the system adjusts the passing time of the current green light phase according to the predicted change trend of the traffic flow through the prediction of the short-time traffic flow;
step S53: t isl≤Nmax,NmaxSetting the maximum value of the passing time according to the traffic flow of the actual intersection, setting the value not to exceed 80s, setting a prompt, and if the duration of the green light exceeds NmaxThen the system receives reminder 2;
step S54: and when the system receives the prompt 2, adjusting the current green light phase passing time, and setting the current green light phase passing time as the maximum value of the passing time.
The invention has the beneficial effects that: by dynamically adjusting the period length of the traffic lights and distributing the length of the green light time in real time, the number of vehicles passing through the intersection is increased, the maximum queuing length and the average queuing length are reduced, the average delay of each time interval is reduced, and the timing scheme effectively relieves the intersection congestion.
Detailed Description
The present invention will be described in detail below with reference to the attached drawings, and it should be noted that the described embodiments are only intended to facilitate understanding of the present invention, and do not have any limiting effect thereon.
The invention provides a real-time timing method for traffic lights at an intersection. As shown in fig. 1, in particular, the method comprises the steps of:
step S1: collecting required traffic data by using a detector at an intersection;
the data to be collected by the method comprises the maximum queue length gL in the phase position of the current green light direction and the queue length rL in each phase position of the current red light direction
jAnd average number of stops per vehicle
The average stopping times of each vehicle are the average times of the vehicles which exit the intersection in the current green light direction phase and meet the red light.
Step S2: evaluating the congestion degree of the intersection by using the obtained data and taking the maximum queuing length in the phase of the current green light direction and the queuing length data in each phase of the current red light direction as the basis to obtain the domain of cycle length under the current traffic flow condition, wherein the flow chart of the process is shown in FIG. 2;
step S22: and evaluating the congestion degree of the intersection according to the average queuing length item in red light in the level-4 service level suggested by the Beijing city planning and design institute. According to its proposed level 4 service level, a queue length L at red light of less than 50 meters is unobstructed VS, between 50 meters and 100 meters is unobstructed NS, between 100 meters and 150 meters is congested NJ, over 150 meters is congested VJ; the obtained gL and rLjThe digital form of the data, according to the proposed level 4 service level, is converted into the form of words VS, NS, NJ, VJ;
step S23: obtaining a discourse domain of the cycle length under the current traffic flow condition according to the combination condition of the base words; taking four-phase control at an intersection as an example, fig. 3 shows. The four-phase base word combination has 35 cases, when the base word combination form is VS, VS// VS, NS, the cycle length domain is omega1(t); the cycle length domain is omega when the combination is VS, NJ// VS, VJ// VS, NS// VS, NS, NJ// VS, NS, VJ// VS, NJ, VJ2(t); and analogizing in turn to obtain the corresponding length discourse domain under each combination condition of the base words.
Step S3: under the cycle length domain, taking the maximum queuing length in the phase of the current green light direction and the average parking times of each vehicle as input, taking the green light time length distributed by the phase of the current green light direction as output, and listing dynamic fuzzy rules;
step S31: the input gL,
Output quantity T
lFuzzification of (1); the range of variation of gL is determined from experience with actual traffic control. Setting the variation range of the input quantity gL as 0-200, the domain of discourse as {0,1,2,3,4,5,6,7,8,9,10}, defining 7 fuzzy subsets on the domain of discourse, and setting the corresponding language value as { l }
1(very short), l
2(short,. l)
3(shorter,. l)
4(intermediate) l
5(longer,. l)
6(length,. l)
7(very long) }; set the input quantity
The variation range of (1) is 0-4, the domain of discourse is {0,1,2,3,4,5}, 5 fuzzy subsets are defined on the domain of discourse, and the corresponding language value is { n }
1(small), n
2(smaller), n
3(intermediate), n
4(larger), n
5(large) }; setting output T
lIs 0 to 40+20k, k is 1,2,3,4,5,6,7, the domain of discourse is {0,1,2,3,4,5,6,7,8,9,10} and defines 5 fuzzy subsets on the domain of discourse, the corresponding linguistic value is { t } t
1(short), t
2(shorter), t
3(intermediate), t
4(longer), t
5(long) };
step S32: the cycle length discourse domain is a continuous time-varying discourse domain sequence: { omega
k(t) }, (k ∈ N), when the domain of discourse changes with time, the membership function of the fuzzy set defined on the domain of discourse also changes with time, and is respectively at each omega
k(t) the input quantity gL,
Output quantity T
lThe membership function corresponding to each linguistic value; FIG. 4 shows that the domain of the current cycle length is Ω
1(t) and Ω
2(t) inputting membership functions corresponding to the linguistic values of the quantity gL; FIG. 5 shows that the clock domain is Ω
3(t) and Ω
4(t) inputting membership functions corresponding to the linguistic values of the quantity gL; similarly when the cycle length is argued as Ω
5(t)、Ω
6(t) and Ω
7(t), the membership functions corresponding to the linguistic values of the input quantity gL are similar to those in fig. 4 and 5, respectively; similarly, an input quantity is defined
Output quantity T
lAt each omega
k(t) membership functions corresponding to the linguistic values;
step S33: considering all possible cases, listing the argument field of the period length to be omega under the time-varying argument fieldkDynamic fuzzy rule R at (t)k。
Step S4: performing clearness calculation by using a gravity center method to obtain the duration of a green light;
step S41: by dynamic stateFuzzy rule solving fuzzy relation matrix R
iThe overall fuzzy rule is R; in the syntax of the fuzzy language, the rules are expressed in a schema of if (rule antecedent) then (conclusion). Each language control rule corresponds to a fuzzy relation r
i k=(l
i×n
i)
T×t
iThe fuzzy relation matrix R can be obtained by the fuzzy control rule
iThe overall fuzzy relationship is
Step S42: obtaining a fuzzy set corresponding to the output variables according to the total fuzzy relation and the reasoning and synthesizing rule:
step S43: and converting the fuzzy quantity obtained by fuzzy reasoning into a clear quantity in the current theoretical domain, and carrying out clear calculation to obtain the green light duration.
Step S5: and judging the obtained green light time length, setting constraint conditions and finishing the timing scheme.
Step S51: comprehensively considering intersection traffic flow and driver traffic safety, relieving traffic jam and reducing red light running phenomena, setting reminding, and if the red light duration of a certain phase exceeds 130s, receiving reminding 1 by a system;
step S52: when the system receives the prompt 1, the system adjusts the passing time of the current green light phase according to the predicted change trend of the traffic flow through the prediction of the short-time traffic flow;
step S53: t isl≤Nmax,NmaxSetting the maximum value of the passing time according to the traffic flow of the actual intersection, setting the value not to exceed 80s, setting a prompt, and if the duration of the green light exceeds NmaxThen the system receives reminder 2;
step S54: and when the system receives the prompt 2, adjusting the current green light phase passing time, and setting the current green light phase passing time as the maximum value of the passing time.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can understand that the modifications or substitutions within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.