CN100501750C - Interdynamic virtual realizing method for tunnel compound monitoring control - Google Patents

Interdynamic virtual realizing method for tunnel compound monitoring control Download PDF

Info

Publication number
CN100501750C
CN100501750C CNB2005101121875A CN200510112187A CN100501750C CN 100501750 C CN100501750 C CN 100501750C CN B2005101121875 A CNB2005101121875 A CN B2005101121875A CN 200510112187 A CN200510112187 A CN 200510112187A CN 100501750 C CN100501750 C CN 100501750C
Authority
CN
China
Prior art keywords
tunnel
vehicle
model
simulation
emulation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CNB2005101121875A
Other languages
Chinese (zh)
Other versions
CN1991845A (en
Inventor
康盛
余鹿延
姚胜东
沈毅
李一丁
包勤峰
罗红
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SHANGHAI ELECTRICAL AUTOMATION DESIGN INST CO Ltd
Original Assignee
SHANGHAI ELECTRICAL AUTOMATION DESIGN INST CO Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SHANGHAI ELECTRICAL AUTOMATION DESIGN INST CO Ltd filed Critical SHANGHAI ELECTRICAL AUTOMATION DESIGN INST CO Ltd
Priority to CNB2005101121875A priority Critical patent/CN100501750C/en
Publication of CN1991845A publication Critical patent/CN1991845A/en
Application granted granted Critical
Publication of CN100501750C publication Critical patent/CN100501750C/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a mutual dynamic virtual realization method used in tunnel integration monitors that characterized in that it realizes the full three-dimensional virtual simulation of tunnel circumstance which includes vehicles, road, and tunnel structure. During the building of the traffic module, the behavior property of driver is considered, and the various mode of simulation calculation module are decomposed particularly. The simulation of tunnel circumstance considers the effects of discharging factor of vehicles, aeration, and tunnel sculpts. The integration simulation system of tunnel traffic, aeration, circumstance is realized. The advantages of the invention are: providing a visual examination circumstance, knowing the design effect before construction, the construction scheme can be arranged effectively, the design periods can be decreased, the quality of design can be increased, the cost of design and construction can be saved; the control scheme can be optimized, control strategy can be improved, control efficiency can be increased. The successful application of virtual simulation technique in tunnel can provide use for reference for other industry.

Description

A kind of mutual dynamic virtual implementation method that is used for the tunnel comprehensively monitoring
Technical field
The present invention relates to a kind of mutual dynamic virtual reality method that is used for the tunnel comprehensively monitoring, belong to the technical field of computer simulation technique and intelligent transportation microcosmic.
Background technology
Shanghai Outer Ring Line Tunnel is a tunnel, three holes that crosses Huangpu River, for having alleviated the pressure of river traffic congestion more, improves Shanghai City urban highway traffic net and a cross-river tunnel building.For guaranteeing tunnel operation, personal safety and improve the vehicle handling capacity that the purpose of reach the mediation traffic, taking precautions against natural calamities and riding calamities is so set up the effective tunnel intelligent traffic system of a cover.An essential characteristic of this system is, system can make real time reaction to the variation of road network transportation condition, and each component can carry out real-time information interchange in the system.In order to assess the benefit of tunnel intelligent traffic system effectively, need a suitable system that the tunnel traffic control system is carried out the modeling evaluation analysis, model can be described the various interactions of the such microcosmic point of single unit vehicle-driver. and traffic engineer can carry out autonomous control to the variation of road network transportation condition like this, thereby can carry out effectively evaluating to the effect before and after the scheme implementation.
The traffic simulation technology is accompanied by the flourish of ITS as an important content of intelligent transport system (ITS), has become one of hot fields of domestic and international traffic engineering circle research at present.
Interactively dynamic virtual realization technology is one of sophisticated technology of present information technology application in the world.The high speed development of The present computer technology makes it become the important research instrument of every field, and the utilization computer simulation technique has become the important technical of many neighborhood system analyses and design.Computer Simulation is meant with the computing machine to be main tool, realistic model with real system or predetermined system is a foundation, by moving concrete realistic model and to the analysis of computer output information, realization is to the comprehensive assessment and the prediction of real system running status and Changing Pattern, and then realization is to improvement or the optimization of real system design with structure.It is a kind of technological means of assay existing system running status or design optimization system in future performance and function.In field such as engineering design, Aero-Space, communications and transportation, economic management, ecologic environment, communication network and computing machine be integrated, all have a wide range of applications.It is the important means of the indispensable analysis of hi-tech industry, research, design, evaluation, decision-making and training.
Along with the growth of the microprocessor performance of computer technology makes the simulation analysis that utilizes microcomputer and workstation to carry out complication system become possibility.OO thought and method in software design, have extensively been adopted, add the progress of computer graphics techniques, interactively Virtual Realization technology has appearred, it is the breakthrough and the development of traditional simulation technology, formed at present a relatively independent subject, it is compared with computer simulation technique with traditional computer graphics, and own significant characteristic is arranged, i.e. our usually said 3I (Immersion, Interaction, Imagination).This subject is the newest fruits of emulation technology development, and its development trend outstanding behaviours is in the following aspects:
Having occurred more OO modeling method of present research and graphical modeling technology in 1 modeling method, all is to utilize computer software technology to manage to provide a kind of visual modeling environment directly perceived, makes complicated modeling process obtain simplifying.
2 Object-Oriented Simulation have then broken through traditional simulation method idea in theory, make modeling process have higher intelligent level, the model of being set up has inherent expandability and reusability, help the foundation of visual modeling simulated environment, thereby provide means easily for the simulation analysis of large-scale complicated system.
3 artificial intelligence technologys are achieved in Application in Simulation.Artificial intelligence related to aspect three with Computer Simulation intersecting on subject: knowledge base is used for modeling and simulation, comprise and utilize knowledge base and expert system for the foundation of realistic model and the service of comprehensively providing advice and be used for the check and the confidence level analysis of simulation result, emulation technology and artificial intelligence technology combine the generation intelligent simulation.
4 virtual reality technologies are also referred to as clever border technology, and the user is placed oneself in the midst of in the virtual environment seemingly, make the user can enter virtual environment inner direct modeling, observation or experience the variation of things inherence, and can participate directly in the interaction of things and go.Mutual dynamic virtual reality technology system compares with traditional emulation technology, and incomparable superiority is arranged.
Adopt mutual dynamic virtual reality technology to study and instruct and have bigger realistic meaning.Only more than 20 of cross-river tunnel planned to build up for the end of the year 2010 in Shanghai, and after plan is finished, Shanghai will become maximum city, tunnel in the world.3 vcehicular tunnels have been built up, 2 railway tunnel and 1 tourist tunnel in Shanghai at present.Also to build up 3 vcehicular tunnels before the end of the year 2004,2 railway tunnel.Tunnel at the bottom of a large amount of rivers also will be built in ground such as Nanjing, Zhejiang, Wuhan in addition.Shanghai will be invested 12,000,000,000 to Chongming Island and be built seabed tunnel, and the seabed tunnel of long distance also will be built in Guangdong, port.Each tunnel all has many uncertain factors along with the difference of the structure length in geographic position, tunnel, shape etc. in design and construction stage, operational management stage, owing to lack the means of research, many problems only are by demonstration and experience solution at present.Foundation is significant and urgency based on Tunnel Design, construction and the management platform of Interactive Dynamic virtual reality technology.
Summary of the invention
The objective of the invention is in order to study each tunnel along with the structure length in geographic position, tunnel, the difference of shape, in many uncertain factors such as design and construction stage, operational management stages, a kind of mutual dynamic virtual reality method that is used for the tunnel comprehensively monitoring is proposed.
Technical scheme of the present invention is: a kind of mutual dynamic virtual reality method that is used for the tunnel comprehensively monitoring is characterized in that method may further comprise the steps:
1, adopt VC constructing system platform and related interfaces, applying three-dimensional graphical simulation instrument OpenInventor realizes the virtual emulation of three-dimensional scenic;
2, set up three-dimensional scenic;
By three-dimensional CAD software, UG, Pro-E set up, again by " Virtual RealityModeling Language mode is read in simulating scenes for complicated model;
3, foundation comprises the required knowledge base of emulated data and system, specifically comprises:
● model data:
Comprise vehicle, tunnel model data;
● the raw data of emulation and parameter:
Comprise vehicle property parameters, tunnel condition parameter, external environment condition parameter;
● the analysis of simulation result and statistics:
The statistics that comprises vehicle fleet size in the tunnel, average velocity, maximum carbonomonoxide concentration;
● the simulation analysis knowledge base
Be meant that the application simulation result data carries out the knowledge or the model of assay to the tunnel situation, use them and can provide suggestion is controlled in the tunnel;
4, adopt 3D mouse to realize tunnel panorama or local interactive three-dimensional roaming;
5, the dynamic generation of vehicle, storage and dynamically disappearance;
Use the chained list class CobList of VC itself, CobList carries out the storage of vehicle; When vehicle arrives preposition, vehicle is disappeared, when vehicle arrival destination need disappear, that piece internal memory of distribution before the just necessary cancellation, and from the tunnel simulating scenes, disappear simultaneously;
6, set up the Traffic Flow Simulation mathematical model:
Comprise: (1) vehicle produces the model model of promptly dispatching a car;
(2) travel time produces model;
(3) car-following model;
(4) lane changing model;
7, realize traffic simulation: the wagon flow in each track adopts the structure of chain sheet form to preserve simulation process intermittent scanning method;
8, determine the air regime determinative; It comprises: vehicle fleet size, the vehicle pollutant emission factor, vehicle average velocity, wind speed, length of tunnel, external environment situation;
9, set up the three-dimensional analogue system, it comprises with lower module:
● detect the pretreatment module of data
Detect data such as vehicle, environmental aspect in the tunnel, and pass to and pass to tunnel mutual dynamic 3 D dummy emulation system model;
● tunnel three-dimensional range module
Realize the panorama in tunnel and local interactive three-dimensional roaming, make the observer watch the various piece in tunnel, comprise the duty of this facility according to the wish of oneself;
● the tunnel traffic emulation module
The traffic simulation module can be according to detecting traffic in the data in real time emulation tunnel;
● the emulation of tunnel air situation
Can be by the difference of color, the distribution and the variation of aspects such as the C0 concentration of air, air themperature in the real-time demonstration tunnel in virtual three-dimensional tunnel scene;
● tunnel illumination situation emulation module
React the illumination state in tunnel by the brightness in the three-dimensional scenic, the illumination state changes with the light conditions of real-time detection;
● intelligent control module
Intelligent control module is the mathematical model of utilizing in above-mentioned 5 kinds of emulation modules, and in conjunction with the knowledge and experience through accumulation, sets up the Based Intelligent Control model, makes the suggestion of the Based Intelligent Control of tunnel device or realizes real-time control to equipment;
The invention has the beneficial effects as follows:
(1) provides the virtual test environment.Can understand design effect in the past, effectively arrange arrangement and method for construction at constructing tunnel, thereby shorten the Tunnel Design cycle, improve designing quality, save design and executive cost.
(2) control and the maintenance for the tunnel provides virtual test atmosphere.Can make we easily optimization control scheme, improve control strategy, rather than after controlling schemes realizes, just pinpoint the problems, thereby improve the efficient of control effectively.
(3) the virtual emulation technology can be offered reference and reference for other industry in the successful Application of tunnel emulation.
Description of drawings
Fig. 1 is the mandatory synoptic diagram that changes;
Fig. 2 changes synoptic diagram for selectivity;
Fig. 3 realizes block diagram for traffic simulation;
Fig. 4 is a three-dimensional analogue system general structure block diagram.
Embodiment
The specific embodiment of the invention is illustrated in conjunction with the accompanying drawings: a kind of mutual dynamic virtual reality method that is used for the tunnel comprehensively monitoring is characterized in that method comprises following concrete steps:
1, adopt VC constructing system platform and related interfaces, applying three-dimensional graphical simulation instrument OpenInventor realizes the virtual emulation of three-dimensional scenic.Open Inventor is the OO three-dimensional picture software package of being released by SGI company, be based on the high-rise graphical development environment of Open GL, also be a kind of relatively independent window system, it can be transplanted on the different hardware platforms by supporting different window systems.Open Inventor is owing to adopted object-oriented thought, and the Drawing Object that it is created is different from the figure that produces with classic method (as using C language or GL).Between the figure that produces with classic method and the operation of figure is that not contact or contact are very weak, therefore, produces complicated three-dimensional picture and realizes that the graphic operation of complexity is very loaded down with trivial details with traditional method.Yet Open Inventor is in the same place the Drawing Object that it is created with the operation " binding " to these Drawing Objects, thereby makes the establishment of three-dimensional picture and operation become simple.All information of the object that Open Inventor is created, as: the position of object, shape, size, color, representing grain, light source etc. all are stored in the scene database of Open Inventor, and the user can read or shows these information.OpenInventor is packaged together the information of Drawing Object with to the operation of Drawing Object.Like this, the user is easy to Drawing Object realization change color, size, texture, shift position, conversion visual angle, animation, the mouse created are chosen, and high brightness shows that bounding box calculates, sequence of operations such as search.
2, set up three-dimensional scenic
By three-dimensional CAD software, UG, Pro-E set up, again by " Virtual RealityModeling Language mode is read in simulating scenes for complicated model.Can add texture in CAD software or Open Inventor environment, for main body surface.The method of employing ' same structure repeatedly uses ' can effectively reduce model and call in the time, when repeatedly occurring as vehicle of the same type, can call the same three-dimensional auto model in the internal memory.The tunnel of going up very much for another example can be realized by repeatedly calling short tunnel.
3, foundation comprises the required knowledge base of emulated data and system, specifically comprises:
● model data
Comprise model datas such as vehicle, tunnel, other annex.
● the raw data of emulation and parameter
Comprise vehicle property parameters, tunnel condition parameter, external environment condition parameter etc.
● the analysis of simulation result and statistics
The statistics that comprises vehicle fleet size in the tunnel, average velocity, maximum carbonomonoxide concentration etc.
● the simulation analysis knowledge base
Be meant that the application simulation result data carries out the knowledge or the model of assay to the tunnel situation, use them and can provide suggestion is controlled in the tunnel.
4, adopt 3D mouse to realize tunnel panorama or local interactive three-dimensional roaming;
Can adopt 3D mouse to realize tunnel panorama or local interactive three-dimensional roaming, design 3D mouse here and in scene, realize roaming.The human-computer interaction module of virtual pattern simulation subsystem is after tunnel scene drawing module initialization, just retrieve the existence of 3D mouse, the 3D mouse class is carried out initialization, set up getting in touch between the pose transform node of 3D mouse state and viewpoint node and tunnel body.Like this, when the operator changed the current state of 3D mouse, message circulation will trigger the corresponding operating to viewpoint node or tunnel this posture transform node, thereby realized the variation of scene viewpoint or tunnel pose.
5, the dynamic generation of vehicle, storage and dynamically disappearance;
The dynamic generation of vehicle comes down to a vehicle model node and is added under the tunnel scene root node, become its child node. " Virtual Reality ModelingLanguage file layout; it exists on the hard disk; car of every like this generation will read once from hard disk; the great waste that causes CPU to use, the while has also been caused the break of emulation because tunnel and vehicle model are transformed by the UG figure.Solution to this problem is to open model file in advance, and reads an OpenInventor node, as long as vehicle adds this node under the root node of tunnel scene when producing.The chained list class CobList of VC itself is used in the storage of vehicle, and the function class of CobList is doubly linked list seemingly, and has saved running space with the class that VC itself has, and has improved travelling speed.When vehicle arrives preposition, vehicle is disappeared, otherwise, along with the continuous operation of simulated program, the memory headroom of computing machine can be more and more littler, until deadlock. because when vehicle produces, distributed internal memory just for each car, so when vehicle arrival destination need disappear, that piece internal memory of distribution before just must cancelling, and from the tunnel simulating scenes, disappear simultaneously.
6, set up the Traffic Flow Simulation mathematical model:
(1) vehicle produces model
The model of promptly dispatching a car is an important component part of traffic simulation module, and the model of dispatching a car is mainly used in the initialization of emulation monomer.The initialization of emulation monomer is a key link in the realistic model, and to a certain extent, the initialization of emulation monomer has determined the keynote of whole simulation model macroscopic property.This model is finished the initialization of following attribute.
A, initialization driver-vehicle attribute
Driver's attribute: by randomizer, with the driving behavior parameter (as the expectation speed of a motor vehicle, target vehicle speed, follow slow train restrain oneself degree, time of driver's reaction, driver's susceptibility, changing Lane the time the space accepted, to the degree etc. of submitting to of traffic signals and traffic sign) compose randomly by a certain distribution (obtaining) and to give each driver by enquiry data;
The vehicle attribute: the distribution that gets according to inquiry agency, with stochastic parameters such as vehicle class, vehicle performance give each vehicle.Vehicle class comprises: according to length of wagon or load-carrying carry out vehicle class classification, etc. classification.Corresponding vehicle performance comprises: peak acceleration, maximum deceleration, normal acceleration, normal retarded velocity.
B, travel time produce model
Poisson distribution is successfully used to describe the vehicle number that sets out of source node in the continuous time interval, and this count distribution pairing (time headway distribution) spaced apart is exactly that negative exponent distributes.Owing to always have minimum time headway between the two cars, the negative exponent distribution (SNED) that therefore is shifted is used to describe the time headway that has more actuality and distributes.Below provide the SNED model of developing by Bunker:
f ( t ) = &lambda;EXP [ - &lambda; ( t - T ) ] , t &GreaterEqual; T 0 , t < T
In the formula, t is the time headway (s) between the two cars that sets out in succession of front and back; &lambda; ( &lambda; = aq 1 - T q ) The average that vehicle sets out during for unit; T is minimum time headway, and a is the ratio that has greater than the vehicle of the time headway of T; Q is the average vehicle rate of setting out ,/s.
In order to obtain meeting the time headway t that following formula distributes, need to use the mathematical method that is called inverse transformation (ITM), result
t = 1 &lambda; ln a r + T
In the formula, r is an equally distributed random number between interval [0,1].
Note t nBe the departure time of back car n, t N-1Be the departure time of front truck n-1, then t n-t N-1=t, the t in the alternate form obtains
t n = t n - 1 + 1 &lambda; ln a r + T
The existence of parameter T limited basically the vehicle maximum rate of setting out be 1/T (/s).
(2) car-following model
In the driving procedure in vehicle same track on the highway section.Vehicle movement is subjected to the influence of its front truck, and the driver wishes to travel with the speed of expectation on the one hand, must keep certain safe distance with front truck again on the other hand.Back car is with respect to being in three kinds of states with the track front truck: freely travel, travel and promptly slow down three kinds of states with car; The threshold values of different driving states defines with the time headway of adjacent two cars in front and back on the division highway section.When the time headway of adjacent two cars in same track during greater than a certain threshold values, the transport condition of back car has not been subjected to the influence of front truck, this car is in free transport condition, here " freely travelling " refers to not be subjected to the constraint of front truck, but still is subjected to the constraint and the influence of road conditions, traffic control rules, vehicle performance, driver's driving habits; In this case, suppose that the driver can adjust acceleration, reaches its target vehicle speed.When the time headway of adjacent two cars in same track during less than this threshold values, vehicle is in sailing state: common car-following model is based on stimulation-reaction pattern, follow direct stimulation that vehicle changes its driving behavior (acceleration) come from before and after the velocity contrast of car, the sensitivity of reaction increases with the increase of current vehicle speed degree, with front-and-rear vehicle distance from increase diminish.When time headway during less than the minimum value set, vehicle is in emergency braking condition, avoids bumping against with front truck.
A, free flow pattern
When vehicle be in a car position or with the leading vehicle distance in track greater than when speeding boundary (time headway is greater than 8s), vehicle is in free transport condition.The acceleration that vehicle adopted is determined by the present speed and the gap between the desired speed of vehicle this moment.Formula is as follows
a free = a max + [ 1 - [ V V exp ] 2 ] , ( V exp > V ) a max - [ 1 - [ V exp V ] 2 ] , ( V exp &le; V )
A in the formula FreeBe the acceleration (m/s under the free transport condition 2);
Figure C200510112187D00132
Be respectively maximum acceleration, deceleration degree (m/s with the type of vehicle of speeding 2); V is the present speed (km/h) with the vehicle of speeding; V ExpBe desirable desired speed (km/h) with the vehicle of speeding.
B, urgent car-following model
When another vehicle and leading vehicle distance during, adopt urgent car-following model less than a certain preset value
a n = min { a n - 1 - ( V n - V n - 1 ) 2 2 gap _ lead , a n - } V n > V n - 1 min { a n - 1 , a n - } V n &le; V n - 1
In the formula, a N-1Be the acceleration of front truck,
Figure C200510112187D00135
Be the normal retarded velocity of back car, gap_lead is from the spatial separation of the front truck tailstock, V N-1Be preceding vehicle speed
C, general with speeding model
When the time headway of adjacent two cars less than when sailing threshold values and arrive the minimum value of time headway, vehicle is in the state of sailing of following.
Car-following model generally speaking is for adopting EDIE non-linear with speeding model:
x * * n ( t + T ) = &alpha; 0 x * n m ( t + T ) [ x n - 1 ( t ) - x n ( t ) ] l * [ x * n - 1 ( t ) - x * n ( t ) ]
In the formula:
Figure C200510112187D00137
For crossing the acceleration, deceleration degree (m/s that adopts in the journey with speeding on the vehicle of speeding 2); T is time of driver's reaction (s);
Figure C200510112187D00138
For vehicle n in t+T speed (m/s) constantly; x N-1(t), x n(t) be respectively vehicle n-1, n at t coordinate (m) constantly;
Figure C200510112187D00139
Be respectively vehicle n-1, n in t speed (m/s) constantly; α 0, m, l be for speeding the calibrating parameters of model.
Because scanning period method is adopted in emulation, therefore, the driver can not be scanned the period at each and just make the acceleration judgement after through one period reaction time, therefore, ignores reaction time T in this realistic model, and model is as follows
x * * n ( t ) = &alpha; 0 x * n m ( t ) [ x n - 1 ( t ) - x n ( t ) ] l * [ x * n - 1 ( t ) - x * n ( t ) ]
The acceleration, deceleration degree here is subjected to the restriction of the maximum acceleration, deceleration degree of each type of vehicle in simulation process, avoid calculating according to formula purely extreme situation occurring.
(3) lane changing model
Changing in the model in early days, people consider just whether the front and back neutral gear in target track satisfies, if satisfy the behavior of changing of then implementing.Do not consider the competition and cooperation relation between the front and back car of vehicle and adjacent lane, the systematic parameter of front and back neutral gear as analogue system is fixed up.Yet, the behavior of changing of vehicle is the subjective behavior of a complexity, not only relevant with the front and back neutral gear of adjacent lane, also should be relevant with the relative velocity of car before and after the type of vehicle, current vehicle-to-target track, driver's type (cautious style, plain edition, impulsive style), road weather condition etc.
The lane-changing intention of vehicle mainly is divided into mandatory change and selectivity is changed.Mandatory changing is vehicle owing to turn or the place ahead the restriction of traffic hazard or track using takes place and must be changed.It then is because the travel speed of vehicle does not reach or exceeded driver's psychological expectation value and change that selectivity is changed.
The lane for driver conversion mainly comprises following three processes (submodel): determine changing Lane (lane changing decision model) whether, seek the specific strategy (changing Lane implementation strategy model) of acceptable space (changing Lane condition model), lane changing.A kind of special situation is arranged in the involuntary conversion track---extruding lane changing (ForcingLane-changing), finger is under the situation that common changing Lane condition does not possess, when the wagon flow of front truck driver by the extruding adjacent lane, force the back car of a certain space to slow down, thereby squeeze out the behavior that acceptable space comes changing Lane.In case make after the above decision-making, the driver will check the condition that whether possesses changing Lane, promptly whether adjacent lane has acceptable preceding space and space, back.If the conditions being possessed of changing Lane, the driver will carry out lane changing.
Current vehicle n is with speed V n, acceleration a nII travels in the track, and produces lane-changing intention.Can track I and track III be arranged for the track of its selection, if select track I, then it counts gap_lead with the distance of front truck n-1, counts gap_lag with the back distance of car n+1, and the vehicle commander counts L.The desired speed of vehicle
Figure C200510112187D00142
By the decision of factors such as type of vehicle, driver's type, be defined as:
V n 0 = V &OverBar; n * &theta;
Wherein,
Figure C200510112187D00151
Be the cruising speed of n car,, be systematic parameter by the vehicle decision; θ is a coefficient of risk, and reaction driver's type is the random number of a normal distribution, between 0.5 and 1.5 (being that average is 1).θ is more little, shows that the driver is careful more, otherwise, show driver's impulsion more.The generation method of random number is as follows:
&theta; &prime; = mean + ( - 7 + &Sigma; i = 1 14 ( Random Number [ 0 . . 1 ] ) ) * S tan dard Deviation
&theta; = 0.5 , &theta; &prime; < 0.5 &theta; &prime; , 0.5 &le; &theta; &prime; &le; 1.5 1.5 , &theta; &prime; > 1.5
Wherein, mean represents average, and Random Number represents a tandom number generator, and StandardDeviation represents mean square deviation.The actual travel speed V of vehicle n: because vehicle is subjected to the restriction (as speed limit or traffic hazard etc.) in track or is subjected to the influence of front truck, often can not travel with its desired speed.
V n=min(V lane_i,V *)
Wherein, V Lane_iThe restricted speed of expression track i; V *Expression is because front truck influences and the restricted speed of a motor vehicle, and its value is calculated (seeing formula (5)) by car-following model.If V n < V n 0 , Then vehicle will produce the intention (selectivity is changed) of change lane.
A, mandatory changing
When vehicle need carry out routing (perhaps the path is determined in advance) during near the crossing again, if need turn, then may need changing Lane at the crossing, the change lane behavior of this moment is enforceable, otherwise vehicle can't arrive the destination.Influence if traffic hazard or other incidents have taken place in the place ahead of vehicle ' vehicle by the time, also will produce and force the change lane intention, otherwise that the speed of a motor vehicle will be reduced to will be zero.This situation also is applicable to the traffic jam situation, and the speed of a motor vehicle of this moment reduces to zero.As shown in Figure 1, suppose that vehicle is with speed V nTravel, it is l apart from the accident spot distance nProduce and force lane-changing intention, and with retarded velocity a nSlow down, perhaps vehicle n can't should be able to guarantee to stop before accident spot under the situation of change lane.Therefore:
a n = - V n 2 2 ( l n - &sigma; )
Wherein, a nRepresent vehicle n for negative value and slow down that σ is a safety allowance, show that vehicle σ rice before accident spot stops.Generally speaking, near more when the vehicle distances accident spot, then the intention of its change lane is strong more, definition:
p n ( t ) = 1 - r * l n ( t ) - &sigma; l n
p n(t) probability that changes for vehicle enforcement, l n(t) be the distance of t moment vehicle n apart from accident spot.R is relevant with driver's type, is the function of coefficient of risk θ, and the span of θ is [0.5,1.5], and r is the subtraction function of θ, is defined as follows:
r=0.1θ 2-0.45θ+0.95
See that easily the span of r is that it will be with retarded velocity a after [0,1] produced the intention of change lane as vehicle n nSlow down, and check whether gap_lead satisfies the requirement of its change lane, and promptly whether gap_lead is more than or equal to the desired following distance gap_lead_needed of car-following model.Definite foundation of gap_lead_needed is: because vehicle n will change track I, it should be used as itself and travel on the I of track, and is a car with vehicle n-1, satisfies car-following model.If gap_lead has satisfied the desired following distance gap_lead_needed of car-following model, vehicle n can not give it the gun, then judges whether gap_lag satisfies its change lane to track I requirement.If gap_lag_needed also satisfies the requirement of car-following model, then vehicle n changes, otherwise vehicle n sends and changes signal to vehicle n+1, and waits for the response of vehicle n+1.And vehicle n+1 is with Probability p n(t) whether decision slows down abdicate enough spaces for vehicle n.If vehicle n still can't change when arriving accident spot, its speed reduces to zero.It stopped and waited for this moment, and constantly sent the request of changing, its p n(t)=1.Acceleration a at vehicle nUnder the known condition of relative velocity, the value of gap_lead_needed and gap_lag_needed can be released by car-following model.This paper adopts the Herman car-following model:
a n = a 0 * V n &alpha; ( gap _ lead _ needed ) &beta; * ( V n - 1 - V n )
a n - 1 = a 0 * V n + 1 &alpha; ( gap _ lag _ needed ) &beta; * ( V n - V n + 1 )
Wherein, α, β are systematic parameter.When α=, during β=2, the Herman model changes the Pipes model into.When α=0, β=1, change the Gazis model into.In sum, after vehicle produces the pressure lane-changing intention, it will at first slow down, and the select target track.After having determined the target track, judge that again it is at the front and back in target track neutral gear.If the front and back neutral gear all satisfies, then implement to change.Otherwise if preceding shelves gap_lead_needed does not satisfy, it will continue to slow down.If shelves gap_lag_needed in back does not satisfy, it just backward car n+1 send the request of changing, back car is with Probability p n(t) whether decision slows down to abdicate enough neutral gears.p n(t) be a variable that increases progressively, along with vehicle n is near more apart from accident spot, value is big more.If because traffic congestion or other special circumstances, at p nO'clock (t)=1, vehicle n still can't change, and speed of its this moment has reduced to zero, promptly stops and waits for.
B, selectivity are changed
If the actual travel speed V of vehicle n nLess than its desired speed
Figure C200510112187D00171
Then vehicle will produce the intention that selectivity is changed.With mandatory changing different be, when it can can't not satisfy because of the restriction of objective condition and stop-for-waiting, vehicle n only can continue in former lanes with lower speed, thus its behavior of changing with mandatory change different.After vehicle n produces lane-changing intention, whether neutral gear gap_lead, gap_lag met the demands before and after it will judge it, then begin the behavior of changing as satisfying, that wherein discusses in the value of gap_lead_needed, gap_lag_needed and mandatory the changing is the same, promptly satisfies formula (5).If gap_lead<gap_lead_needed, then it will slow down, the normal retarded velocity that retarded velocity is picked up the car (normal retarded velocity is a systematic parameter, and is relevant with factors such as type of vehicle, driver's types) is reduced to speed till the requirement that can satisfy gap_lead_needed always.Be equivalent to vehicle n this moment and on the I of track, travel, though it is still on this track with person's vehicle n-1.As shown in Figure 2, behind gap_lead 〉=gap_lead_needed, vehicle n judges gap_lag more whether greater than gap_lag_needed, if do not satisfy, it will continue to travel with existing speed, and change signal for the vehicle n+1 request of sending.Vehicle n+1 is with certain Probability p N+1Select whether to slow down abdicate enough neutral gears for vehicle n.p N+1Be defined as
p n + 1 = min ( 0.75 , &alpha; ( V 0 - V n 0 ) ( 1.5 - &theta; ) )
α is a systematic parameter, gets 0.2; θ is driver's an impulsion coefficient.Find out that thus vehicle n might can't finish the behavior of changing, also might behind certain later vehicle of vehicle n+1, finish the behavior of changing.
7, realize traffic simulation
The traffic simulation implementation method as shown in Figure 3.Wherein the wagon flow in each track adopts the data structure of chain sheet form to preserve.
Its traffic simulation process is:
The emulation thinking that this traffic flow simulation system is total: intermittent scanning method
Simulated clock simulation clock is pushed ahead by set time step-length (must be enough little), whenever pushing away the future event that further all closes on regard to run-down takes place constantly and the generation condition. see the incident that whether is equal to or less than current time constantly and has or not the generation condition to satisfy that produces, if have then simulate this incident, otherwise just continue to push ahead simulated clock simulation clock. so constantly repeat down, finish up to the emulation simulation time.
After vehicle sends, started timer (settimer), system state and statistical variable etc. are put with initial value. calculate the speed of each car in each simulation time section (20ms), total distance of acceleration and vehicle to run. each step all will be judged front vehicles and next door proximate vehicle, determine whether and to change trains, as change trains and just quicken and forward to the track, next door, as can not be just with following the model control rate of speeding. in each simulation time section, we can obtain upgrading after the positional information of car the nodes of locations of this car. also to judge whether to dispatch a car and to withdraw from the condition (simulation time) of emulation at last dissatisfied. and to dispatch a car as system requirements and then readjust the distribution vehicle model. if the simulation end condition satisfies, and then finishes emulation.
8, determine the air regime determinative: it comprises: vehicle fleet size, the vehicle pollutant emission factor, vehicle average velocity, wind speed, length of tunnel, external environment situation;
(1) air regime determination data
Air regime determinative: vehicle fleet size, the vehicle pollutant emission factor, vehicle average velocity, wind speed, length of tunnel, external environment situation.Wherein length of tunnel is known, and the air regime of external environment is obtained by actual measurement, below is other each determination method for parameter.
A, vehicle auto-pollution thing emission factor
The on-highway motor vehicle pollutant emission factor: the quality of the pollutant of the automotive average solo running unit mileage discharging on highway of travelling, the g/ of unit (km.) the vehicle pollutant emission factor is mainly by measuring, and the method for measurement mainly contains two clocks:
A. the laboratory measurement of the bicycle pollutant emission factor
This method is to the measurement of the pollutant emission factor of the automobile that using on testing laboratory's dynamometer machine.
The discreteness that can find various auto-pollution thing emission factors in the measurement is very big, and the very large situation of error often appears in the measurement pollutant emission of therefore adopting the pollutant emission factor of minority bicycle to calculate in the actual traffic.
B. the measurement of the average bicycle pollutant emission factor in the traffic tunnel
This method is by environmental elements such as wind speed in detection operation tunnel internal contamination concentration profile and the tunnel, can obtain the average bicycle pollutant emission factor in the wagon flow by atmospheric diffusion equation again.
The pollutant emission factor that draws like this is the pollutant emission level of the actual motor vehicle wagon flow of representative under time of day, so also more reliable.This method is extensively adopted by western countries.
The quantity of B, vehicle and average overall travel speed
The quantity of vehicle and average velocity can count by measuring emulation module.
C, wind speed
Wind speed in the tunnel outside the Pass having with tunnel structure, mainly is subjected to three factor affecting: flow naturally, vehicle influence, fan.Here put aside natural cause, only consider the influence of vehicle and fan.
Vehicle is to Influences on Wind Velocity
Can draw by momentum or theorem of kinetic energy according to measuring average velocity and average front face area.
Fan is to Influences on Wind Velocity
Power and Energy conservation law according to fan calculate fan to Influences on Wind Velocity.
(2) air regime realistic model
Long because of the tunnel, can think that pollutant distribution is even on the cross section.So the tunnel air situation is regarded as one-dimensional stable transport of substances equation.Do not consider the chemical reaction attenuation process of automotive emissions, then obtain according to the stable state mass-conservation equation:
u ( x ) &PartialD; C ( x ) &PartialD; x = q - kC ( x )
Wherein:
C (x): tunnel internal contamination substrate concentration mg/m3
U (x): the wind speed in the tunnel, m/s
K: pollutant is rate of descent in the tunnel, s-1
Q: unit volume pollutant emission speed or edge are strong in the tunnel, mg/ (s.m3)
9, set up the three-dimensional analogue system, the general structure of three-dimensional analogue system as shown in Figure 4.The tunnel checkout equipment in real time or the data of analog detection, after pre-service, pass to each emulation module in the three-dimensional virtual environment,, utilize the mathematical model in the emulation module through behind the three-dimensional artificial, and, make Based Intelligent Control suggestion to tunnel device in conjunction with knowledge and experience through accumulation.Each functions of modules is as follows.
● detect the pretreatment module of data
Detect data such as vehicle, environmental aspect in the tunnel, and pass to and pass to tunnel mutual dynamic 3 D dummy emulation system model;
● tunnel three-dimensional range module
Realize the panorama in tunnel and local interactive three-dimensional roaming, make the observer watch the various piece in tunnel, comprise the duty of this facility according to the wish of oneself.
● the tunnel traffic emulation module
The traffic simulation module can be according to detecting traffic in the data in real time emulation tunnel.
● the emulation of tunnel air situation
Can be by the difference of color, the distribution and the variation of aspects such as the C0 concentration of air, air themperature in the real-time demonstration tunnel in virtual three-dimensional tunnel scene.
● tunnel illumination situation emulation module
React the illumination state in tunnel by the brightness in the three-dimensional scenic, the illumination state changes with the light conditions of real-time detection.
● intelligent control module
Intelligent control module is the mathematical model of utilizing in above-mentioned 5 kinds of emulation modules, and in conjunction with the knowledge and experience through accumulation, sets up the Based Intelligent Control model, makes the suggestion of the Based Intelligent Control of tunnel device or realizes real-time control to equipment.
Above said content only is the basic explanation of the present invention under conceiving, and according to any equivalent transformation that technical scheme of the present invention is done, all should belong to protection scope of the present invention.

Claims (1)

1, a kind of mutual dynamic virtual implementation method that is used for the tunnel comprehensively monitoring is characterized in that method may further comprise the steps:
(1) adopt VC constructing system platform and related interfaces, applying three-dimensional graphical simulation instrument OpenInventor realizes the virtual emulation of three-dimensional scenic;
(2) set up three-dimensional scenic;
By three-dimensional CAD software, UG, Pro-E set up, and read in simulating scenes by " Virtual RealityModeling Language " mode again for complicated model;
(3) foundation comprises the required knowledge base of emulated data and system, specifically comprises:
● model data:
Comprise vehicle, tunnel model data;
● the raw data of emulation and parameter:
Comprise vehicle property parameters, tunnel condition parameter, external environment condition parameter;
● the analysis of simulation result and statistics:
The statistics that comprises vehicle fleet size in the tunnel, average velocity, maximum carbonomonoxide concentration;
● the simulation analysis knowledge base
Be meant that the application simulation result data carries out the knowledge or the model of assay to the tunnel situation, use them and can provide suggestion is controlled in the tunnel;
(4) adopt 3D mouse to realize tunnel panorama or local interactive three-dimensional roaming;
(5) the dynamic generation of vehicle, storage and dynamically disappearance;
Use the chained list class CobList of VC itself, CobList carries out the storage of vehicle; When vehicle arrives preposition, vehicle is disappeared, when vehicle arrival destination need disappear, that piece internal memory that distributes before just cancelling, and from the tunnel simulating scenes, disappear simultaneously;
(6) set up the Traffic Flow Simulation mathematical model:
Comprise: A, vehicle produce the model model of promptly dispatching a car, and described vehicle produces the initialization that model is mainly used in the emulation monomer, and this model is finished the initialization of driver's attribute and vehicle attribute;
It is the vehicle number that sets out that is used to describe source node in the continuous time interval that B, travel time produce model, and meets Poisson distribution;
C, car-following model, comprise free flow pattern, urgent car-following model and general with speeding model, the free flow pattern be meant when vehicle be in a car position or with the leading vehicle distance in track greater than time headway when speeding boundary during greater than 8 seconds, vehicle is in free transport condition, urgent car-following model is meant when another vehicle and leading vehicle distance during less than a certain preset value, adopt urgent car-following model, general with the model of speeding be meant when the time headway of adjacent two cars less than when sailing threshold values and not arriving the minimum value of time headway, vehicle is in the state of sailing of following;
D lane changing model: the lane-changing intention of vehicle, mainly be divided into mandatory change and selectivity is changed, mandatory changing is vehicle owing to turn or the place ahead the restriction of traffic hazard or track using takes place and must be changed, and it then is because the travel speed of vehicle does not reach or exceeded driver's psychological expectation value and change that selectivity is changed; The lane changing model mainly comprises following three processes: the changing Lane implementation strategy model that determines the specific strategy of the lane changing decision model of changing Lane whether, the changing Lane condition model of seeking acceptable space, lane changing;
(7) realize traffic simulation: the wagon flow in each track adopts the structure of chain sheet form to preserve simulation process intermittent scanning method;
(8) determine the air regime determinative; It comprises: vehicle fleet size, the vehicle pollutant emission factor, vehicle average velocity, wind speed, length of tunnel, external environment situation;
(9) set up the three-dimensional analogue system, it comprises with lower module:
● detect the pretreatment module of data
Detect vehicle, environmental aspect data in the tunnel, and pass to tunnel mutual dynamic 3 D dummy emulation system model;
● tunnel three-dimensional range module
Realize the panorama in tunnel and local interactive three-dimensional roaming, make the observer watch the various piece in tunnel, comprise the duty of this facility according to the wish of oneself;
● the tunnel traffic emulation module
The traffic simulation module can be according to detecting traffic in the data in real time emulation tunnel;
● tunnel air situation emulation module
By the difference of color, in virtual three-dimensional tunnel scene, show the CO concentration of air in the tunnel, distribution and the variation aspect the air themperature in real time;
● tunnel illumination situation emulation module
React the illumination state in tunnel by the brightness in the three-dimensional scenic, the illumination state changes with the light conditions of real-time detection;
● intelligent control module
Intelligent control module is the mathematical model of utilizing in above-mentioned 5 kinds of emulation modules, and in conjunction with the knowledge and experience through accumulation, sets up the Based Intelligent Control model, makes the suggestion of the Based Intelligent Control of tunnel device or realizes real-time control to equipment.
CNB2005101121875A 2005-12-29 2005-12-29 Interdynamic virtual realizing method for tunnel compound monitoring control Active CN100501750C (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CNB2005101121875A CN100501750C (en) 2005-12-29 2005-12-29 Interdynamic virtual realizing method for tunnel compound monitoring control

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CNB2005101121875A CN100501750C (en) 2005-12-29 2005-12-29 Interdynamic virtual realizing method for tunnel compound monitoring control

Publications (2)

Publication Number Publication Date
CN1991845A CN1991845A (en) 2007-07-04
CN100501750C true CN100501750C (en) 2009-06-17

Family

ID=38214098

Family Applications (1)

Application Number Title Priority Date Filing Date
CNB2005101121875A Active CN100501750C (en) 2005-12-29 2005-12-29 Interdynamic virtual realizing method for tunnel compound monitoring control

Country Status (1)

Country Link
CN (1) CN100501750C (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10760512B2 (en) 2018-04-25 2020-09-01 Ford Global Technologies, Llc Methods and systems for an aftertreatment system

Families Citing this family (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101364241B (en) * 2007-08-08 2010-06-02 同济大学 Computation method of shield tunnel liner continuous and nonuniform stiffness model structure
CN101235724B (en) * 2008-02-02 2010-12-08 西南交通大学 Express highway adjoining tunnel linkage aeration control method
CN101235723B (en) * 2008-02-02 2010-08-18 西南交通大学 Express highway section multi- tunnel gathering type intelligent aeration control method
CN101882166B (en) * 2009-05-08 2012-08-22 珠海菁英节能科技有限公司 Illumination layout simulation method and system
CN101763103B (en) * 2009-12-18 2011-09-14 武汉理工大学 L-DNA simulate monitoring method and system of long city tunnel
CN101938878A (en) * 2010-09-19 2011-01-05 天津大学 Automatic control method for tunnel LED lighting based on intelligent expert illuminance curve
CN102289656B (en) * 2011-05-11 2013-03-27 苏州两江科技有限公司 Method for calculating effect of traffic flow on city pollution
CN102831786B (en) * 2011-06-16 2016-05-18 深圳市安华信科技发展有限公司 A kind of method for supervising of vehicle driving state in tunnel and supervising device thereof
CN102521868B (en) * 2011-11-30 2017-04-05 中国神华能源股份有限公司 Railway information visualization method
FR2984557B1 (en) * 2011-12-20 2014-07-25 IFP Energies Nouvelles SYSTEM AND METHOD FOR PREDICTING EMISSIONS OF POLLUTANTS OF A VEHICLE WITH SIMULTANEOUS CALCULATIONS OF CHEMICAL KINETICS AND EMISSIONS
CN102682155A (en) * 2012-03-16 2012-09-19 王晓原 Network analysis micro-simulation system for urban road traffic
CN102779357A (en) * 2012-04-20 2012-11-14 同济大学 Expressway tunnel and tunnel group operation environment visual scene simulation method and system
CN102769977B (en) * 2012-07-18 2014-06-11 招商局重庆交通科研设计院有限公司 Method for determining brightness requirements of middle section of underground passage based on traffic flow principle
CN103235843B (en) * 2013-04-03 2015-10-28 北京交通大学 A kind of urban railway transit train running optimizatin control simulation method and system
CN104181871A (en) * 2013-05-27 2014-12-03 万克林 Intelligent environment control system
CN104183011A (en) * 2013-05-27 2014-12-03 万克林 Three-dimensional interactive virtual reality (3D IVR) restoring system
CN103425054B (en) * 2013-08-21 2016-01-27 国家电网公司 A kind of based on digitized electric power tunnel construction control method
CN104361773A (en) * 2014-09-30 2015-02-18 北京邮电大学 Virtual experiment system and implementation method thereof
CN105092276B (en) * 2015-08-31 2019-06-04 招商局重庆交通科研设计院有限公司 The test method that lining cutting chip off-falling influences tunnel in service operation safety
CN105045397B (en) * 2015-08-31 2019-07-26 招商局重庆交通科研设计院有限公司 The test method that tunnel intraoral illumination environment influences tunnel in service operation safety
CN105181000B (en) * 2015-08-31 2019-04-02 招商局重庆交通科研设计院有限公司 The test method and device that environmental factor influences tunnel operation safety
CN108846644B (en) * 2018-06-22 2021-12-03 中船第九设计研究院工程有限公司 Integrated simulation technology, cooperative work, knowledge management and project management and control system
CN109035863B (en) * 2018-08-09 2021-11-23 北京智行者科技有限公司 Forced lane-changing driving method for vehicle
CN109002674A (en) * 2018-10-09 2018-12-14 浙江省水利水电勘测设计院 A kind of tunnel group construction speed emulation mode and system
CN112947238B (en) 2021-03-15 2021-11-09 哈尔滨工业大学 Industrial robot real-time control system based on VR technique
CN113538863B (en) * 2021-04-13 2022-12-16 交通运输部科学研究院 Tunnel digital twin scene construction method and computer equipment
CN113706883B (en) * 2021-08-12 2022-11-29 广州大学 Tunnel section safe driving system and method
CN114936456B (en) * 2022-05-18 2023-07-11 西南交通大学 Tunnel construction organization scheme simulation method, computer device and computer readable storage medium

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
公路隧道交通流的数据挖掘. 许宏科,揣锦华,张华,樊海玮.长安大学学报,第25卷第4期. 2005
公路隧道交通流的数据挖掘. 许宏科,揣锦华,张华,樊海玮.长安大学学报,第25卷第4期. 2005 *
高速公路隧道交通监视与控制***. 张,洋,田志学.交通与计算机,第19卷第3期. 2001
高速公路隧道交通监视与控制***. 张,洋,田志学.交通与计算机,第19卷第3期. 2001 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10760512B2 (en) 2018-04-25 2020-09-01 Ford Global Technologies, Llc Methods and systems for an aftertreatment system

Also Published As

Publication number Publication date
CN1991845A (en) 2007-07-04

Similar Documents

Publication Publication Date Title
CN100501750C (en) Interdynamic virtual realizing method for tunnel compound monitoring control
Altan et al. GlidePath: Eco-friendly automated approach and departure at signalized intersections
Jiang et al. Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment
Huang et al. Ecological driving system for connected/automated vehicles using a two-stage control hierarchy
Yang et al. Eco-driving system for connected automated vehicles: Multi-objective trajectory optimization
Coelho et al. Effect of roundabout operations on pollutant emissions
CN101807224B (en) Mesoscopic-microcosmic integrated traffic simulation vehicle flow loading method
CN101639871B (en) Vehicle-borne dynamic traffic information induction system analog design method facing behavior research
US20130304380A1 (en) Methods and apparatus for estimating power usage
CN106898143A (en) A kind of magnitude of traffic flow modeling method of pilotless automobile
CN103116608A (en) Method of reproducing traffic flow on express way
CN101295326B (en) Method for generating OD matrix based on GPS data, traffic simulation method thereof
Lee et al. Environmental impacts of a major freight corridor: a study of I-710 in California
Johari et al. Impacts of bus stop location and berth number on urban network traffic performance
Németh et al. Optimised speed profile design of a vehicle platoon considering road inclinations
CN107657345A (en) A kind of pedestrian&#39;s walking behavior prediction method based on Markovian state&#39;s saltus step
Pi et al. Automotive platoon energy-saving: A review
Samaras et al. Development of a methodology and tool to evaluate the impact of ICT measures on road transport emissions
Ye et al. An advanced simulation framework of an integrated vehicle-powertrain eco-operation system for electric buses
CN110119528A (en) A kind of random traffic flow simulation system of bridge based on intelligent body cellular automata
Ahn et al. Traffic flow theory and characteristics
CN117373243A (en) Three-dimensional road network traffic guidance and emergency rescue collaborative management method for underground roads
van Wageningen-Kessels et al. Traffic flow modeling: A genealogy
Maheshwari An urban design response to the technological shift in transportation: How to conduct urban design with vehicle automation, sharing and connectivity
CN102938201A (en) Electron hole microscopic traffic flow modeling method in density unsaturation state

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant