CN106370198A - Route selection method taking outgoing delayed reaction into account - Google Patents

Abstract

The invention discloses a route selection method taking outgoing delayed reaction into account, and belongs to the field of transportation planning. The route selection method comprises the following steps: defining reference points of persons going out, confirming properties of the reference points, classifying the persons, analyzing risk preference coefficients of different types of person going out, furthermore calculating value functions and weight functions of the person going out by using related software, furthermore acquiring sensation values of different types of persons going out about candidate schemes, and finally, selecting routes by users going out according to the principle that the sensation values are maximized. By adopting the route selection method, the reference points of the users going out are defined, a classification method for the users going out is confirmed, the risk preference coefficients of different types of users going out are included into a route selection consideration range, a calculation method for the risk preference coefficients of the users going out is completed, and thus the route selection method can relatively well meet practices. In addition, the influence of actual outgoing time on the users going out is relatively better considered, and route selection behaviors of the users going out when actually going out are relatively well simulated.

Description

A kind of routing resource considering that trip is heterogeneous

Technical field

The invention belongs to traffic programme field, specifically one kind can apply under actual traffic scene, simulation all kinds of go out The method of passerby's optimizing paths.

Background technology

With increasing rapidly of China's Urban vehicles poputation, the environmental pollution of traffic congestion and its induction, traffic thing Therefore wait the bottleneck being increasingly becoming restriction urban economy and social development.For traveler, sixty-four dollar question is: how to lead to Cross Selecting Travel Paths, it is to avoid traffic congestion, quickly arrive at.Due to the impact of the factors such as traffic environment, trip experience, In real traffic situation, traveler may will not select travel time path the shortest, such behavior, it is possible to use limited Rational behavior describes.

The research of legacy paths housing choice behavior is typically based on expected utility theory under assuming traveler rational framework Or launch under stochastic utility theory, using the cost minimization of trip or the maximum foundation as choice for traveling of effectiveness, less consideration The bounded rationality problem of traveler, leads to the deviation of various degrees between traffic distribution result and reality.Therefore, will have The research that limit rational behavior includes traffic network design is very necessary.Prospect theory, can used as a kind of descriptive theory Explain bounded rationality behavior well.

Progressively going deep into correlational study, at present, a large amount of scholars' application accumulation prospect theories are to traveler in actual feelings Parameter characteristic in border and travel behaviour are studied.But perceptibility and happiness that the less consideration person of existing research spends to trip Good difference, the traveler with different trip purposes spends hobby difference may lead to its routing line to the trip of oneself For diversity.Additionally, existing research usually assumes that all travelers are homogeneities, that is, all trip users have identical ginseng Examination point.In general, reference point can change the preference of prospect, directly affects the assessment of alternative.Such assume this show Right and practical situation has deviation.So adding heterogeneous for user in model it is considered to different traveler spends hobby to trip Diversity, can enable model provide and more conform to real scene.

Content of the invention

The purpose of the present invention is to propose to a kind of trip considering that trip is heterogeneous that can more preferably be applied to actual traffic environment User's routing resource.Technical scheme is as follows:

A kind of vehicle going on city speed predicting method based on road network characteristic, comprises the following steps:

Step one, determine present in road network trip starting point and terminal, determine that present in target road network, od is to w.

The free stream velocity in step 2, the transport need gathering in target road network region, and each section and road energy Power；

Step 3, calculating target road network each Path Travel Time t_rw, in this, as the travel time in each section of current road network Expect；

Step 4, the reference point of definition trip user, obtain reference point u to traveler between w for the od in target road network_w；

Step 5, reference point is divided into m interval；Extract the reference point data in m interval, obtain m class traveler Reference point；

Step 6, calculate m class traveler away from reference point when the sensitivity level α that disappears_m、β_m；

Step 7, the cost function calculating m class traveler, weighting function；In conjunction with traveler itself od, according to target road network Current state, calculates the perceived value in each path of m class traveler in road network this moment

Step 8, traveler carry out Path selection with perceived value maximization for criterion, obtain m class traveler in od to w Between flow on the r of pathComplete Path selection；

When step 9, traveler are gone on a journey on the r of path, according to the actual travel timeCarry out section reference pointAnd path reference pointRenewal；

Step 10, when traveler is not reached home, return to step five.

Proposed by the present invention go out a kind of trip user's routing resource considering that trip is heterogeneous, advantage is to contemplate The heterogeneity of row user, analyzes the risk goal function of different trip users it is contemplated that because trip purpose difference may be led The trip consumer's risk preference difference causing, simulates trip user during trip, adjusts expectation based on the actual travel time Travel time is the behavior of reference point, can preferably simulate trip users' route choice behavior.

Brief description

Fig. 1 considers the heterogeneous Path selection flow chart of steps of trip

Fig. 2 trip user's Path selection result

Fig. 3 trip user completes each path flow after Path selection

Specific embodiment

A kind of main thought of Path selection new method considering that trip is heterogeneous proposed by the present invention is: reference point is taken Classified from the traveler of normal distribution, analysis different trip consumer's risk preference coefficients it is considered to trip heterogeneous to and real The impact to reference point and perceived value for the border travel time, calculates the perception valency of each alternative of different classes of trip user Value, turns to principle with perceived value maximum and carries out Path selection.

Fig. 1 is a kind of Path selection new method flow chart considering that trip is heterogeneous.Mainly comprise the steps that

Determine trip starting point and terminal present in road network, determine that present in target road network, od is to w；And section j, its Middle j ∈ j；

Transport need q in collection target road network region, and the free stream velocity in each sectionAnd road passage capability c_j；

Using calculating target road network each Path Travel Time t_rw, computational methods are as follows:

In above formula,It is the travel time of section j on path r between od is to w,It is road on path r between od is to w The flow of section j.

As it is assumed that each section travel time Normal Distribution in road network, from the property of normal distribution, path goes out Row time also Normal Distribution, therefore Path Travel Time be desired for t_rw；

The reference point defining user is expected the travel time for user, and freely flows out row by estimated congestion coefficient and path Time determines.Due to alternative (Path Travel Time) Normal Distribution, user is expected that the travel time should also be as just obeying State is distributed；

Reference point u to traveler between w for the target road network od_wComputing formula be:

In above formula, u_wBe od to the traveler reference point between w,It is the estimated congestion coefficient of section j on the r of path, n is The quantity to alternative path between w for the od.

Reference point ascending order is arranged, according to reference point extreme value by u_wBe divided into m interval it may be assumed that

Extract the reference point data in m interval, calculate the expectation of each interval internal reference examination point, obtain the ginseng of m class traveler Examination point, i.e. the reference point of m class travelerComputational methods are:

In above formulaFor the reference point to m class traveler between w for the od, l is the sum of m class traveler,For the trip of m class The reference point of l position traveler in person.

Calculate m class traveler away from reference point u₀When the sensitivity level α that disappears_m、β_m, i.e. the risk partiality of traveler The method of coefficient is:

In above formulaIt is the reference point to the m class trip user between w with maximum reference point for the od. δ is scale parameter (δ ≤ 1) .k is time value coefficient (0 ＜ k≤1).As a rule, having larger k for trip user means for trip The required precision of time is higher, and commuting subscriber just has characteristics that.

Then cost function, the weighting function of m class traveler are calculated；In conjunction with traveler itself od, worked as according to target road network Front state, calculates the perceived value in each path of m class traveler in road network this moment, its computational methods is:

In above formula, g (u) is cost function, u₀For reference point, λ is risk averse coefficient.

ω (p)=exp {-[ln (p)]^r} (7)

In above formula, ω (p) is weighting function, and p is the actual probabilities that the time occurs, and γ is weighting function curvature, in order to ensure The monotonicity of weighting function, typically has 0 ＜ γ≤1.

In above formula, v is perceived value, φ_uU () is the cumulative probability density function (cdf) of alternative

Traveler carries out Path selection with perceived value maximization for criterion, obtains m class traveler path between od is to w Flow on rComplete Path selection it may be assumed that

In above formulaFor the perceived value to m class traveler on path r between w for the od,For od to m on path r between w The maximum of the perceived value of class traveler.

When traveler is gone on a journey on the j of path r section, user is according to the actual travel time for tripCarry out section Reference point and the renewal of path reference point, specific formula for calculation is:

In above formulaReference point to section j on m class trip user path r between for od to w,For The actual time of i-th section trip on m class trip user path r between for od to w.

After the user that goes on a journey completes the renewal of section reference point, return-formula (4) re-starts Path selection, until reaching Terminal.

Fig. 2 is the different traveler perceived value of the different time value coefficient that model calculates.

Fig. 3 is the different traveler Path selection results of the different time value coefficient that model calculates.

Claims (5)

1. it is characterised in that setting up a kind of reference point definition, reference point takes a kind of routing resource considering that trip is heterogeneous From normal distribution and classified, analyze the disappearance sensitivity of all kinds of travelers, calculate the perception in each path in road network further It is worth, Path selection is carried out for criterion with perceived value maximization, according to the actual travel time, section reference point is updated, Until traveler is reached home, output result.Mainly comprise the steps that

Step one, determine present in road network trip starting point and terminal, determine that present in target road network, od is to w.

The free stream velocity in step 2, the transport need gathering in target road network region, and each section and road passage capability；

Step 3, calculating target road network each Path Travel Time t_rw, in this, as the travel time expectation in each section of current road network；

Reference point u to traveler between w for the od in step 4, acquisition target road network_w；

Step 5, reference point is divided into m interval；Extract the reference point data in m interval, obtain the reference of m class traveler Point；

Step 6, calculate m class traveler away from reference point when the sensitivity level α that disappears_m、β_m；

Step 7, the cost function calculating m class traveler, weighting function；In conjunction with traveler itself od, current according to target road network State, calculates the perceived value in each path of m class traveler in road network this moment

Step 8, traveler carry out Path selection with perceived value maximization for criterion, obtain m class traveler between od is to w Flow on the r of pathComplete Path selection；

When step 9, traveler are gone on a journey on the r of path, according to the actual travel timeCarry out section reference pointAnd path reference pointRenewal；

Step 10, when traveler is not reached home, return to step five.

2. the heterogeneous routing resource of trip is considered according to claim 1 it is characterised in that described step 4, specifically Refer to: define user expectation the travel time be user reference point it is contemplated that the travel time by path the free stream travel time and User is expected that congestion coefficient determines, due to alternative path travel time Normal Distribution, therefore, it is desirable to the travel time just obeys State is distributed

3. the heterogeneous routing resource of trip is considered according to claim 1 it is characterised in that described step 5, specifically Refer to: the reference point data of the traveler of reference point Normal Distribution is carried out pretreatment, according to reference point extreme value by reference point M that is divided into equalization interval, i.e. formula (1), extracts the reference point data in m interval, and the expectation by data in each intervalReference point as m class traveler.

$\[u_{\min },u_{\min }+\frac{u_{\max }-u_{\min }}{m}\],\[u_{\min }+\frac{u_{\max }-u_{\min }}{m},u_{\min }+2\left(\frac{u_{\max }-u_{\min }}{n}\right)\],\mathrm{...},\[u_{\min }+\left(m-1\right)\left(\frac{u_{\max }-u_{\min }}{m}\right),u_{\max }\]---\left(1\right)$

4. the heterogeneous routing resource of trip is considered according to claim 1 it is characterised in that described step 6, specifically Refer to: the reference point data of all kinds of travelers between w of the od in extraction step five, data is carried out ascending order arrangement, defines reference point A minimum class user is first kind trip user, and reference point isThe user with maximum reference point is m class user, reference Put and beAll types of user to the disappearance sensitivity level away from reference point is:

${\mathrm{\α}}^m={\mathrm{\β}}^m={\[1-(1-k)(u_0^m/u_0^m)\]}^{\mathrm{\δ}}---\left(2\right)$

5. the heterogeneous routing resource of trip is considered according to claim 1 it is characterised in that it is characterized in that, described step Rapid nine, specifically refer to: traveler can adjust the expectation travel time according to the present situation during trip in good time, when traveler exists Complete in the r of path a certain section trip when, it can change therewith to the expectation travel time in remaining section, trip to next road The expectation travel time of section is:

$\begin{array}{c}{u}_{rw}^{m,j,desired}=u_w-u_{od}^{rest}=u_{od}-t_r^{m.traveled}-t_r^{untraveled}\\ =u_w-\left(\underset{i=1}{\overset{j-1}{\mathrm{\σ}}}{t}_{rw}^{m,i,real}\right)-\underset{j=m+1}{\overset{j}{\mathrm{\σ}}}\left(1+{\mathrm{\α}}_r^j\right)t_{0rw}^j\end{array}---\left(3\right)$

$\begin{array}{c}{u}_w^m=u_w-u_{od}^{rest}=u_{od}-t_r^{m.traveled}\\ =u_w-\left(\underset{i=1}{\overset{j-1}{\mathrm{\σ}}}{t}_{rw}^{m,i,real}\right)\end{array}---\left(4\right)$

When the perceived value in next section is too small, or when after renewal, the perceived value in remaining section is less than other paths, traveler Trip route can be changed.