CN105632177A - Dynamic traffic demand-oriented intersection operation efficiency change rate calculating method - Google Patents

Abstract

The invention discloses a dynamic traffic demand-oriented intersection operation efficiency change rate calculating method. Average delay time of every vehicle and queuing length are selected at the same time to represent operation efficiency of an intersection traffic flow. With the help of the mapping relation between two indexes of different management and control schemes and the traffic demand, the efficiency index change rule of one traffic demand can be determined, and the comprehensive change rate index having the emphasis on the queuing length at the peak level and the emphasis on the delay time at the flat hump level and the valley level is formed to reflect the intersection operation efficiency change rate before and after the management and control schemes. The influence of the intersection dynamic environment change can be eliminated at the first time, and the limitation of the conventional way of taking the single traffic flow operation efficiency indexes as the assessment basis is broken, and the technical support and the decision basis can be provided for the objective and righteous assessment of the advantages and the disadvantages of the combinations of different intersection management and control schemes.

Description

A kind of crossing operational efficiency rate of change computational methods towards dynamic traffic demand

Technical field

The present invention relates to a kind of crossing operational efficiency rate of change computational methods towards dynamic traffic demand, for the computational methods to the operational efficiency rate of change under the difference time-space distribution distribution measure of specific crossing, belong to intelligent transportation research field.

Background technology

The change of the crossing operational efficiency under evaluation dynamic traffic demand scientifically and rationally, contribute to quantifying the implementation result of more various traffic organization and signal time distributing conception, objectively and fairly evaluate crossing time-space distribution service efficiency, provide decision-making foundation for optimizing management and control measure further.

Conventional crossing operational efficiency evaluation index has average traffic delay, queue length, queuing number of times etc. These evaluation indexes under specific transport need, i.e. traffic conditions, can only assess the operational efficiency of crossing. Transport need and management and control measure combined effect affect the operational efficiency of crossing, the dynamic environment of urban transportation, especially dynamic transport need environment has not reproducible very by force, the change of intersection traffic demand before and after New Measure or new departure enforcement is generally ignored in conventional evaluation methodology, and its evaluation result can exist relatively large deviation. Therefore, in order to accurately weigh crossing operational efficiency change, objective, just evaluation crossing management and control scheme implements crossing, front and back operational efficiency rate of change, in the urgent need to proposing a kind of traffic mouth traffic efficiency rate of change computational methods that can reject intersection traffic factors influencing demand.

Summary of the invention

It is an object of the invention to provide a kind of crossing operational efficiency rate of change computational methods towards dynamic traffic demand. The core concept of the method is the operational efficiency simultaneously selecting average traffic delay and queue length to characterize intersection traffic stream, mapping relations by two indices under different management and control schemes with transport need, determine the efficiency index Changing Pattern under a certain transport need, construct that queue length is laid particular stress on a peak, flat ebb stresses the comprehensive rate of change index of delay time at stop and totally reflects the crossing operational efficiency rate of change before and after management and control scheme.

For realizing above-mentioned target, the crossing operational efficiency rate of change computational methods towards dynamic traffic demand that the present invention proposes include: calculate average traffic delay and the queue length of each track group traffic flow of crossing, define the mapping relations of delay time at stop and queue length and traffic flow, definition aggregative indicator and weight coefficient, and determine, according to the mapping relations of delay time at stop, queue length and traffic flow and comprehensive rate of change weight coefficient, the crossing operational efficiency rate of change rejecting transport need impact, relative analysis scheme implement before and after effect.

The basic step of the present invention is as follows:

The traffic flow of each track group, i.e. transport need amount in c1, statistics different periods, and average traffic delay and queue length index is calculated with track group for elementary cell;

Under c2, the different management and control scheme of calculating, the rate of change of average traffic delay and queue length corresponding to each transport need interval;

C3, definition characterize the comprehensive rate of change of packet that crossing operational efficiency changes, and calculate the weight coefficient of queue length and average traffic delay in aggregative indicator;

C4, with crossing flow for weight, it is determined that management and control scheme implement before and after crossing operational efficiency rate of change.

The process of step c1 includes:

C11, with 15min for interval, with there is identical signal timing dial track for a track group, add up track group transport need amount q, intersection signal cycle duration c, phase place long green light time g, phase place red light duration r, supersaturation duration T_c; Demarcate section jam density k_jam, start wave-wave speed v_p;

C12, track group i for crossing j, calculate average traffic delay D_i,jWith queue length L_i,j;

1. transition function model is utilized to calculate average traffic delay:

$D_{i,j}=\left\{\begin{array}{cc}\frac{c_j{(1-g_{i,j}/c_j)}^2}{2(1-q_{i,j}/S_{i,j})}+\frac{N_{i,j}}{C_{i,j}}& \mathrm{\&chi;}<1\\ \frac{r_{i,j}}{2}+\frac{N_{i,j}}{C_{i,j}}& {\mathrm{\&chi;}}_{i,j}\&GreaterEqual;1\end{array}\right.$

Wherein:

$N_{i,j}=\left\{\begin{array}{cc}\frac{c_{j}T}{4}\left(\right({\mathrm{\&chi;}}_{i,j}-1)+\sqrt{{({\mathrm{\&chi;}}_{i,j}-1)}^2+\frac{12({\mathrm{\&chi;}}_{i,j}-{\mathrm{\&chi;}}_0)}{C_{i,j}\&CenterDot;t}})& {\mathrm{\&chi;}}_{i,j}>{\mathrm{\&chi;}}_0\\ 0& {\mathrm{\&chi;}}_{i,j}\&le;{\mathrm{\&chi;}}_0\end{array}\right.$

In formula: D_i,jThe average traffic delay (s/pcu) of wagon flow corresponding to the group i of j track, crossing; c_jCycle duration (s) for crossing j; g_i,jThe long green light time (s) of phase place corresponding to the group i of j track, crossing; q_i,jTransport need amount (pcu/s) for j track, crossing group i; S_i,jFor the saturation volume (pcu/s) of j track, crossing group i, generally can be taken as 0.5; N_i,jFor j track, the crossing group i initial queue vehicle number (pcu) at the green light initial stage; C_i,jThe traffic capacity (pcu/s) for j track, crossing group i; ��₀For saturation threshold value; ��_i,jFor the saturation of j track, crossing group i, for q_i,jWith C_i,jRatio; C_i,jAnd ��₀Computing formula be:

$C_{i,j}=S_{i,j}\&CenterDot;\frac{g_{i,j}}{c_j}$

${\mathrm{\&chi;}}_0=0.67+\frac{S_{i,j}\&CenterDot;(g_{i,j}-I_{i,j})}{600}$

In formula, I_i,jCorresponding to the group i of j track, crossing, the copper sulfate basic of phase place, can be taken as 3s.

2. traffic shock wave Theoretical Calculation queue length L is utilized_i,jWith queuing intensity ��_i,j:

$L_{i,j}=\frac{v_s\&lsqb;(c_j\&CenterDot;q_{i,j}-g_{i,j}\&CenterDot;S_{i,j})T_c+v_p\&CenterDot;r_{i,j}\&CenterDot;k_{jam}\&CenterDot;c_j\&rsqb;}{k_{jam}\&CenterDot;c_j(v_s-v_p)}$

${\mathrm{\&eta;}}_{i,j}=\frac{L_{i,j}}{l_i}$

In formula, L_i,jThe queue length (m) of wagon flow corresponding to the group i of j track, crossing; v_sFor startup wave-wave speed (m/s) of wagon flow, definite value; k_jamFor the density of blocking up (pcu/m) of wagon flow, definite value; v_pFor the stop wave velocity of wave (m/s) of wagon flow, available q_i,jWith k_jamRatio approximate evaluation; T_cFor supersaturation persistent period (s), if supersaturation does not occur, T_cValue be 0; ��_i,jThe queuing intensity of wagon flow corresponding to the group i of j track, crossing; l_iThe length (m) in section corresponding to the group i of j track, crossing.

C13, with 15min be interval, the average traffic delay D that is weight calculation crossing j with the transport need of track group_j:

$D_j=\frac{\underset{n=1}{\overset{N}{\&Sigma;}}{D}_{n,j}\&CenterDot;q_{n,j}}{\underset{n=1}{\overset{N}{\&Sigma;}}{q}_{n,j}}$

In formula, N is the track group number of crossing j.

C14, with 15min be interval, with the queuing intensity of track group for index calculate crossing queuing intensity ��_j;

${\mathrm{\&eta;}}_j=\underset{n=1}{\overset{N}{\&Sigma;}}\frac{{\mathrm{\&eta;}}_{n,j}^2}{\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&eta;}}_{n,j}}$

The process of step c2 includes:

C21, the traffic demand data utilizing each period and calculated average traffic delay and queuing intensity, it is determined that the mapping relations of three.

1. by the packet method in statistics, according to fixed interval, transport need being divided into some intervals, transport need amount in each interval, average traffic delay and queuing intensity data renumber; The computing formula of interval sum K and gap size �� is;

K=1+3.322lgM

$\mathrm{\&omega;}=\frac{q_{max}-q_{min}}{1+3.3lgM}$

In formula, M is that the point incuring loss through delay (queuing intensity) and flow corresponding relation is to number; q_maxAnd q_minThe respectively maximum transport need amount in survey data and minimum transport need amount (pcu/h).

2. the operational efficiency in this flow rate zone is characterized with queuing intensity and the arithmetic mean of instantaneous value of delay time at stop in often group data; For crossing j, intersection delay time and queuing strength calculation formula in kth flow intervals be:

$D_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{D}_{k,j,x}$

${\mathrm{\&eta;}}_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j,x}$

In formula, D_k,j,xFor x-th point in j kth interval, crossing to corresponding average traffic delay (s); ��_k,j,xFor x-th point in j kth interval, crossing to corresponding queuing intensity.

C22, for crossing j, represent the two sets of plan successively implemented respectively with m and m+1, then in kth flow rate zone, the average traffic delay variable quantity D' of two sets of plan_k,jWith queuing Strength Changes amount �� '_k,jIt is respectively as follows:

$D_{k,j}^{\&prime;}=D_{k,j}^{m+1}-D_{k,j}^m$

${\mathrm{\&eta;}}_{k,j}^{\&prime;}={\mathrm{\&eta;}}_{k,j}^{m+1}-{\mathrm{\&eta;}}_{k,j}^m$

In formula,WithRespectively crossing j average traffic delay (s) under m+1 scheme and m scheme;WithRespectively crossing j queuing intensity under m+1 scheme and m scheme.

C23, for transport need interval k, utilize interval intermediate value q_k,jAs the transport need eigenvalue in this interval, and calculate the rate of change of the delay time at stop within the scope of whole transport need and queuing intensity as weight index; Crossing j is the scheme m+1 delay index mean change amount �� D relative to scheme m in kth transport need interval_k,jWith queuing intensity index mean change amount �� ��_k,jIt is respectively as follows:

${\mathrm{\&Delta;D}}_{k,j}=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{D}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

${\mathrm{\&Delta;\&eta;}}_{k,j}=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

In the kth transport need interval of c24, j crossing, the scheme m+1 delay index average rate of change relative to scheme mWith the queuing intensity index average rate of changeComputing formula be:

${\mathrm{\&gamma;}}_{k,j}^D=\frac{{\mathrm{\&Delta;D}}_{k,j}}{D_{k,j}^m}$

${\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}=\frac{{\mathrm{\&Delta;\&eta;}}_{k,j}}{{\mathrm{\&eta;}}_{k,j}^m}$

The process of step c3 includes:

C31, crossing operational efficiency to consider from two aspects of both macro and micro; Macroscopic aspect mainly considers the queuing intensity of crossing, and microcosmic point is considered as the average traffic delay of crossing, and comprehensive rate of change index should take into account queuing intensity and average traffic delay; For crossing j, the comprehensive rate of change �� of crossing operational efficiency in kth transport need interval_i,jFor:

${\mathrm{\&psi;}}_{k,j}=-(1-{\mathrm{\&alpha;}}_{k,j}){\mathrm{\&gamma;}}_{k,j}^D-{\mathrm{\&alpha;}}_{k,j}{\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}$

In formula, ��_k,jFor the queuing intensity weight coefficient in j kth flow rate zone in crossing in aggregative indicator.

C32, transport need interval k for crossing j, utilize interval intermediate value as the traffic characteristic value in this interval, and with this eigenvalue calculation weight coefficient ��_k,j��

1. at offpeak period, queuing intensity is only small, and the probability that can affect upstream intersection traffic stream properly functioning is very low, and now comprehensive rate of change index is mainly considered as crossing average traffic delay; Along with being continuously increased of traffic flow, queuing intensity becomes big, and the probability affecting upstream intersection traffic stream operation is also gradually increased, and when traffic flow increases to a certain degree, comprehensive rate of change should consider emphatically the intensity of on average queuing up of crossing; Under this theory, the queuing strength factor computing formula in the comprehensive rate of change index of crossing is:

${\mathrm{\&alpha;}}_{k,j}=\frac{1}{1+e^{-b_j({\mathrm{\&eta;}}_{k,j}-{\mathrm{\&mu;}}_j)}}$

In formula, b_jAnd ��_jIt is two model parameters, it is necessary to demarcate.

2., when the saturation of crossing is less than 1, the long green light time in each cycle all has to a certain degree has more than needed, and index now need not consider queuing intensity; The saturation queuing intensity equal to 1 is in index to start to consider as a whole and queues up and the minimum threshold of delay time at stop; The time headway assuming that vehicle is saturated when discharging is h, then start to consider the minimum threshold queued up with the delay time at stop as a wholeComputing formula be:

${\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\frac{g_{i,j}\&CenterDot;S_{i,j}\&CenterDot;h}{l_{i,j}}$

3. when the queuing intensity of crossing is equal to 0.5, should the rate of change of waiting lines's intensity and delay time at stop the two different aspects on an equal basis; Meanwhile, according to 3 �� principles in mathematical statistics, aggregative indicator only considering, the queuing intensity threshold of vehicle delay time at stop is ��_j-3 ��; Owing to the span of queuing intensity is (0,1), ��_jThe lower limit value that value is 0.5,3 �� be 0.00125; Therefore, parameter b_jComputing formula be:

$b_j=\frac{\ln 799}{0.5-{\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j}$

The process of the c4 of step includes:

Transport need for crossing j is interval, it is possible to use interval intermediate value q_k,jAs the transport need eigenvalue in this interval, and calculate the comprehensive rate of change within the scope of whole transport need as weight index; The scheme m+1 operational efficiency comprehensive rate of change in crossing relative to scheme m is:

${\stackrel{\&OverBar;}{\mathrm{\&psi;}}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{U}_j\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

The rate of change drawn on the occasion of, illustrate that operational efficiency is promoted, changing value is negative value, illustrates that operational efficiency declines.

Beneficial effects of the present invention: the present invention proposes a kind of crossing operational efficiency rate of change computational methods towards dynamic traffic demand, eliminate the impact of crossing dynamic traffic changes in demand first, break traditional only with single traffic flow operational efficiency index for assessing the limitation of foundation, provided technical support and decision-making foundation for objective, the just crossing operational efficiency evaluated under the difference management and control strategy combination of crossing.

Accompanying drawing explanation

Fig. 1 calculates process flow diagram flow chart

Fig. 2 flow rate zone divides schematic diagram

Efficiency index contrast schematic diagram under the change of Fig. 3 dynamic environment

The comprehensive rate of change weight coefficient of Fig. 4 calculates figure

Detailed description of the invention

Below in conjunction with accompanying drawing, the invention will be further described

The traffic flow of specific crossing j for certain city, calculates the crossing operational efficiency rate of change under former and later two management and control measures, referring to Fig. 1.

1. calculate crossing mean delay time and the queuing intensity of each period

(1), data are gathered

Gather the crossing mean delay time in each period and the traffic flow data needed for queuing intensity: the traffic flow q of track group i_i,j; Peg model there is related parameter: start wave-wave speed v_p, the saturation volume S of track group i_i,j; Signal timing dial parameter required in investigation model: the phase place red light duration r of wagon flow corresponding to the group i of track_i,j, wagon flow corresponding to the group i of track supersaturation duration T_i,j, long green light time g_i,j, and signal period duration c_j.

(2) delay time at stop of each track group traffic flow in each period is calculated

1. the saturation threshold value in the saturation of each period and transition function is calculated:

$x_{i,j}=\frac{q_{i,j}}{S_{i,j}\&CenterDot;(g_{i,j}-I_{i,j})}$

$\tilde{x}=0.67+\frac{S_{i,j}\&CenterDot;(g_{i,j}-I_{i,j})}{600}$

2. supersaturation period T is calculated_i,jIn, the traffic capacity of track group i:

$C_{i,j}=\frac{g_{i,j}\&CenterDot;S_{i,j}}{c_{i,j}}$

3. supersaturation period T is calculated_i,jIn, track group i opens the initial queue length value in bright moment at each cycle green light:

$N_{i,j}=\left\{\begin{array}{cc}\frac{c_j{T}_{i,j}}{4}\left(\right(x_{i,j}-1)+\sqrt{{(x_{i,j}-1)}^2+\frac{12(x_{i,j}-x_0)}{C_{i,j}\&CenterDot;t}})& x_{i,j}>{\mathrm{\&chi;}}_x\\ 0& x_{i,j}\&le;{\mathrm{\&chi;}}_0\end{array}\right.$

4. transition function is utilized to calculate the vehicles average delay time of different tracks group:

$D_{i,j}=\left\{\begin{array}{cc}\frac{c_j{(1-g_{i,j}/c_j)}^2}{2(1-q_{i,j}/S_{i,j})}+\frac{N_{i,j}}{C_{i,j}}& x_{i,j}<1\\ \frac{r_{i,j}}{2}+\frac{N_{i,j}}{C_{i,j}}& x_{i,j}\&GreaterEqual;1\end{array}\right.$

5. the vehicles average delay time of crossing in each period is estimated:

$D_j=\frac{\underset{i=1}{\overset{I}{\&Sigma;}}{D}_{i,j}\&CenterDot;q_{i,j}}{\underset{i=1}{\overset{I}{\&Sigma;}}{q}_{i,j}}$

(3) the queuing intensity of each track group traffic flow in each period is calculated

1. traffic shock wave theory is utilized to estimate j track, crossing group i queue length average within each period:

$L_{i,j}=\frac{v_s\&lsqb;(c_j\&CenterDot;q_{i,j}-g_{i,j}\&CenterDot;S_{i,j})T_c+v_p\&CenterDot;r_{i,j}\&CenterDot;k_{jam}\&CenterDot;c_j\&rsqb;}{k_{jam}\&CenterDot;c_j(v_s-v_p)}$

2. j track, crossing i queuing intensity within each period is calculated:

${\mathrm{\&eta;}}_{i,j}=\frac{L_{i,j}}{l_i}$

3. whole crossing intensity of on average queuing up within each period is estimated:

${\mathrm{\&eta;}}_j=\underset{n=1}{\overset{N}{\&Sigma;}}\frac{{\mathrm{\&eta;}}_{n,j}^2}{\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&eta;}}_{n,j}}$

2. calculate the crossing operational efficiency rate of change under different management and control scheme

(1) average traffic delay in each period of crossing and queuing intensity are grouped according to transport need, draw packet situation map, as shown in Figure 3; The group of packet from �� and group number K is:

K=1+3.322lgM

$\mathrm{\&omega;}=\frac{q_{max}-q_{\min }}{1+3.3lgM}$

(2) average traffic delay and the queuing strength mean value of crossing j management and control scheme in each transport need interval are calculated:

$D_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{D}_{k,j,x}$

${\mathrm{\&eta;}}_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j,x}$

(3) crossing j average traffic delay variable quantity and queuing Strength Changes amount under different schemes in each transport need interval are calculated:

$D_{k,j}^{\&prime;}=D_{k,j}^{m+1}-D_{k,j}^m$

${\mathrm{\&eta;}}_{k,j}^{\&prime;}={\mathrm{\&eta;}}_{k,j}^{m+1}-{\mathrm{\&eta;}}_{k,j}^m$

(4) calculating in each flow rate zone, crossing j is at the delay time at stop rate of change of scheme m+1 and scheme m and queuing change rate of strength, such as Fig. 2.

1. calculate in kth flow rate zone, the scheme m+1 delay index mean change amount �� D relative to scheme m_k,jWith queuing intensity index mean change amount �� ��_j:

${\mathrm{\&Delta;D}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{D}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

${\mathrm{\&Delta;\&eta;}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

2. j crossing is calculated in kth transport need interval, the scheme m+1 delay index average rate of change relative to scheme mWith the queuing intensity index average rate of change

${\mathrm{\&gamma;}}_{k,j}^D=\frac{{\mathrm{\&Delta;D}}_{k,j}}{D_{k,j}^m}$

${\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}=\frac{{\mathrm{\&Delta;\&eta;}}_{k,j}}{{\mathrm{\&eta;}}_{k,j}^m}$

(5) determine that crossing j is in different transport need intervals, average traffic delay and queuing intensity weight coefficient in aggregative indicator

1. the parameter in the middle of weight coefficient is demarcatedAnd b_j:

${\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\frac{g_{i,j}\&CenterDot;S_{i,j}\&CenterDot;h}{l_{i,j}}$

$b_j=\frac{\ln 799}{0.5-{\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j}$

2. calculate queuing strength factor, weight coefficient with queuing intensity change as shown in Figure 4;

${\mathrm{\&alpha;}}_{k,j}=\frac{1}{1+e^{j({\mathrm{\&eta;}}_{k,j}-{\mathrm{\&mu;}}_j)}}$

(6) calculate under dynamic traffic demand under different management and control the comprehensive rate of change of crossing operational efficiency

1. for crossing j, calculating in each transport need interval, the comprehensive rate of change of operational efficiency between scheme m+1 and m is

${\mathrm{\&psi;}}_{k,j}=-(1-{\mathrm{\&alpha;}}_{k,j}){\mathrm{\&gamma;}}_{k,j}^D-{\mathrm{\&alpha;}}_{k,j}{\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}$

2. for crossing j, calculate within the scope of whole transport need, the comprehensive assessment index of two different schemes:

${\stackrel{\&OverBar;}{\mathrm{\&psi;}}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{U}_j\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

3. complete the management and control effect assessment of different schemes

Can calculate and obtain this crossing at latter approach for previous scheme, the crossing operational efficiency comprehensive rate of change such as following table in 6 packets.

New departure is relative to the comprehensive rate of change of crossing operational efficiency of former scheme

By result it can be seen that crossing operational efficiency rate of change is-0.45%, namely crossing operational efficiency declines 0.45%.

Claims (5)

1. the crossing operational efficiency rate of change computational methods towards dynamic traffic demand, it is characterised in that the method comprises the following steps:

The traffic flow of each track group, i.e. transport need amount in c1, statistics different periods, and average traffic delay and queue length index is calculated with track group for elementary cell;

Under c2, the different management and control scheme of calculating, the rate of change of average traffic delay and queue length corresponding to each transport need interval;

C3, definition characterize the comprehensive rate of change of packet that crossing operational efficiency changes, and calculate the weight coefficient of queue length and average traffic delay in aggregative indicator;

C4, with crossing flow for weight, it is determined that management and control scheme implement before and after crossing operational efficiency rate of change.

2. the crossing operational efficiency rate of change computational methods towards dynamic traffic demand according to claim 1, it is characterized in that: in step c1, crossing is divided into different tracks group according to the flow direction, calculate in units of the group of track and incur loss through delay and queue length, then the average traffic delay of weighted calculation crossing and queue length:

C11, with 15min for interval, add up track group transport need amount q, intersection signal cycle duration c, phase place long green light time g, phase place red light duration r, supersaturation duration T_c; Demarcate section jam density k_jam, start wave-wave speed v_p;

C12, track group i for crossing j, calculate average traffic delay D_i,jWith queue length L_i,j;

1. transition function model is utilized to calculate average traffic delay:

$D_{i,j}=\left\{\begin{array}{cc}\frac{c_j{\left(1-g_{i,j}/c_j\right)}^2}{2\left(1-q_{i,j}/S_{i,j}\right)}+\frac{N_{i,j}}{C_{i,j}}& {\mathrm{\&chi;}}_{i,j}<1\\ \frac{r_{i,j}}{2}+\frac{N_{i,j}}{C_{i,j}}& {\mathrm{\&chi;}}_{i,j}\&GreaterEqual;1\end{array}\right.$

Wherein:

$N_{i,j}=\left\{\begin{array}{cc}\frac{c_{j}T}{4}\left(\left({\mathrm{\&chi;}}_{i,j}-1\right)+\sqrt{{\left({\mathrm{\&chi;}}_{i,j}-1\right)}^2+\frac{12\left({\mathrm{\&chi;}}_{i,j}-{\mathrm{\&chi;}}_0\right)}{C_{i,j}\&CenterDot;t}}\right)& {\mathrm{\&chi;}}_{i,j}>{\mathrm{\&chi;}}_0\\ 0& {\mathrm{\&chi;}}_{i,j}\&le;{\mathrm{\&chi;}}_0\end{array}\right.$

In formula: D_i,jThe average traffic delay of wagon flow corresponding to the group i of j track, crossing; c_jCycle duration for crossing j; g_i,jThe long green light time of phase place corresponding to the group i of j track, crossing; q_i,jTransport need amount for j track, crossing group i; S_i,jSaturation volume for j track, crossing group i; N_i,jFor j track, the crossing group i initial queue vehicle number at the green light initial stage; C_i,jThe traffic capacity for j track, crossing group i; ��₀For saturation threshold value; ��_i,jFor the saturation of j track, crossing group i, for q_i,jWith C_i,jRatio; C_i,jAnd ��₀Computing formula be:

$C_{i,j}=S_{i,j}\&CenterDot;\frac{g_{i,j}}{c_j}$

${\mathrm{\&chi;}}_0=0.67+\frac{S_{i,j}\&CenterDot;(g_{i,j}-I_{i,j})}{600}$

In formula, I_i,jCorresponding to the group i of j track, crossing, the copper sulfate basic of phase place, can be taken as 3s;

2. traffic shock wave Theoretical Calculation queue length L is utilized_i,jWith queuing intensity ��_i,j:

$L_{i,j}=\frac{v_s\&lsqb;\left(c_j\&CenterDot;q_{i,j}-g_{i,j}\&CenterDot;S_{i,j}\right)T_c+v_p\&CenterDot;r_{i,j}\&CenterDot;k_{jam}\&CenterDot;c_j\&rsqb;}{k_{jam}\&CenterDot;c_j\left(v_s-v_p\right)}$

${\mathrm{\&eta;}}_{i,j}=\frac{L_{i,j}}{l_i}$

In formula, L_i,jThe queue length of wagon flow corresponding to the group i of j track, crossing; v_sStartup wave-wave speed for wagon flow; k_jamDensity of blocking up for wagon flow; v_pStop wave velocity of wave for wagon flow; T_cFor the supersaturation persistent period, if supersaturation does not occur, T_cValue be 0; ��_i,jThe queuing intensity of wagon flow corresponding to the group i of j track, crossing; l_iThe length in section corresponding to the group i of j track, crossing;

C13, with 15min be interval, the average traffic delay D that is weight calculation crossing j with the transport need of track group_j:

$D_j=\frac{\underset{n=1}{\overset{N}{\&Sigma;}}{D}_{n,j}\&CenterDot;q_{n,j}}{\underset{n=1}{\overset{N}{\&Sigma;}}{q}_{n,j}}$

In formula, N is the track group number of crossing j;

C14, with 15min be interval, with the queuing intensity of track group for index calculate crossing queuing intensity ��_j;

${\mathrm{\&eta;}}_j=\underset{n=1}{\overset{N}{\&Sigma;}}\frac{{\mathrm{\&eta;}}_{n,j}^2}{\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{\&eta;}}_{n,j}}.$

3. the crossing operational efficiency rate of change computational methods towards dynamic traffic demand according to claim 1, it is characterized in that: the average traffic delay of crossing and queuing intensity are grouped by step c2 according to transport need, Comparative indices change under same transport need, so rejects the transport need impact on index; Detailed process includes:

C21, the traffic demand data utilizing each period and calculated average traffic delay and queuing intensity, it is determined that the mapping relations of three;

1. by the packet method in statistics, according to fixed interval, transport need being divided into some intervals, transport need amount in each interval, average traffic delay and queuing intensity data renumber; The computing formula of interval sum K and gap size �� is;

K=1+3.322lgM

$\mathrm{\&omega;}=\frac{q_{max}-q_{min}}{1+3.31gM}$

In formula, M is that the point of queuing intensity and flow corresponding relation is to number; q_maxAnd q_minThe respectively maximum transport need amount in survey data and minimum transport need amount;

2. the operational efficiency in this flow rate zone is characterized with queuing intensity and the arithmetic mean of instantaneous value of delay time at stop in often group data; For crossing j, intersection delay time and queuing strength calculation formula in kth flow intervals be:

$D_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{D}_{k,j,x}$

${\mathrm{\&eta;}}_{k,j}=\frac{1}{K}\underset{x=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j,x}$

In formula, D_k,j,xFor x-th point in j kth interval, crossing to corresponding average traffic delay; ��_k,j,xFor x-th point in j kth interval, crossing to corresponding queuing intensity;

C22, for crossing j, represent the two sets of plan successively implemented respectively with m and m+1, then in kth flow rate zone, the average traffic delay variable quantity D' of two sets of plan_k,jWith queuing Strength Changes amount �� '_k,jIt is respectively as follows:

$D_{k,j}^{\&prime;}=D_{k,j}^{m+1}-D_{k,j}^m$

${\mathrm{\&eta;}}_{k,j}^{\&prime;}={\mathrm{\&eta;}}_{k,j}^{m+1}-{\mathrm{\&eta;}}_{k,j}^m$

In formula,WithRespectively crossing j average traffic delay under m+1 scheme and m scheme;WithRespectively crossing j queuing intensity under m+1 scheme and m scheme;

C23, for transport need interval k, utilize interval intermediate value q_k,jAs the transport need eigenvalue in this interval, and calculate the rate of change of the delay time at stop within the scope of whole transport need and queuing intensity as weight index; Crossing j is the scheme m+1 delay index mean change amount �� D relative to scheme m in kth transport need interval_k,_jWith queuing intensity index mean change amount �� ��_jIt is respectively as follows:

${\mathrm{\&Delta;D}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{D}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

${\mathrm{\&Delta;\&eta;}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&eta;}}_{k,j}^{\&prime;}\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

In the kth transport need interval of c24, j crossing, the scheme m+1 delay index average rate of change relative to scheme mWith the queuing intensity index average rate of changeComputing formula be:

${\mathrm{\&gamma;}}_{k,j}^D=\frac{{\mathrm{\&Delta;D}}_{k,j}}{D_{k,j}^m}$

${\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}=\frac{{\mathrm{\&Delta;\&eta;}}_{k,j}}{{\mathrm{\&eta;}}_{k,j}^m}.$

4. the crossing operational efficiency rate of change computational methods towards dynamic traffic demand according to claim 1, it is characterized in that: the comprehensive rate of change chosen in step c3 considers queuing intensity and average traffic delay, utilize in transport need group intermediate value as the traffic characteristic value in this interval, and calculate weight coefficients with 3 �� principles in this eigenvalue and mathematical statistics; Detailed process includes:

C31, crossing operational efficiency to consider from two aspects of both macro and micro; Macroscopic aspect mainly considers the queuing intensity of crossing, and microcosmic point is considered as the average traffic delay of crossing, and aggregative indicator should take into account queuing intensity and average traffic delay; For crossing j, the comprehensive rate of change �� of crossing operational efficiency in kth transport need interval_i,jFor:

${\mathrm{\&psi;}}_{k,j}=-(1-{\mathrm{\&alpha;}}_{k,j}){\mathrm{\&gamma;}}_{k,j}^D-{\mathrm{\&alpha;}}_{k,j}{\mathrm{\&gamma;}}_{k,j}^{\mathrm{\&eta;}}$

In formula, ��_k,jFor the queuing intensity weight coefficient in j kth flow rate zone in crossing in aggregative indicator;

C32, transport need interval k for crossing j, utilize interval intermediate value as the traffic characteristic value in this interval, and with this eigenvalue calculation weight coefficient ��_k,j;

1. at offpeak period, queuing intensity is only small, and the probability that can affect upstream intersection traffic stream properly functioning is very low, and now comprehensive rate of change is mainly considered as crossing average traffic delay; Along with being continuously increased of traffic flow, queuing intensity becomes big, and the probability affecting upstream intersection traffic stream operation is also gradually increased, and when traffic flow increases to a certain degree, comprehensive rate of change should consider emphatically the intensity of on average queuing up of crossing; Under this theory, the queuing strength factor computing formula in the comprehensive rate of change index of crossing is:

${\mathrm{\&alpha;}}_{k,j}=\frac{1}{1+e^{-b_j({\mathrm{\&eta;}}_{k,j}-{\mathrm{\&mu;}}_j)}}$

In formula, b_jAnd ��_jIt is two model parameters;

2., when the saturation of crossing is less than 1, the long green light time in each cycle all has to a certain degree rich, and rate of change index now need not consider queuing intensity; The saturation queuing intensity equal to 1 is in comprehensive rate of change to start to consider as a whole and queues up and the minimum threshold of delay time at stop; The time headway assuming that vehicle is saturated when discharging is h, then start to consider the minimum threshold queued up with the delay time at stop as a wholeComputing formula be:

${\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j=\frac{1}{N}\underset{i=1}{\overset{N}{\&Sigma;}}\frac{g_{i,j}\&CenterDot;S_{i,j}\&CenterDot;h}{l_{i,j}}$

3. when the queuing intensity of crossing is equal to 0.5, should the rate of change of waiting lines's intensity and delay time at stop the two different aspects on an equal basis; Meanwhile, according to 3 �� principles in mathematical statistics, comprehensive rate of change index only considering, the queuing intensity threshold of vehicle delay time at stop is ��_j-3 ��; Owing to the span of queuing intensity is (0,1), ��_jThe lower limit value that value is 0.5,3 �� be 0.00125; Therefore, parameter b_jComputing formula be:

$b_j=\frac{\ln 799}{0.5-{\stackrel{\&OverBar;}{\mathrm{\&eta;}}}_j}.$

5. the crossing operational efficiency rate of change computational methods towards dynamic traffic demand according to claim 1, it is characterised in that: in the c4 of step, utilize interval intermediate value q_k,jAs the transport need eigenvalue in this interval, and calculate the comprehensive rate of change within the scope of whole transport need as weight index; Detailed process includes:

Transport need for crossing j is interval, utilizes interval intermediate value q_k,jAs the transport need eigenvalue in this interval, and calculate the comprehensive index value within the scope of whole transport need as weight index, draw crossing operational efficiency rate of change; The scheme m+1 crossing operational efficiency rate of change relative to scheme m is:

${\stackrel{\&OverBar;}{\mathrm{\&psi;}}}_j=\frac{\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&psi;}}_j\&CenterDot;q_{k,j}}{\underset{k=1}{\overset{K}{\&Sigma;}}{q}_{k,j}}$

The rate of change drawn on the occasion of, illustrate that operational efficiency is promoted, changing value is negative value, illustrates that operational efficiency declines.