CN112820126B - Road right priority operation control and simulation method for non-invasive guided transport vehicle - Google Patents
Road right priority operation control and simulation method for non-invasive guided transport vehicle Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/087—Override of traffic control, e.g. by signal transmitted by an emergency vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/081—Plural intersections under common control
- G08G1/083—Controlling the allocation of time between phases of a cycle
Abstract
The invention provides a method for controlling and simulating road right priority operation of a non-invasive guided transport vehicle, which comprises the following steps: s1: respectively establishing a non-invasive road right priority operation control mode facing the road section, the entrance way and the intersection area; s2: formulating an open state and closed state switching rule of the intelligent spike system, and establishing an intelligent spike control mode cooperated with the road right priority operation control mode; s3: forming a mixed traffic flow microscopic simulation method comprising guiding transportation vehicles and social vehicles according to the road right priority operation control mode and the intelligent spike control mode; s4: and calculating the benefit value of the road priority operation control mode parameter set according to the hybrid traffic flow microscopic simulation method, and determining an optimal mode parameter set. The invention overcomes the dependence of the traditional road right priority control technology on special road space, can provide priority right of way for guiding transport vehicles under mixed traffic conditions, and solves the key technical bottleneck in operation and popularization.
Description
Technical Field
The invention belongs to the field of road traffic vehicle operation control, and relates to a non-invasive type guided transport vehicle right-of-way priority operation control and simulation method.
Background
The guided transportation system is a novel public transportation mode which is oriented to a vehicle-road cooperative intelligent road environment and combines the running characteristics of rail vehicles and advanced vehicle control technology, has the novel technical characteristics of variable marshalling, semi-automatic driving, tracking self-guided operation and the like compared with the traditional tramcar, and is one of the key research and development and equipment manufacturing directions special for the key research and development plan of 'advanced rail transit' of the department of science and technology in China.
The guide transportation vehicle gets rid of the constraint of the physical steel rail, does not depend on an independent operation space, and can adapt to the complex traffic condition mixed with social vehicles. For a novel public transportation mode, how to ensure the prior right of way of a guided transportation vehicle under the public right of way becomes a key operation difficult problem of the application and popularization link of a guided transportation system, and a matched right of way priority technology is urgently needed. At present, the guided transport vehicle is still in the stage of equipment development and operation theory exploration, so that a road right priority control mode adapting to the unique operation characteristics of the guided transport vehicle does not exist. In the prior art of controlling the prior operation of the right of way of the traditional ground public transport and tram, the special road space in the form of a special steel rail or a special bus way is generally relied on, so that the utilization rate of the road space is low, and the method can not be applied to guided transport vehicles mixed with social vehicles.
The development of the guide transportation vehicle takes full use of road resources as a basic principle, and a special road space is liberated by introducing an advanced vehicle control technology under a vehicle-road cooperative environment. In view of the above, the invention provides a non-invasive road right priority control technology suitable for unique running characteristics of a guided vehicle, wherein virtual non-invasive sections are respectively arranged at the head and the tail of the guided vehicle, and the non-invasive sections on a lane are transmitted to surrounding social vehicle drivers in real time through an intelligent spike system, so that the influence of the following and lane changing behaviors of the social vehicles on the smooth running of the guided vehicle is avoided. Meanwhile, the simulation method of the control technology is provided from a microscopic traffic flow level, and the selection of relevant control technology parameters is guided by means of a simulation result, so that the method has important and urgent practical significance for application popularization and operation mode exploration after the research and the completion of the guided transportation system.
Disclosure of Invention
The invention aims to provide a method for controlling and simulating the road right priority operation of a non-invasive guided transport vehicle, which effectively provides the guided transport vehicle with the priority right of way under the mixed traffic condition.
The technical scheme of the invention is as follows: a method for controlling and simulating road priority operation of a non-intrusive guide transport vehicle comprises the following steps:
s1: respectively constructing a non-invasive road right priority operation control mode facing a road section area, an entrance road area and an intersection area so as to ensure the priority right of a guided transport vehicle in a mixed traffic flow, wherein the road right priority operation control mode is implemented by matching with an intelligent spike system which is cooperated with the road right priority operation control mode;
s2: establishing an intelligent spike control mode cooperated with the road right priority operation control mode according to the road right priority operation control mode, wherein the intelligent spike is communicated with a coil sensor at a corresponding position of a lane, a joint control rule consistent with the traffic flow direction is adopted among the intelligent spikes, and the intelligent spike control mode comprises an open state-closed state switching rule and a closed state-open state switching rule;
s3: according to a road right priority operation control mode and an intelligent spike control mode, a mixed traffic flow microscopic simulation method comprising a guide transport vehicle and social vehicles is formed, and the mixed traffic flow microscopic simulation method comprises a traffic environment simulation module, a vehicle following behavior simulation module and a vehicle lane changing behavior simulation module;
s4: and according to the hybrid traffic flow microscopic simulation method, calculating the utility value of the road priority operation control mode parameter set, and determining the optimal road priority operation control mode parameter set.
In step S1, specifically, the method includes:
s11: the non-invasive road right priority operation control mode established for the road section area specifically comprises the following steps: in a road section area, when a social vehicle in front of a guided transport vehicle approaches a front-end non-invasive section due to deceleration driving, the intelligent spike system indicates the social vehicle to drive in an accelerating way or drive away from a current lane, so that the occupation of the front-end non-invasive section with the standard length of the guided transport vehicle is avoided; when the social vehicle on the side of the guide transport vehicle actively enters the front-end non-invasive section due to the accelerated running reason, the intelligent spike system indicates that the social vehicle is prohibited to occupy the front-end non-invasive section with the standard length of the guide transport vehicle through the lane changing behavior; when the social vehicle behind the guide transport vehicle approaches the rear-end non-invasive section due to acceleration driving, the intelligent spike system indicates the social vehicle to drive in a deceleration mode or in a mode of driving away from the current lane, so that the occupation of the rear-end non-invasive section with the standard length of the guide transport vehicle is avoided;
s12: the non-invasive road right priority operation control mode constructed facing the entrance way area specifically comprises the following steps: in the entrance lane area, when the social vehicles in front of the guided transportation vehicles are queued for waiting due to intersection signal control, the guided transportation vehicles can approach the social vehicles in front under the deceleration braking working condition, and the front non-intrusive interval is compressed to a parking safety distance from a standard length; when the guided vehicles do not queue at the intersection, maintaining a non-intrusive interval at the front end of the standard length;
s13: the non-invasive road right priority operation control mode established for the intersection area specifically comprises the following steps: in the intersection area, when the guided vehicles wait for queuing due to intersection signal control, after the target phase is switched to a green light state, the guided vehicles enter an acceleration working condition again when the length of the front-end non-intrusive interval is recovered to a steering safety distance from a parking safety distance; when the guided vehicles do not wait in line at the intersection, the front-end non-intrusive section is compressed to a steering safety distance from a standard length after passing through the intersection stop line.
Preferably, in step S2, specifically, the method includes:
s21: the "open state-closed state" switching rule is specifically: when a coil sensor communicated with an intelligent spike detects the head of a guide transport vehicle, receiving and analyzing state parameter information sent by the guide transport vehicle, calculating the length of the body of the guide transport vehicle by using the vehicle marshalling number, sending a closed state instruction to the intelligent spike within the range of the length of the body of the guide transport vehicle at the upstream of the linkage control, and sending a closed state instruction to the intelligent spike within the range of the standard length of the non-invasive section at the front end of the guide transport vehicle at the downstream of the linkage control, wherein the state parameter information comprises the ID of the guide transport vehicle, the standard length of the non-invasive section at the front end and the rear end, a parking safety distance, a steering safety distance, the vehicle marshalling number, an instantaneous speed, an instantaneous acceleration, a planned parking station and a time sequence;
s22: the "closed state-open state" switching rule is specifically: when the coil sensor communicated with the intelligent spike detects the tail of the guided transport vehicle, an open state instruction is sent to all the intelligent spikes of the ID record of the guided transport vehicle on the upstream of the joint control.
Preferably, in step S3, specifically, the method includes:
s31: the traffic environment simulation module has the function of establishing an integrated traffic environment containing vehicle information, road information and intersection information; the vehicle information comprises guiding transport vehicle information and social vehicle information, the guiding transport vehicle information comprises guiding transport vehicle ID, standard length of front-end and rear-end non-invasive interval, parking safety distance, steering safety distance, vehicle marshalling number, instantaneous speed time series, instantaneous acceleration time series, planned parking station and time series, located lane ID time series and located lane position coordinate time series, the social vehicle information comprises a social vehicle ID, an instantaneous speed time sequence, an instantaneous acceleration time sequence, a located lane ID time sequence and a located lane position coordinate time sequence, wherein the located lane position coordinate time sequence is a vehicle head and vehicle tail position coordinate time sequence; the road information comprises lane ID, lane position coordinates, a bearing state time sequence, intelligent spike ID and an intelligent spike state time sequence; the intersection information comprises a signal phase ID, a signal phase starting time sequence and a signal phase ending time sequence;
s32: the vehicle-following behavior simulation module comprises a following rule of a guide transport vehicle and a following rule of a social vehicle, wherein the following rule of the guide transport vehicle comprises an automatic acceleration behavior decision, an automatic deceleration behavior decision and vehicle position updating; the following rules of the social vehicles comprise the steps of determining the random slowing probability of the vehicle speed, the decision of the accelerating behavior of the driver, the decision of the decelerating behavior of the driver, the random correction of the vehicle speed and the updating of the vehicle position;
s33: the vehicle lane change behavior simulation module comprises lane change motivation judgment, safety condition judgment, lane change determination and vehicle position updating of the social vehicles.
Preferably, in step S4, specifically, the method includes:
s41: generating a road right priority control mode parameter set, wherein the road right priority control mode parameter set comprises standard length of a front-end and rear-end non-invasive interval of a guided transport vehicle, a parking safety distance, a steering safety distance and a vehicle grouping number;
s42: calculating utility values of the road right priority control mode parameter set according to a hybrid traffic flow microscopic simulation method, wherein the utility values are generalized utility values containing per-capita delay cost and per-capita energy consumption cost;
s43: and (4) iteratively solving the generalized utility values of the different road weight priority operation control mode parameter sets by utilizing a heuristic algorithm, and determining the optimal road weight priority operation control mode parameter set.
The invention has the beneficial effects that:
the invention overcomes the dependence of the traditional road right priority control technology on special road space, can provide priority right of way for the guided transportation vehicle under mixed traffic conditions, avoids the influence of the following and lane changing behaviors of social vehicles on the stable running of the guided transportation vehicle, and solves the key technical bottleneck in the operation and popularization of the guided transportation system.
Drawings
FIG. 1 is a schematic illustration of a guided vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating steps of a method for controlling and simulating the road priority operation of a non-intrusive guided transportation vehicle according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a road priority operation control mode for guided vehicles in a road segment area according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a guided vehicle right-of-way priority operation control scheme in the area of an approach according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a guided vehicle preemption-by-road operation control scheme in the intersection area in accordance with an embodiment of the present invention;
fig. 6 is a technical route schematic diagram of a hybrid traffic flow microscopic simulation method according to an embodiment of the present invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and enable its practice, and the embodiments of the present invention are not limited thereto.
As shown in fig. 1, the guided transportation system, as a novel ground public transportation tool in the pilot stage of research and development, relies on a tire-ground coupling power and multi-axis cooperative tracking operation technology, gets rid of the dependence of the traditional tramcar and subway on steel rail facilities, and can be mixed with general social vehicles; the automatic or semi-automatic driving mode is adopted for the development trend of future intelligent traffic, the grouping scale is flexible and variable, and the positioning advantages of medium and high passenger capacity, low construction cost, intelligent networking and the like are achieved. For medium and small cities, the guided transportation system is a new choice for transition from public transportation cities to subway cities, is a new practice for low-carbon transportation advocated by the nation, and has the outstanding advantages of high efficiency, economy, environmental protection and the like for improving the transportation capacity of the public transportation system.
As shown in fig. 2, a method for controlling and simulating road priority operation of a non-intrusive guided transportation vehicle includes:
s1: respectively constructing a non-invasive road right priority operation control mode facing a road section area, an entrance road area and an intersection area so as to ensure the priority right of a guided transport vehicle in a mixed traffic flow, wherein the road right priority operation control mode is implemented by matching with an intelligent spike system which is cooperated with the road right priority operation control mode;
s2: establishing an intelligent spike control mode cooperated with the road right priority operation control mode according to the road right priority operation control mode, wherein the intelligent spike is communicated with a coil sensor at a corresponding position of a lane, a joint control rule consistent with the traffic flow direction is adopted among the intelligent spikes, and the intelligent spike control mode comprises an open state-closed state switching rule and a closed state-open state switching rule;
s3: according to a road right priority operation control mode and an intelligent spike control mode, a mixed traffic flow microscopic simulation method comprising a guide transport vehicle and social vehicles is formed, and the mixed traffic flow microscopic simulation method comprises a traffic environment simulation module, a vehicle following behavior simulation module and a vehicle lane changing behavior simulation module;
s4: and according to the hybrid traffic flow microscopic simulation method, calculating the utility value of the road priority operation control mode parameter set, and determining the optimal road priority operation control mode parameter set.
As shown in fig. 3, in step S1, S11: the non-invasive road right priority operation control mode established for the road section area specifically comprises the following steps: in a road section area, when a social vehicle in front of a guided transport vehicle approaches a front-end non-invasive section due to deceleration driving, the intelligent spike system indicates the social vehicle to drive in an accelerating way or drive away from a current lane, so that the occupation of the front-end non-invasive section with the standard length of the guided transport vehicle is avoided; when the social vehicle on the side of the guide transport vehicle actively enters the front-end non-invasive section due to the accelerated running reason, the intelligent spike system indicates that the social vehicle is prohibited to occupy the front-end non-invasive section with the standard length of the guide transport vehicle through the lane changing behavior; when the social vehicle behind the guide transport vehicle approaches the rear-end non-invasive section due to acceleration driving, the intelligent spike system indicates the social vehicle to drive in a deceleration mode or in a mode of driving away from the current lane, so that the occupation of the rear-end non-invasive section with the standard length of the guide transport vehicle is avoided;
as shown in fig. 4, in step S1, S12: the non-invasive road right priority operation control mode constructed facing the entrance way area specifically comprises the following steps: in the entrance lane area, when the social vehicles in front of the guided transportation vehicles are queued for waiting due to intersection signal control, the guided transportation vehicles can approach the social vehicles in front under the deceleration braking working condition, and the front non-intrusive interval is compressed to a parking safety distance from a standard length; when the guided vehicles do not queue at the intersection, maintaining a non-intrusive interval at the front end of the standard length;
as shown in fig. 5, in step S1, S13: the non-invasive road right priority operation control mode established for the intersection area specifically comprises the following steps: in the intersection area, when the guided vehicles wait for queuing due to intersection signal control, after the target phase is switched to a green light state, the guided vehicles enter an acceleration working condition again when the length of the front-end non-intrusive interval is recovered to a steering safety distance from a parking safety distance; when the guided vehicles do not wait in line at the intersection, the front-end non-intrusive section is compressed to a steering safety distance from a standard length after passing through the intersection stop line.
In step S2, specifically, the method includes:
s21: the "open state-closed state" switching rule is specifically: when a coil sensor communicated with an intelligent spike detects the head of a guide transport vehicle, receiving and analyzing state parameter information sent by the guide transport vehicle, calculating the length of the body of the guide transport vehicle by using the vehicle grouping number, sending a closed state instruction to the intelligent spike within the range of the length of the body of the guide transport vehicle at the upstream of the joint control, and sending a closed state instruction to the intelligent spike within the range of the standard length of the non-invasive section at the front end of the guide transport vehicle at the downstream of the joint control, wherein the state parameter information comprises the ID of the guide transport vehicle, the standard length of the non-invasive section at the front end and the rear end, a parking safety distance, a steering safety distance, the vehicle grouping number, an instantaneous speed, an instantaneous acceleration, a planned parking station and a time sequence;
s22: the "closed state-open state" switching rule is specifically: when the coil sensor communicated with the intelligent spike detects the tail of the guided transport vehicle, an open state instruction is sent to all the intelligent spikes of the ID record of the guided transport vehicle on the upstream of the joint control.
As shown in fig. 6, in step S3, the technical route of the mixed traffic flow microscopic simulation method includes a traffic environment simulation module, a car following and lane changing behavior simulation module. In the implementation process, a traffic environment simulation module simulates the real-time working states of facilities and equipment such as road sections, entrance roads, intersections, signal lamps, detectors and the like and the real-time running states of different types of vehicles (namely, guided transport vehicles and social vehicles), and a microscopic traffic flow iterative simulation algorithm based on a cellular automaton theory is built in the traffic environment simulation module; the vehicle following and lane changing behavior simulation module is dynamically interacted with the traffic environment simulation module, a built-in vehicle following model and a built-in lane changing model are flexibly called according to the type and the area of the vehicle, so that the interaction in the running of two types of vehicles under the real condition is simulated, the automatic driving behavior of the guided transport vehicle and the behavior information of social vehicle drivers are transmitted into the traffic environment simulation module, the dynamic updating of the real-time running state of the vehicle is realized, and finally the running state simulation result of the mixed traffic flow is obtained and is used as the decision basis for setting the road right priority running control mode parameter set.
In step S3, specifically, the method includes:
s31: the traffic environment simulation module has the function of establishing an integrated traffic environment containing vehicle information, road information and intersection information; the vehicle information comprises guiding transportation vehicle information and social vehicle information, the guiding transportation vehicle information comprises a guiding transportation vehicle ID, a standard length of a front-end and rear-end non-invasive interval, a parking safety distance, a steering safety distance, a vehicle marshalling number, an instantaneous speed time sequence, an instantaneous acceleration time sequence, a planned parking stop point and time sequence, a located lane ID time sequence and a located lane position coordinate time sequence, wherein the coordinate time sequence of the position of the lane is the coordinate time sequence of the front part of the front non-invasive section, the tail part of the rear non-invasive section, the position of the vehicle head and the vehicle tail, the social vehicle information comprises a social vehicle ID, an instantaneous speed time sequence, an instantaneous acceleration time sequence, a located lane ID time sequence and a located lane position coordinate time sequence, wherein the located lane position coordinate time sequence is a vehicle head and vehicle tail position coordinate time sequence; the road information comprises lane ID, lane position coordinates, a bearing state time sequence, intelligent spike ID and an intelligent spike state time sequence; the intersection information comprises a signal phase ID, a signal phase starting time sequence and a signal phase ending time sequence;
s32: the vehicle-following behavior simulation module comprises following rules of a guided transport vehicle and the following rules of social vehicles, wherein the following rules of the guided transport vehicle comprise an automatic acceleration behavior decision, an automatic deceleration behavior decision and a vehicle position update; the following rules of the social vehicles comprise the steps of determining the random slowing probability of the vehicle speed, the decision of the acceleration behavior of the driver, the decision of the deceleration behavior of the driver, the random correction of the vehicle speed and the update of the vehicle position;
s321: the following rules guiding the transport vehicle comprise an automatic acceleration behavior decision, an automatic deceleration behavior decision and vehicle position updating;
s3211: the operation logic of the decision of the automatic acceleration behavior of the guided transport vehicle is as follows:
in the formula (I), the compound is shown in the specification,
the instantaneous speed of the nth vehicle (i.e., the lead vehicle or the social vehicle ID) of the mth vehicle type (i.e., the lead transportation vehicle or the social vehicle) at the area z (i.e., the road section area, the entrance lane area, or the intersection area) at time t;
the instantaneous acceleration of the nth vehicle of the mth vehicle type in the area z at the time t;
the maximum driving speed of the area z for the mth vehicle type;
the distance between the nth vehicle of the mth vehicle type and the vehicles right in front and behind the nth vehicle at the moment t;
the length of the front-end and rear-end non-intrusive section in an operating state x (i.e., an operating state adopting a standard length, a safe parking distance, or a safe steering distance);
at the time t, representing whether the front and rear vehicles of the nth vehicle of the mth vehicle type are 0-1 variables of the guiding transportation vehicle, taking 0 for no and taking 1 for yes;
s3212: the operation logic of the decision of the automatic deceleration behavior of the guided transport vehicle is as follows:
s3213: according to the following rule of the guiding transportation vehicle, the position updating rule of the guiding transportation vehicle is as follows:
in the formula (I), the compound is shown in the specification,
at the time of t +1, respectively, coordinates of the positions of the head and the tail of the nth vehicle of the mth vehicle type in the lane where the area z is located; lmThe length of the vehicle body is the length of the vehicle body of the mth vehicle type;
at the time of t +1, respectively, coordinates of the front part of the front-end non-invasive section and the tail part of the rear-end non-invasive section of the nth vehicle of the mth vehicle type at the lane position of the area z;
s322: the following rules of the social vehicles comprise the steps of determining the random slowing probability of the vehicle speed, the decision of the accelerating behavior of the driver, the decision of the decelerating behavior of the driver, the random correction of the vehicle speed and the updating of the vehicle position;
s3221: the calculation rule of the random slowing probability of the social vehicle speed is as follows:
in the formula (I), the compound is shown in the specification,
at the time t, the speed of the nth vehicle of the mth vehicle type in the area z is randomly slowed down by the probability; theta1、θ2、θ3、θ4Respectively the random slowing probabilities of the speed of the vehicle under the working conditions of ultra-long stay, short stay, acceleration and deceleration;
the accumulated parking time of the nth vehicle of the mth vehicle type in the area z at the moment of t; f. ofzA cumulative parking time threshold for zone z;
s3222: the operation logic of the social vehicle driver acceleration behavior decision is as follows:
in the formula, alphazThe value of the speed fluctuation amplitude of the social vehicle in the area z,
i.e. obeying a mean of 0 and a variance of
A standard normal distribution of (a);
s3223: the operation logic of the social vehicle driver deceleration behavior decision is as follows:
in the formula (I), the compound is shown in the specification,
at the time t + 1, the predicted speed of the nth-1 vehicle (i.e. the vehicle in front of the nth vehicle) of the mth vehicle type in the area z;
s3224: according to the calculation rule of the random slowing probability of the speed of the social vehicle, the speed random correction formula of the social vehicle is as follows:
in the formula, gamma is a value of a random slowing constant of the vehicle speed; p is a radical ofsFor judging whether the social vehicle speed isRandom values at which random slowing occurs, i.e. random values generated between 0 and 1, ps＝rand(0,1)；
S3225: according to the following rule of the social vehicles, the position updating rule of the social vehicles is as follows:
s33: the vehicle lane changing behavior simulation module comprises lane changing motivation judgment, safety condition judgment, lane changing determination and vehicle position updating of social vehicles;
s331: the social vehicle lane change engine meets the following constraint conditions that the social vehicle lane change engine is too close to a front vehicle, has at least one adjacent lane with better driving state at one side, and has a vehicle speed greater than that of a vehicle at the side rear, and the formula is as follows:
in the formula (I), the compound is shown in the specification,
the expected vehicle speed in the area z for the mth vehicle type; ζ is a safe following distance threshold value of the social vehicle; c. C1,c2,c3,c4,c5Respectively adjacent vehicles which are right in front, left in front, right in front, left in back and right in back of the vehicle n;
at time t, c ∈ { c } is the coordinate of the lane position in the zone z of the neighboring vehicle c2,c3}；lcIs the body length of vehicle c;
the speed difference between the nth vehicle and the side rear vehicle c of the mth vehicle type at the time t, and c is formed by { c ∈ [)4,c5}。
In addition, when the social vehicle invades the front end or rear end non-invasion section of the guided vehicle in an active or passive mode, whether the lane changing engine is established or not is directly judged according to the state of the intelligent spike.
S332: the lane changing behavior of the social vehicle needs to meet the lane changing safety condition, namely the speed of the vehicle after lane changing is smaller than that of the vehicle in front of the side and the safe following distance is kept between the vehicle and the adjacent vehicle, when the adjacent vehicle is a guide transport vehicle, a front end or rear end non-invasion interval with a corresponding length is additionally reserved, and the formula is as follows:
in the formula (I), the compound is shown in the specification,
the speed difference between the nth vehicle and the vehicle c in front of the side at the moment t, c belongs to { c ∈ }2,c3}。
S333: when the social vehicle has a plurality of adjacent lanes simultaneously and accords with lane change motivation and lane change safety conditions, the adjacent lane with the maximum lane change expected value is changed, and the calculation formula of the lane change expected value is as follows:
in the formula (I), the compound is shown in the specification,
at the time t, the nth vehicle of the mth vehicle type is changed into the expected value of the lane where the vehicle c is located;
s334: according to the lane change rule of the social vehicles, the position updating rule of the social vehicles is as follows:
in the formula (I), the compound is shown in the specification,
at the time t, the nth vehicle of the mth vehicle type is changed into the coordinate of the corresponding position in the lane in the area z; p is a radical ofiFor the random number used to determine whether social vehicle lane change behavior occurs, i.e. a random value generated between 0 and 1, piRand (0, 1); theta is the average lane change probability of the social vehicles;
in step S4, specifically, the method includes:
s41: generating a set of road right priority control pattern parameters, wherein the set of road right priority control pattern parameters comprises standard length of a front-end and rear-end non-intrusive interval of a guided transport vehicle, parking safety distance, steering safety distance and vehicle grouping number;
s42: calculating utility values of the road right priority control mode parameter set according to a hybrid traffic flow microscopic simulation method, wherein the utility values are generalized utility values containing per-capita delay cost and per-capita energy consumption cost;
s421: calculating the per-person delay under the road right priority operation control parameter set, wherein the formula is as follows:
in the formula, D is the per-capita delay under the priority operation control parameter set phi of the road right in the simulation period; qmThe number of vehicles of the mth vehicle type; chi shapemThe passenger capacity of the mth vehicle type; rm,nThe total delay of the nth vehicle of the mth vehicle type; r ism,n(t) delay of the nth vehicle of the mth vehicle type at the time t; mu.smExpected total delay for the mth vehicle type;
s422: calculating the per-person energy consumption under the road right priority operation control parameter set, wherein the formula is as follows:
in the formula, F is the per-capita energy consumption under the priority operation control parameter set phi of the road right in the simulation time period;
respectively the coal carbon consumption equivalent values of the nth guide transport vehicle and the social vehicle at the time t; omega is a conversion coefficient between the number of the guide transportation vehicle groups and the energy consumption;
for guiding the electric energy consumption and coal consumption of transport vehiclesCalculating coefficients;
the conversion coefficient of the social vehicle fuel consumption and the coal consumption is obtained; y {. is a microscopic electric energy consumption equation of the guided transport vehicle about the exponential form combination term of the instantaneous speed and the instantaneous acceleration; z {. is a microscopic fuel consumption equation of the social vehicle about an exponential form combination term of instantaneous speed and instantaneous acceleration; h. k is an index term of instantaneous speed and instantaneous acceleration in the microscopic energy consumption equation respectively;
s423: according to the per-person delay and the per-person energy consumption, calculating the generalized utility value of the road right priority operation control parameter set, wherein the formula is as follows:
K|Φ＝δ1κD+δ2τF
in the formula, K is a generalized utility value under a road right priority operation control parameter set phi; delta1、δ2The weight coefficients of the per-person delay D and the per-person energy consumption F are respectively; kappa and tau are respectively economic quantization coefficients of human-average delay and human-average energy consumption;
s43: and (4) iteratively solving the generalized utility values of the different road weight priority operation control mode parameter sets by utilizing a heuristic algorithm, and determining the optimal road weight priority operation control mode parameter set.
Those of ordinary skill in the art will understand that: the drawings are merely schematic representations of one embodiment, and the flow charts in the drawings are not necessarily required to practice the present invention.
Claims (4)
1. A method for controlling and simulating road priority operation of a non-intrusive guide transport vehicle comprises the following steps:
s1: respectively constructing a non-invasive road right priority operation control mode facing a road section area, an entrance road area and an intersection area so as to ensure the priority right of a guided transport vehicle in a mixed traffic flow, wherein the road right priority operation control mode is implemented by matching with an intelligent spike system cooperated with the road right priority operation control mode;
s2: establishing an intelligent spike control mode cooperated with the road right priority operation control mode according to the road right priority operation control mode, wherein the intelligent spike is communicated with a coil sensor at a corresponding position of a lane, a joint control rule consistent with a traffic flow direction is adopted among the intelligent spikes, and the intelligent spike control mode comprises an open state-closed state switching rule and a closed state-open state switching rule;
s3: forming a mixed traffic flow microscopic simulation method comprising guide transportation vehicles and social vehicles according to the road right priority operation control mode and the intelligent spike control mode, wherein the mixed traffic flow microscopic simulation method comprises a traffic environment simulation module, a vehicle following behavior simulation module and a vehicle lane changing behavior simulation module;
s4: according to the hybrid traffic flow microscopic simulation method, calculating the utility value of the road priority operation control mode parameter set, and determining the optimal road priority operation control mode parameter set;
in step S1, specifically, the method includes:
s11: the non-invasive road right priority operation control mode established for the road section area specifically comprises the following steps: in a road section area, when a social vehicle in front of a guided transport vehicle approaches a front-end non-invasive section due to deceleration driving, the intelligent spike system indicates the social vehicle to drive in an accelerating way or drive away from a current lane, so that the occupation of the front-end non-invasive section with the standard length of the guided transport vehicle is avoided; when the social vehicle on the side of the guide transport vehicle actively enters the front-end non-invasive section due to the accelerated running reason, the intelligent spike system indicates that the social vehicle is prohibited to occupy the front-end non-invasive section with the standard length of the guide transport vehicle through the lane changing behavior; when the social vehicle behind the guide transport vehicle approaches the rear-end non-invasive section due to acceleration driving, the intelligent spike system indicates the social vehicle to drive in a deceleration mode or in a mode of driving away from the current lane, so that the occupation of the rear-end non-invasive section with the standard length of the guide transport vehicle is avoided;
s12: the non-invasive road right priority operation control mode constructed facing the entrance way area specifically comprises the following steps: in the entrance lane area, when the social vehicles in front of the guided transportation vehicles are queued for waiting due to intersection signal control, the guided transportation vehicles approach the social vehicles in front under the deceleration braking working condition, and the front non-intrusive interval is compressed to a parking safety distance from a standard length; when the guided vehicles do not queue at the intersection, maintaining a non-intrusive interval at the front end of the standard length;
s13: the non-invasive road right priority operation control mode established for the intersection area specifically comprises the following steps: in the intersection area, when the guided vehicles wait for queuing due to intersection signal control, after the target phase is switched to a green light state, the guided vehicles enter an acceleration working condition again when the length of the front-end non-intrusive interval is recovered to a steering safety distance from a parking safety distance; when the guided vehicles do not wait in line at the intersection, the front-end non-intrusive section is compressed to a steering safety distance from a standard length after passing through the intersection stop line.
2. The method for road priority operation control and simulation of a non-intrusive guided transport vehicle as claimed in claim 1, wherein in step S2, the method specifically comprises:
s21: the "open state-closed state" switching rule is specifically: when a coil sensor communicated with an intelligent spike detects the head of a guide transport vehicle, receiving and analyzing state parameter information sent by the guide transport vehicle, calculating the length of the body of the guide transport vehicle by using the vehicle grouping number, sending a closed state instruction to the intelligent spike within the range of the length of the body of the guide transport vehicle at the upstream of the joint control, and sending a closed state instruction to the intelligent spike within the range of the standard length of the non-invasive section at the front end of the guide transport vehicle at the downstream of the joint control, wherein the state parameter information comprises the ID of the guide transport vehicle, the standard length of the non-invasive section at the front end and the rear end, a parking safety distance, a steering safety distance, the vehicle grouping number, an instantaneous speed, an instantaneous acceleration, a planned parking station and a time sequence;
s22: the "closed state-open state" switching rule is specifically: when the coil sensor communicated with the intelligent spike detects the tail of the guided transport vehicle, an open state instruction is sent to all the intelligent spikes of the ID record of the guided transport vehicle on the upstream of the joint control.
3. The method for road priority operation control and simulation of a non-intrusive guided transport vehicle as claimed in claim 1, wherein in step S3, the method specifically comprises:
s31: the traffic environment simulation module has the function of establishing an integrated traffic environment containing vehicle information, road information and intersection information; the vehicle information comprises guiding transportation vehicle information and social vehicle information, the guiding transportation vehicle information comprises a guiding transportation vehicle ID, a standard length of a front-end and rear-end non-invasive interval, a parking safety distance, a steering safety distance, a vehicle marshalling number, an instantaneous speed time sequence, an instantaneous acceleration time sequence, a planned parking stop point and time sequence, a located lane ID time sequence and a located lane position coordinate time sequence, wherein the coordinate time sequence of the position of the lane is the coordinate time sequence of the front part of the front non-invasive section, the tail part of the rear non-invasive section, the position of the vehicle head and the vehicle tail, the social vehicle information comprises a social vehicle ID, an instantaneous speed time sequence, an instantaneous acceleration time sequence, a located lane ID time sequence and a located lane position coordinate time sequence, wherein the located lane position coordinate time sequence is a vehicle head and vehicle tail position coordinate time sequence; the road information comprises lane ID, lane position coordinates, a bearing state time sequence, intelligent spike ID and an intelligent spike state time sequence; the intersection information comprises a signal phase ID, a signal phase starting time sequence and a signal phase ending time sequence;
s32: the vehicle-following behavior simulation module comprises a following rule of a guiding transport vehicle and a following rule of a social vehicle, wherein the following rule of the guiding transport vehicle comprises an automatic acceleration behavior decision, an automatic deceleration behavior decision and a vehicle position update; the following rules of the social vehicles comprise the steps of determining the random slowing probability of the vehicle speed, the decision of the acceleration behavior of the driver, the decision of the deceleration behavior of the driver, the random correction of the vehicle speed and the update of the vehicle position;
s33: the vehicle lane changing behavior simulation module comprises lane changing motivation judgment, safety condition judgment, lane changing determination and vehicle position updating of social vehicles.
4. The method for road priority operation control and simulation of a non-intrusive guided transport vehicle as claimed in claim 1, wherein in step S4, the method specifically comprises:
s41: generating a set of road right priority control pattern parameters, wherein the set of road right priority control pattern parameters comprises standard length of a front-end and rear-end non-intrusive interval of a guided transport vehicle, parking safety distance, steering safety distance and vehicle grouping number;
s42: calculating utility values of the road right priority control mode parameter set according to a hybrid traffic flow microscopic simulation method, wherein the utility values are generalized utility values containing per-capita delay cost and per-capita energy consumption cost;
s43: and (4) iteratively solving the generalized utility values of the different road weight priority operation control mode parameter sets by utilizing a heuristic algorithm, and determining the optimal road weight priority operation control mode parameter set.
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