CN116246452A - Rationality analysis method for network-connected automatic driving vehicle lane planning scheme - Google Patents

Rationality analysis method for network-connected automatic driving vehicle lane planning scheme Download PDF

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CN116246452A
CN116246452A CN202310243214.0A CN202310243214A CN116246452A CN 116246452 A CN116246452 A CN 116246452A CN 202310243214 A CN202310243214 A CN 202310243214A CN 116246452 A CN116246452 A CN 116246452A
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李同飞
朱宏菲
范博
熊杰
窦雪萍
周文涵
陈艳艳
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Beijing University of Technology
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    • G08G—TRAFFIC CONTROL SYSTEMS
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Abstract

The invention provides a rationality analysis method for a network-connected automatic driving vehicle lane planning scheme, which comprises the following steps: dividing different following modes by considering the types of the front and rear vehicles and CAV vehicle formation characteristics, and according to different headway in the corresponding mixed traffic flow under the different following modes; establishing a macroscopic probability model to calculate the average headway of the vehicle and the corresponding road traffic capacity under the mixed running condition; deriving a road section impedance function applicable to the mixed traffic flow based on the research on the road traffic capacity in the mixed traffic scene; assuming that after setting the special lane, the lane selection of the CAV travelers follows the user balance condition to obtain the CAV traveler proportion of the selected special lane; and obtaining the rationality judgment condition of the special road planning scheme by comparing the total travel cost before and after the CAV special road section is set. The invention provides a condition for judging the rationality of a special road planning scheme aiming at a road section without a special road.

Description

Rationality analysis method for network-connected automatic driving vehicle lane planning scheme
Technical Field
The invention provides a rationality analysis method for a network-connected automatic driving vehicle lane planning scheme, and belongs to the technical field of automatic driving.
Background
With the development of intelligent networking technology and autopilot technology, networked autopilot vehicles (Connected and autonomous vehicles, CAVs) are recognized as the development direction of future vehicles, with great potential in improving traffic safety and traffic efficiency. Compared with the traditional manual driving vehicles (HVs), the CAV has faster response time, can keep smaller safe headway with the front vehicles, and can form a team to drive on the road by virtue of real-time communication and coordination control, which further shortens the headway between the CAV and the front vehicles, so that the CAV can remarkably improve the traffic capacity of the road. However, CAV does not completely replace HV in a short period of time, and both types of vehicles will share urban road resources for a longer period of time in the future, subject to the state of the art and acceptance.
In a mixed driving scene, a plurality of different following modes can be divided by considering the types of vehicles in front and back and CAV vehicle formation characteristics, and the different following modes correspond to different safety headway, so that the duty ratio of different types of vehicles and the spatial distribution of the different types of vehicles on a road directly influence the average headway, the vehicle density and the road traffic capacity. In summary, it is known that the traffic capacity of a road in a mixed traffic scene is not a constant value, but a random variable related to the vehicle occupancy of different types and the road space distribution thereof. In addition, as the driving behavior of the manual driving vehicle has uncertainty, the HV in the mixed driving scene can seriously interfere with the passing and formation of the CAV, so that the technical advantage of the CAV is fully exerted, the passing efficiency of the road section is improved, the CAV and the mixed driving traffic can be separated by arranging a CAV special road, the mutual interference between the CAV and the HV is reduced, and the CAV formation is promoted. However, the CAV lane planning scheme directly changes the lane selection of travelers and the total travel cost of the road sections of all vehicles, and the unreasonable planning scheme not only can not improve the traffic efficiency but also can increase the traffic jam, so that how to simply and conveniently analyze the rationality of the CAV lane planning scheme is a great difficulty to be solved. Therefore, the invention provides a reasonable planning and analyzing method for the special lane of the network-connected automatic driving vehicle for the HV and CAV mixed running scene.
In the prior art, levin et al (Levin, M.W., & Boyles, S.D. (2016). A multiclass cell transmission model for shared human and autonomous vehicle roads.transport Research Part C: emerging Technologies,62, 103-116.), liu et al (Liu, Z., & Song, Z. (2019), strategic planning of dedicated autonomous vehicle lanes and autonomous vehicle/toll lanes in transportation networks. Transport Research Part C: emerging Technologies,106, 381-403.) all assume that the distribution of different types of vehicles on the lane is completely random, i.e., that the distribution of both types of vehicles on the lane is a Bernoulli process, regardless of CAV vehicle organization. However, in a practical scenario, CAV has a tendency of formation driving, that is, by means of an advanced network-linked automatic driving technology, coordination control between vehicles is realized, and formation driving is performed on a road through operations such as autonomous lane changing, speed increasing (speed decreasing) and the like, so that two types of vehicles are not completely and randomly distributed on the road, which results in serious errors in calculation of traffic capacity of a mixed road in the technology.
The study of Ghiasi et al (Ghiasi, a., hussain, o., qian, z.s., & Li, x. (2017). A mixed traffic capacity analysis and lane management model for connected automated vehicles: a Markov chain method.transmission Research Part B: method logic, 106, 266-292.) although taking into account the tendency of CAV to travel on the road, and defining and introducing an index of formation strength for qualitatively describing the aggregation of CAV on the road, the index does not have a specific mathematical expression, only gives the maximum value and the minimum value of the index of queuing strength for all CAVs in the vehicle team or for all CAVs not in the vehicle team, respectively, and cannot accurately quantitatively describe the formation of CAV on the vehicle road.
At present, part of researches mainly study the influence of a special road of an online automatic driving vehicle on the travel efficiency of a road network and optimize the layout scheme of the special road. And respectively establishing traffic distribution models in the common lane mode and the special lane mode, giving out a solving algorithm of the models, researching the mixed balanced flow state in different lane configuration modes, and determining an optimal lane configuration scheme. For example Zhou Zhaoming et al (Zhou Zhaoming, huang Zhongxiang, yuan Jianbo, & Li Pan (2021) based on different lane mode traffic flow optimization of unmanned vehicles, university of long-distance security university report (natural science edition)), assuming that unmanned vehicles, advanced traveler travel system (advanced traveler information systems, ATIS) device vehicles and ordinary driving vehicles respectively follow system optimal mode, user balanced mode, random user balanced mode selection paths, respectively establishing traffic distribution models in ordinary lane and special lane modes, respectively, adopting a continuous average method (method of successive averages, MSA) to solve the models, analyzing and determining the traffic capacities of ordinary lanes and unmanned special lanes at different speeds, and analyzing the influence of model parameters such as information quality level, travel demand, market penetration rate and the like on average travel time by calculation examples; and researching the mixed balanced flow state under different lane configuration modes on the basis of determining the values of various parameters.
The technology does not consider that the traffic capacity of the mixed road is not a constant value according to different headway corresponding to different following modes in the mixed running environment, but is a random variable depending on the duty ratio of two types of vehicles and the spatial distribution of the two types of vehicles on the road. The model provided by the technology optimizes the planning layout of the CAV special road from the road network level, and a planning scheme can be obtained by establishing a complex mathematical planning model and solving the complex mathematical planning model, so that the method is too complex, the calculation difficulty is high, and the method is difficult to be used in the actual traffic planning process.
In addition, the road section traffic capacity is mainly improved, a layout scheme for optimizing the special road is provided, the road section traffic capacity is maximized by constructing a lane management model, and a special road layout strategy is researched. In addition, the influence of special road layout on the traffic capacity of road segments is studied by a simulation technology. For example, chen et al (Chen, d., ahn, s., chirturi, m., & Noyce, d.a. (2017) & Towards vehicle automation: roadway capacity formulation for traffic mixed with regular and automated vehicles transmission research part B: method logic, 100,196-221.) studied the impact of different lane management schemes on road segment traffic flow based on its developed hybrid road traffic capacity calculation model, such as network-connected vehicle lane and artificial vehicle lane coexistence schemes, network-connected vehicle lane and hybrid lane coexistence schemes, artificial vehicle lane and hybrid lane coexistence schemes, and developed a set of generic models to determine the effective domains of different lane management schemes.
Firstly, assuming that all CAVs appear in the form of a train, and the CAV trains exist periodically, so that traffic flow is periodic, and each period consists of one n-CAV train and one m-HV to obtain a road traffic capacity formula consisting of HV and CAV trains; and then respectively researching the traffic capacity of the double-lane highway under different lane models. A general formula is further formulated, including all lane policies considered, to determine how CAV should be allocated on a lane given traffic demand, CAV permeability, and CAV efficiency gains. Finally, the formula is extended to a general multi-lane highway.
In this technique, it is assumed that CAV fleets exist periodically, each period is composed of one n-CAV fleet and one m-HV, and the HV and CAV fleets are obtained, so that a road traffic capacity formula of mixed traffic flow is obtained, which is not consistent with randomness of HV and CAV distributed on lanes in actual situations, and formation tendency of CAV vehicles running on roads is not considered.
Disclosure of Invention
Aiming at HV and CAV mixed driving scenes, the minimum safe distance between mixed driving vehicles is considered to be related to the types of vehicles in front of and behind as well as the vehicle formation scenes, indexes are introduced to quantitatively describe the formation condition of CAV in the road driving process, a calculation formula with more universal traffic capacity of the mixed driving road section is provided, and on the basis, a method for rapidly judging whether the CAV special road planning scheme is reasonable or not is provided for traffic planners according to given road sections and CAV special road planning schemes.
The specific technical scheme is as follows:
a rationality analysis method for a network-linked automatic driving vehicle lane planning scheme comprises the following steps:
step 1, dividing different following modes by considering the types of front and rear vehicles and CAV vehicle formation characteristics, and according to different headway in the corresponding mixed traffic flow under the different following modes;
let the maximum fleet size be s vehicles. That is, when the fleet size exceeds s, a new fleet will be formed by the subsequent CAVs. According to different following modes, five different types of headway exist in the mixed traffic flow, and the different headway corresponds to the vehicle running form on the road:
(1)h 11 a headway representing that HV follows another HV travel;
(2)h 21 representing the headway of CAV following HV driving;
(3)h 12 representing the headway of HV following CAV;
(4)h 22 representing the headway in the same CAV queue;
(5)h 22′ representing the headway of CAV following the maximum CAV formation;
step 2, establishing a macroscopic probability model to calculate the average headway of the vehicle and the corresponding road traffic capacity under the mixed running condition;
the ratio of each headway occurrence in the step 2.1 mixed flow is as follows:
p 11 +p 12 ＝p H (1)
p 21 +p 22′ +p 22 ＝1-p H ＝p C (2)
Figure BDA0004125077990000041
Figure BDA0004125077990000042
Figure BDA0004125077990000043
wherein ,pH 、p C Represents the permeabilities of HV and CAV, respectively;
Figure BDA0004125077990000044
representing the formation proportion of CAVs, i.e. the proportion of the number of CAVs forming a formation with a preceding vehicle to all CAVs present on the road; p is p 11 、p 12 Respectively representing the probability that HV follows another HV to travel and the probability that HV follows CAV to travel; p is p 22 、p 22′ 、p 21 The probability that CAV follows another CAV in the CAV queue is respectively; probability of CAV following CAV tail travel; the probability that CAV follows HV travel.
Step 2.2, calculating an average headway and corresponding road traffic capacity;
the minimum safe headway which HV can keep as a rear vehicle is equal, namely h 12 ＝h 11 ；
The average headway calculation formula of the lane is:
Figure BDA0004125077990000045
the average traffic capacity under the mixed traffic flow environment is obtained as follows:
Figure BDA0004125077990000046
/>
step 3, deducing a road section impedance function suitable for the mixed traffic flow based on the research on the road traffic capacity in the mixed traffic scene;
on the urban road with speed limit, the free running time t of each lane 0 And the same traffic lane number is m, and N vehicles are used. According to (8), (10 (11) calculating the impedance of the road section of the road mixed with no special road, the CAV special road after the special road is set and the road section of the road mixed after the special road is set respectively. The specific calculation formula is as follows:
no special lane is set:
when no CAV special lane is set, the lanes are mixed lanes allowing HV and CAV to pass, and the travel time of the vehicle is obtained by a function of the United states federal road agency (BPR):
Figure BDA0004125077990000047
wherein t represents the passing time of the section of the non-set special road; t is t 0 Representing the free flow time of CAV and HV over a road segment; c 0 Indicating traffic capacity of the lane at pure HV;
Figure BDA0004125077990000048
a conversion factor representing CAV-HV; n (p) C ρ+p H ) Traffic flow representing the transition of the mixed traffic stream to a standard HV; alpha, beta represent two parameters in the BPR function.
Meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
Figure BDA0004125077990000051
after the special channel is set:
after the CAV special lane is arranged, the CAV can run on the special lane and the common lane, but the HV can only run on the mixed lane. If the proportion of CAV to all CAV is lambda, the following passing time of the vehicle after the special road is set can be obtained:
(1) CAV lane transit time calculation
Figure BDA0004125077990000052
Wherein n represents the number of CAV dedicated tracks; t' represents the transit time of the CAV lane;
Figure BDA0004125077990000053
conversion coefficients of CAV-HV representing the private track; p's' C The permeability of CAV on the specific track is represented as 1; />
Figure BDA0004125077990000054
The queue proportion of CAV on CAV dedicated tracks is represented as 1.
(2) Mixed traffic lane transit time calculation
Figure BDA0004125077990000055
Wherein t' represents the traffic time of the mixed traffic lane after the CAV special lane is set;
Figure BDA0004125077990000056
a conversion coefficient of CAV-HV representing a mixed traffic lane after setting a special lane; p' C "means CAV permeability of a mixed traffic lane after setting a special lane; />
Figure BDA0004125077990000057
And the formation proportion of CAV of the mixed traffic lane after the special lane is set is represented.
Meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
T C ＝Np C λt′+N(1-p C λ)t″ (12)
step 4, assuming that after the special lane is set, the lane selection of the CAV travelers follows the user balance condition to obtain the CAV traveler proportion of the selected special lane;
user Equipment (UE) condition:
in order to obtain the CAV proportion of the entering special lanes, the CAV traveler lane selection is made to follow the UE balancing principle, namely when the balance is achieved, the utilized lanes for the CAV traveler have equal and minimum traveling cost, and meanwhile, the CAV is necessarily present on the special lanes in combination with the actual situation, so that one of the following two conditions is met:
case one: when equation (13) is satisfied, the transit time for the CAV traveler lane is less than that of the mixed lane, at which time all CAV travelers choose to travel on the lane (where λ=1), i.e., t' < t ".
(m-n)p C h 22 -n(1-p C )h 11 ＜0 (13)
And a second case: if the first situation is not satisfied, it is stated that the traffic time for the CAV traveler lane is equal to the traffic time of the hybrid lane, i.e., t "=t', at which:
Figure BDA0004125077990000061
step 5, obtaining rationality judgment conditions of the special road planning scheme by comparing the total travel cost of the CAV special road section; in the HV and CAV mixed driving environment, the rationality judgment conditions of the lane planning scheme are as follows:
T＞T C (14)
according to the situation that the traffic time of the CAV traveler private road and the traffic time of the mixed road section exist after the CAV private road is set in the step 4, the condition for judging the rationality of the CAV private road planning scheme is obtained respectively
Case one: for CAV travelers, the traffic time of the selected special lane is smaller than that of the common mixed lane, and in this case, when the CAV permeability and the lane planning scheme (including the CAV lane number and the mixed lane number) satisfy the formula (15), the planning scheme of the special lane is reasonable.
Figure BDA0004125077990000062
wherein ,
Figure BDA0004125077990000063
and a second case: if the parameters do not meet the first condition, the special lane traffic time is equal to the traffic time of the common mixed lane for the CAV traveler, and in this case, when the CAV permeability and the lane planning scheme (comprising the number of CAV lanes and the number of mixed lanes) meet the formula (16), the special lane planning scheme is reasonable.
n(p C ρ+1-p C )-mp C λρ′＞0 (16)
wherein ,
Figure BDA0004125077990000064
or, step 5 considers that the minimum safe distance which can be kept between the mixed vehicles is related to the type of the vehicles in front of and behind and the vehicle formation scene, the given judging conditions are applicable to the more common traffic scene, and the judging conditions given in step 5 are simplified, so that the method is more applicable to the traffic planning scene.
Let CAV formation be ignored, let CAV and the headway between CAVs be h 22 The time intervals among other headings are equal, namely h 11 ＝h 12 ＝h 21 Conversion coefficient of CAV-HV at this time:
Figure BDA0004125077990000071
according to the above, the rationality judgment conditions of the simplified special lane planning scheme are as follows:
case one: for CAV travelers, the traffic time of the selected special lane is smaller than that of the common mixed lane, in which case, when the CAV permeability and the lane planning scheme (including the CAV lane number and the mixed lane number) satisfy the formula (18), the planning scheme of the special lane is reasonable.
Figure BDA0004125077990000072
And a second case: if the parameters do not meet the first condition, the special lane traffic time is equal to the traffic time of the common mixed lane for the CAV traveler, and in this case, when the CAV permeability and the lane planning scheme (comprising the number of CAV lanes and the number of mixed lanes) meet the formula (19), the special lane planning scheme is reasonable.
Figure BDA0004125077990000073
wherein ,
Figure BDA0004125077990000074
the invention has the specific technical effects that:
(1) The invention provides a more universal calculation formula for the average traffic capacity of the lane in the HV and CAV mixed running environment. Considering that the minimum safe distance kept between the mixed vehicles is related to the following and following vehicle types and vehicle formation scenes, defining five types of different headway according to different following modes, and quantitatively describing the distribution situation of different vehicle following modes on a mixed road by adopting two indexes of the ratio of different types of vehicles to the ratio of the vehicles participating in formation in the networked automatic driving vehicle (the formation ratio for short), and establishing a macroscopic probability model to calculate the average headway and the corresponding average traffic capacity of a lane under the mixed condition.
(2) The invention provides a condition for judging the rationality of a special road planning scheme aiming at a road section without a CAV special road under a mixed running scene. Deriving a road section impedance function applicable to different types of lanes based on the research on the traffic capacity of the road; under the condition that the CAV permeability and the lane planning scheme (the specific number of common lanes and CAV special lanes) are known, the condition for judging the rationality of the special lane planning scheme for the section of the non-set special lane is provided by comparing the total travel cost before and after the set CAV special lane.
Drawings
FIG. 1 is a schematic view of the headway in different heel modes of the present invention.
Detailed Description
The specific technical scheme of the invention is described with reference to the accompanying drawings.
A rationality analysis method for a network-linked automatic driving vehicle lane planning scheme comprises the following steps:
step 1, dividing different following modes by considering the types of the front and rear vehicles and CAV vehicle formation characteristics, and according to different headway in the corresponding mixed traffic flow under the different following modes:
considering that CAV has tendency of formation driving on a road, CAV of formation driving is communicated with a head car in real time and is influenced by the limitation of an information transmission range, and the longer the vehicle team is, the more unstable the information is transmitted, so that CAV vehicle teams on the same lane have maximum scale limitation, and the maximum vehicle team scale is s vehicles. That is, when the fleet size exceeds s, a new fleet will be formed by the subsequent CAVs. According to different following modes, five different types of headway exist in the mixed traffic flow, and the different headway corresponds to the running form of the vehicle on the road as shown in fig. 1.
(1)h 11 A headway representing that HV follows another HV travel;
(2)h 21 representing the headway of CAV following HV driving;
(3)h 12 representing the headway of HV following CAV;
(4)h 22 representing the headway in the same CAV queue;
(5)h 22′ the headway for CAV to follow the maximum CAV formation travel is indicated (the example given in the figure assumes that the maximum formation length is 4 vehicles).
Step 2, establishing a macroscopic probability model to calculate the average headway of the vehicle and the corresponding road traffic capacity under the mixed running condition;
the ratio of each headway occurrence in the step 2.1 mixed flow is as follows:
p 11 +p 12 ＝p H (1)
p 21 +p 22′ +p 22 ＝1-p H ＝p C (2)
Figure BDA0004125077990000081
Figure BDA0004125077990000082
Figure BDA0004125077990000083
wherein ,pH 、p C Represents the permeabilities of HV and CAV, respectively;
Figure BDA0004125077990000084
representing the formation proportion of CAVs, i.e. the proportion of the number of CAVs forming a formation with a preceding vehicle to all CAVs present on the road; p is p 11 、p 12 Respectively representing the probability that HV follows another HV to travel and the probability that HV follows CAV to travel; p is p 22 、p 22′ 、p 21 The probability that CAV follows another CAV in the CAV queue is respectively; probability of CAV following CAV tail travel; the probability that CAV follows HV travel.
Step 2.2, calculating an average headway and corresponding road traffic capacity;
assuming that HV is equal as the minimum safe headway that the rear vehicle can hold, i.e. h 12 ＝h 11 。
The average headway calculation formula of the lane is:
Figure BDA0004125077990000091
thus, the average traffic capacity in the mixed traffic flow environment is obtained as:
Figure BDA0004125077990000092
step 3, deducing a road section impedance function suitable for the mixed traffic flow based on the research on the road traffic capacity in the mixed traffic scene;
the CAV is added to make the calculation of the travel cost of the road section more complex, and the invention provides a novel mixed traffic flow environmentAnd setting a calculation formula of travel time of the special lane front-rear mixed lane and the CAV special lane. Suppose that on an urban road with speed limitation, the free running time t of each lane 0 And the same traffic lane number is m, and N vehicles are used. The impedance of the road section where no special road is set, the CAV special road after the special road is set, and the road section where the special road is set can be calculated according to the formulas (8), (10) and (11). The specific calculation formula is as follows:
no special lane is set:
when no CAV special lane is set, the lanes are mixed lanes allowing HV and CAV to pass, and the travel time of the vehicle is obtained by a function of the United states federal road agency (BPR):
Figure BDA0004125077990000093
wherein t represents the passing time of the section of the non-set special road; t is t 0 Representing the free flow time of CAV and HV over a road segment; c 0 Indicating traffic capacity of the lane at pure HV;
Figure BDA0004125077990000094
a conversion factor representing CAV-HV; n (p) C ρ+p H ) Traffic flow representing the transition of the mixed traffic stream to a standard HV; alpha, beta represent two parameters in the BPR function.
Meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
Figure BDA0004125077990000095
after the special channel is set:
after the CAV special lane is arranged, the CAV can run on the special lane and the common lane, but the HV can only run on the mixed lane. If the proportion of CAV to all CAV is lambda, the following passing time of the vehicle after the special road is set can be obtained:
(1) CAV lane transit time calculation
Figure BDA0004125077990000096
Wherein n represents the number of CAV dedicated tracks; t' represents the transit time of the CAV lane;
Figure BDA0004125077990000101
conversion coefficients of CAV-HV representing the private track; p's' C The permeability of CAV on the specific track is represented as 1; />
Figure BDA0004125077990000102
The queue proportion of CAV on CAV dedicated tracks is represented as 1.
(2) Mixed traffic lane transit time calculation
Figure BDA0004125077990000103
Wherein t' represents the traffic time of the mixed traffic lane after the CAV special lane is set;
Figure BDA0004125077990000104
a conversion coefficient of CAV-HV representing a mixed traffic lane after setting a special lane; p' C "means CAV permeability of a mixed traffic lane after setting a special lane; />
Figure BDA0004125077990000105
And the formation proportion of CAV of the mixed traffic lane after the special lane is set is represented.
Meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
T C ＝Np C λt′+N(1-p C λ)t″ (12)
step 4, assuming that after the special lane is set, the lane selection of the CAV travelers follows the user balance condition to obtain the CAV traveler proportion of the selected special lane;
user Equipment (UE) condition:
in order to get the CAV proportion into the private road, it is assumed that CAV traveler lane selection follows the UE balancing principle, i.e. when balancing is achieved, the lanes utilized for CAV travelers have equal and minimum travel costs, while in combination with the fact that CAV must be present on the private road, one of the following two cases should be satisfied:
case one: when equation (13) is satisfied, the transit time for the CAV traveler lane is less than that of the mixed lane, at which time all CAV travelers choose to travel on the lane (where λ=1), i.e., t' < t ".
(m-n)p C h 22 -n(1-p C )h 11 ＜0 (13)
And a second case: if the first condition is not satisfied, it is indicated that the traffic time for the CAV traveler's lane is equal to the traffic time of the mixed lane, i.e., t "=t', at this time
Figure BDA0004125077990000106
Step 5, obtaining rationality judgment conditions of the special road planning scheme by comparing the total travel cost of the CAV special road section; in the HV and CAV mixed driving environment, the rationality judgment conditions of the lane planning scheme are as follows:
T＞T C (14)
according to the situation that the traffic time of the CAV traveler private road and the traffic time of the mixed road section exist after the CAV private road is set in the step 4, the condition for judging the rationality of the CAV private road planning scheme is obtained respectively
Case one: for CAV travelers, the traffic time of the selected special lane is smaller than that of the common mixed lane, and in this case, when the CAV permeability and the lane planning scheme (including the CAV lane number and the mixed lane number) satisfy the formula (15), the planning scheme of the special lane is reasonable.
Figure BDA0004125077990000111
wherein ,
Figure BDA0004125077990000112
and a second case: if the parameters do not meet the first condition, the special lane traffic time is equal to the traffic time of the common mixed lane for the CAV traveler, and in this case, when the CAV permeability and the lane planning scheme (comprising the number of CAV lanes and the number of mixed lanes) meet the formula (16), the special lane planning scheme is reasonable.
n(p C ρ+1-p C )-mp C λρ′＞0 (16)
wherein ,
Figure BDA0004125077990000113
and 5, considering that the minimum safe distance which can be kept between the mixed vehicles is related to the type of the vehicles in front of and behind and the vehicle formation scene, the given judging conditions are suitable for the more common traffic scene, and the judging conditions given in the step 5 are simplified, so that the method is more suitable for the traffic planning scene.
Let CAV formation be ignored, let CAV and the headway between CAVs be h 22 The time intervals among other headings are equal, namely h 11 ＝h 12 ＝h 21 Conversion coefficient of CAV-HV at this time:
Figure BDA0004125077990000114
/>
according to the above, the rationality judgment conditions of the simplified special lane planning scheme are as follows:
case one: for CAV travelers, the traffic time of the selected special lane is smaller than that of the common mixed lane, in which case, when the CAV permeability and the lane planning scheme (including the CAV lane number and the mixed lane number) satisfy the formula (18), the planning scheme of the special lane is reasonable.
Figure BDA0004125077990000115
And a second case: if the parameters do not meet the first condition, the special lane traffic time is equal to the traffic time of the common mixed lane for the CAV traveler, and in this case, when the CAV permeability and the lane planning scheme (comprising the number of CAV lanes and the number of mixed lanes) meet the formula (19), the special lane planning scheme is reasonable.
Figure BDA0004125077990000121
wherein ,
Figure BDA0004125077990000122
/>

Claims (7)

1. the rationality analysis method for the network-connected automatic driving vehicle lane planning scheme is characterized by comprising the following steps of:
step 1, dividing different following modes by considering the types of front and rear vehicles and CAV vehicle formation characteristics, and according to different headway in the corresponding mixed traffic flow under the different following modes;
step 2, establishing a macroscopic probability model to calculate the average headway of the vehicle and the corresponding road traffic capacity under the mixed running condition;
step 3, deducing a road section impedance function suitable for the mixed traffic flow based on the research on the road traffic capacity in the mixed traffic scene;
step 4, assuming that after the special lane is set, the lane selection of the CAV travelers follows the user balance condition to obtain the CAV traveler proportion of the selected special lane;
and step 5, obtaining the rationality judgment condition of the special road planning scheme by comparing the total travel cost before and after the CAV special road section is set.
2. The method for rationality analysis of a lane planning scheme for networked automatic driving vehicles according to claim 1, wherein in step 1, the maximum fleet size is set to s vehicles; that is, when the fleet size exceeds s, the subsequent CAV will form a new fleet; according to different following modes, five different types of headway exist in the mixed traffic flow, and the different headway corresponds to the vehicle running form on the road:
(1)h 11 a headway representing that HV follows another HV travel;
(2)h 21 representing the headway of CAV following HV driving;
(3)h 12 representing the headway of HV following CAV;
(4)h 22 representing the headway in the same CAV queue;
(5)h 22′ representing the headway of CAV following the maximum CAV formation travel.
3. The method for rationality analysis of a networked automatic driving vehicle lane planning scheme according to claim 2, wherein the step 2 specifically comprises the following sub-steps:
the ratio of each headway occurrence in the step 2.1 mixed flow is as follows:
p 11 +p 12 ＝p H (1)
p 21 +p 22′ +p 22 ＝1-p H ＝p C (2)
Figure FDA0004125077980000011
Figure FDA0004125077980000012
Figure FDA0004125077980000013
wherein ,pH 、p C Represents the permeabilities of HV and CAV, respectively;
Figure FDA0004125077980000014
representing the formation proportion of CAVs, i.e. the proportion of the number of CAVs forming a formation with a preceding vehicle to all CAVs present on the road; p is p 11 、p 12 Respectively representing the probability that HV follows another HV to travel and the probability that HV follows CAV to travel; p is p 22 、p 22′ 、p 21 The probability that CAV follows another CAV in the CAV queue is respectively; probability of CAV following CAV tail travel; probability of CAV following HV travel;
step 2.2, calculating an average headway and corresponding road traffic capacity;
the minimum safe headway which HV can keep as a rear vehicle is equal, namely h 12 ＝h 11 ；
The average headway calculation formula of the lane is:
Figure FDA0004125077980000021
the average traffic capacity under the mixed traffic flow environment is obtained as follows:
Figure FDA0004125077980000022
4. the method for rationality analysis of a lane planning scheme for an online automatic driving vehicle according to claim 3, wherein in step 3, specifically:
on the urban road with speed limit, the free running time t of each lane 0 The same, there are m lanes, N vehicles; calculating the impedance of the road section without the special road and the road section with the special road and the CAV special road after the special road according to (8), (10) and (11); the specific calculation formula is as follows:
no special lane is set:
when no CAV special road is set, the lanes are mixed lanes allowing HV and CAV to pass, and the travel time of the vehicle is obtained by a BPR function of the federal road agency:
Figure FDA0004125077980000023
wherein t represents the passing time of the section of the non-set special road; t is t 0 Representing the free flow time of CAV and HV over a road segment; c 0 Indicating traffic capacity of the lane at pure HV;
Figure FDA0004125077980000024
a conversion factor representing CAV-HV; n (p) C ρ+p H ) Traffic flow representing the transition of the mixed traffic stream to a standard HV; alpha and beta represent two parameters in the BPR function;
meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
Figure FDA0004125077980000025
after the special channel is set:
after the CAV special lane is arranged, the CAV can run on the special lane and the common lane, but the HV can only run on the mixed lane; if the proportion of CAV to all CAV is lambda, the passing time of the vehicle after the special road is set is as follows:
(1) CAV lane transit time calculation
Figure FDA0004125077980000031
Wherein n represents the number of CAV dedicated tracks; t' represents the transit time of the CAV lane;
Figure FDA0004125077980000032
conversion coefficients of CAV-HV representing the private track; p's' C The permeability of CAV on the specific track is represented as 1; />
Figure FDA0004125077980000033
The formation proportion of CAV on the CAV special track is represented, and the value is 1;
(2) Mixed traffic lane transit time calculation
Figure FDA0004125077980000034
/>
Wherein t' represents the traffic time of the mixed traffic lane after the CAV special lane is set;
Figure FDA0004125077980000035
a conversion coefficient of CAV-HV representing a mixed traffic lane after setting a special lane; p' C The CAV permeability of the mixed traffic lane after the special lane is arranged is represented; />
Figure FDA0004125077980000036
The CAV formation proportion of the mixed traffic lane after the special lane is set is represented;
meanwhile, the total passing time of the vehicle without the CAV special road is obtained as follows:
T C ＝Np C λt′+N(1-p C λ)t″ (12)。
5. the method for rationality analysis of a network-linked automatic driving vehicle lane planning scheme according to claim 4, wherein the user balancing condition in step 4 is:
in order to obtain the CAV proportion of the entering special lanes, the CAV traveler lane selection is made to follow the UE balancing principle, namely when the balance is achieved, the utilized lanes for the CAV traveler have equal and minimum traveling cost, and meanwhile, the CAV is necessarily present on the special lanes in combination with the actual situation, so that one of the following two conditions is met:
case one: when the formula (13) is satisfied, the transit time of the special lane for the CAV travelers is smaller than that of the mixed lane, and all CAV travelers can choose to travel on the special lane at the moment, wherein lambda=1, namely t '< t';
(m-n)p C h 22 -n(1-p C )h 11 ＜0 (13)
and a second case: if the first situation is not satisfied, it is stated that the traffic time for the CAV traveler lane is equal to the traffic time of the hybrid lane, i.e., t "=t', at which:
Figure FDA0004125077980000037
6. the method for rationality analysis of a lane planning scheme for an online automatic driving vehicle according to claim 5, wherein the specific judgment conditions in step 5 are as follows:
in the HV and CAV mixed driving environment, the rationality judgment conditions of the lane planning scheme are as follows:
T＞T C (14)
after the CAV special road is set in the step 4, the conditions for judging the rationality of the CAV special road planning scheme are respectively obtained for two situations of the CAV traveler special road and the traffic time of the mixed road section:
case one: for CAV travelers, the passing time of the selected special lane is smaller than that of a common mixed lane, and in the situation, when the CAV permeability and the lane planning scheme meet the formula (15), the planning scheme of the special lane is reasonable;
Figure FDA0004125077980000041
wherein ,
Figure FDA0004125077980000042
and a second case: if the parameters do not meet the first condition, the special lane is selected to pass through the time equal to the passing time of the common mixed lane for CAV travelers, and in the case, when the CAV permeability and the lane planning scheme meet the formula (16), the special lane planning scheme is reasonable;
n(p C ρ+1-p C )-mp C λρ′＞0 (16)
wherein ,
Figure FDA0004125077980000043
7. the method for rationality analysis of a networked automatic driving vehicle lane planning scheme according to claim 5, wherein,
the simplified judgment conditions in step 5 are:
regardless of CAV formation, the headway between CAV and CAV is h 22 Other time intervals of the head are equal, namely h 11 ＝h 12 ＝h 21 Conversion coefficient of CAV-HV at this time:
Figure FDA0004125077980000044
the rationality judgment conditions of the simplified special lane planning scheme are as follows:
case one: for CAV travelers, the passing time of the selected special lane is smaller than that of a common mixed lane, and in the situation, when the CAV permeability and the lane planning scheme meet the formula (18), the planning scheme of the special lane is reasonable;
Figure FDA0004125077980000045
and a second case: if the parameters do not meet the first condition, the special lane is selected to pass through the time equal to the passing time of the common mixed lane for CAV travelers, and in the case, when the CAV permeability and the lane planning scheme meet the formula (19), the special lane planning scheme is reasonable;
Figure FDA0004125077980000051
wherein ,
Figure FDA0004125077980000052
/>
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118038702A (en) * 2024-03-11 2024-05-14 北京工业大学 Method and system for calculating and analyzing upper and lower limits of traffic capacity of lanes in mixed traffic scene

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