Space-time resource configuration method and system for multi-lane single intersection in mixed traffic environment

Abstract

The present application relates to the technical field of intelligent traffic control, in particular to a kind of mixed environment under multi-lane single intersection space resource configuration method and system, storage medium, electronic equipment.The method comprises: determining the traffic flow of each flow direction of the intersection to be analyzed, the traffic flow of each flow direction of artificial vehicle, and the maximum and minimum permitted period length, the maximum and minimum permitted phase green time and green interval time of the intersection;Determine the saturation flow rate of the dedicated lane for the net-connected automatic vehicle and the dedicated lane for the artificial vehicle, and the conversion coefficient of the left, straight and right net-connected automatic vehicle flow and artificial vehicle flow;Determine the channelization scheme of the multi-lane intersection corresponding to the intersection to be analyzed under the mixed environment in combination with the layout of the connected road section of the intersection to be analyzed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent traffic control, and particularly relates to a multi-lane single intersection space-time resource allocation method under a mixed traffic environment, a multi-lane single intersection space-time resource allocation system under a mixed traffic environment, a storage medium, and an electronic device. BACKGROUND

[0002] An autonomous vehicle with real-time communication with the outside world is called a networked autonomous vehicle. The networked autonomous vehicle has more timely and accurate information acquisition capability, faster reaction capability and more accurate operation capability, which can improve road traffic safety and reduce the minimum following time to improve road traffic capacity. Therefore, the networked autonomous vehicle is considered to effectively alleviate urban traffic congestion and improve travel safety and efficiency in the future. After years of unremitting efforts by governments, enterprises and research institutions, the Internet of Vehicles and autonomous driving technology have developed rapidly, and the networked autonomous vehicle has entered the stage of field operation. For example, in late 2018, Google released the world's first networked autonomous taxi in the suburbs of Phoenix, USA, for the first commercial application. Baidu has deployed its networked autonomous taxi operation service in Changsha, Cangzhou and Beijing, serving more than 210,000 people.

[0003] When the networked autonomous vehicle is widely used, the road network traffic flow will change from a traditional single artificial vehicle flow to a mixed flow composed of artificial vehicles and networked autonomous vehicles. In order to ensure safe operation or improve road network travel efficiency, the manager may redistribute road resources, set some lanes on the road section as exclusive lanes for networked autonomous vehicle operation, called networked autonomous vehicle exclusive lanes, and set some lanes as artificial vehicle exclusive lanes. Related studies show that the redistribution of lanes into networked autonomous vehicle exclusive lanes and artificial vehicle exclusive lanes can significantly improve the efficiency of road section traffic flow, improve road traffic capacity, and reduce delay. However, for the redistribution of road resources under the mixed traffic environment of networked autonomous vehicles and artificial vehicles, current research is limited to the redistribution of lane resources on the road section, and the operation of road network traffic flow is also affected by the space-time resource allocation of intersections. When the lanes on the road section are set as networked autonomous vehicle exclusive lanes and artificial vehicle exclusive lanes, there is an urgent need for a method to optimize the space-time resource allocation of intersections, especially for intersections with a large number of import lanes, to optimize the import lane channeling scheme, avoid interweaving, improve the safety of traffic flow at the import of intersections under the mixed traffic environment, and optimize the signal timing scheme of intersections under the current lane channeling scheme, avoid internal traffic conflicts at intersections, and improve the efficiency of intersections.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The present disclosure provides a method and system for configuring space-time resources of a multi-lane single intersection in a mixed traffic environment, a storage medium, and an electronic device, which can optimize the channelization design and signal timing scheme of a multi-lane intersection in a mixed traffic environment and improve the travel efficiency at the intersection.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or will be learned by practice of the present disclosure.

[0007] According to a first aspect of the present disclosure, a method for configuring space-time resources of a multi-lane single intersection in a mixed traffic environment is provided, the method comprising:

[0008] determining the flow of net-connected automatic vehicle flow and the flow of manual vehicle flow in each direction of the intersection to be analyzed, and the maximum and minimum allowable cycle time, the maximum and minimum allowable phase green time, and the green interval time of the intersection;

[0009] determining the saturation flow rate of the net-connected automatic vehicle lane and the manual vehicle lane, and the conversion coefficient of the left, straight, and right net-connected automatic vehicle flow and the manual vehicle flow;

[0010] determining the channelization scheme of the multi-lane intersection in the mixed traffic environment corresponding to the intersection to be analyzed in combination with the layout of the road segments connected to the intersection to be analyzed.

[0011] In an exemplary embodiment, the method further comprises: constructing a conflict set according to the relative positions of the net-connected automatic vehicle lane and the manual vehicle lane and the running trajectories of each vehicle flow;

[0012] constructing a mixed integer linear programming model based on the channelization scheme of the intersection, to optimize the signal timing scheme of the intersection to be analyzed with the maximum traffic capacity and / or the minimum delay as the target.

[0013] In an exemplary embodiment, the method further comprises: constructing a conflict set according to the relative positions of the net-connected automatic vehicle lane and the manual vehicle lane and the running trajectories of each vehicle flow;

[0014] setting the left or right side of a certain entrance road segment connected to the intersection as a net-connected automatic vehicle lane, and setting the other lanes for manual vehicle operation;

[0015] setting a pre-signal light and a pre-signal stop line on the net-connected automatic vehicle lane, and setting a series control area between the pre-signal stop line and the intersection stop line;

[0016] configuring the net-connected automatic vehicle lane on the upstream side of the pre-signal stop line close to the manual lane as a parking queue area, and configuring the other lane as a passing area;

[0017] The three lanes of left, straight and right connected automatic vehicle flows on the 7 continuous connected automatic vehicle lanes are controlled in series by using a pre-signal.

[0018] The channelization scheme of the artificial vehicle lane of the intersection to be analyzed is configured according to the consistency principle of the left, straight and right turning vehicle flow ratio and the guide lane number ratio.

[0019] In an exemplary embodiment, the length of the series control zone is set according to the capacity to accommodate the parking and queuing of any one of the turning vehicle flows in a cycle, the length of the parking and queuing zone is set according to the capacity to accommodate the parking and queuing of any two of the turning vehicle flows in a cycle, and the sum of the length of the series control zone and the length of the parking and queuing zone should be less than the length of the road section.

[0020] In an exemplary embodiment, the conflict set includes intersection conflicts, merging conflicts and series conflicts.

[0021] In an exemplary embodiment, the conflict set is constructed according to the relative positions of the connected automatic vehicle lane and the artificial vehicle lane and the running trajectories of the vehicle flows, including:

[0022] According to the layout position of the connected automatic vehicle lane and the running trajectories of the vehicle flows, it is determined whether the running trajectories of two different turning vehicle flows intersect within the intersection, and the conflicting vehicle flows that will have intersection conflicts are added to the conflict set;

[0023] According to the layout position of the connected automatic vehicle lane and the running trajectories of the vehicle flows, it is determined whether the running trajectories of two different turning vehicle flows will have merging conflicts at the exit lane, and the conflicting vehicle flows that will have merging conflicts are added to the conflict set;

[0024] The three lanes of connected automatic vehicle flows in the direction of the connected automatic vehicle lane in the entrance direction are paired two by two, and added to the conflict set as series conflict vehicle flows.

[0025] In an exemplary embodiment, a mixed integer linear programming model is constructed based on the intersection channelization scheme, with the maximum traffic capacity and the minimum delay of the intersection to be analyzed as the target, and the signal timing scheme of the intersection to be analyzed is optimized, including:

[0026] According to the first constraint condition, the conflicting traffic flows are separated in the time dimension;

[0027] According to the second constraint condition, it is ensured that the green light phase of the allocated artificial vehicle flow meets the phase structure requirement;

[0028] According to the third constraint condition, it is ensured that the artificial vehicle flows in the same lane group have the same green light phase;

[0029] According to the fourth constraint condition, it is ensured that the phase saturation degree of the mixed traffic intersection where the V2X lane is arranged meets the maximum saturation degree.

[0030] According to the fifth constraint condition, it is ensured that the optimized timing parameters are within the permitted range.

[0031] Based on the constraint conditions, a mixed integer linear programming model is constructed. According to a second aspect of the present disclosure, a system for configuring time-space resources of a multi-lane single intersection in a mixed traffic environment is provided, and the system comprises:

[0032] A first parameter acquisition module is configured to determine the V2X vehicle flow of each flow direction of a to-be-analyzed intersection, the artificial vehicle flow of each flow direction, and the maximum and minimum permitted cycle time, the maximum and minimum permitted phase green time, and the green interval time of the intersection.

[0033] A second parameter acquisition module is configured to determine the saturation flow rate of the V2X lane and the artificial vehicle lane, and the conversion coefficient of the left, straight, and right V2X vehicle flow and the artificial vehicle flow.

[0034] A channelization scheme configuration module is configured to determine the channelization scheme of the multi-lane intersection in the mixed traffic environment corresponding to the to-be-analyzed intersection in combination with the layout of the road segments connected to the to-be-analyzed intersection.

[0035] In an exemplary embodiment, the system further comprises:

[0036] A signal timing scheme determination module is configured to construct a conflict set according to the relative positions of the V2X lane and the artificial vehicle lane and the running trajectories of each vehicle flow, and construct a mixed integer linear programming model based on the intersection channelization scheme, so as to optimize the signal timing scheme of the to-be-analyzed intersection with the maximum traffic capacity and / or the minimum delay of the to-be-analyzed intersection as the target.

[0037] According to a third aspect of the present disclosure, a storage medium is provided, and the storage medium stores a computer program. When the program is executed by a processor, the method for configuring time-space resources of a multi-lane single intersection in a mixed traffic environment according to the first aspect is implemented.

[0038] According to a fourth aspect of the present disclosure, an electronic device is provided, and the electronic device comprises a processor and a memory for storing executable instructions of the processor. The processor is configured to execute the executable instructions to implement the method for configuring time-space resources of a multi-lane single intersection in a mixed traffic environment according to the first aspect.

[0039] The method for configuring time and space resources of a multi-lane single intersection in a mixed traffic environment provided by one embodiment of the present disclosure optimizes an intersection channeling scheme according to whether a connected road section of the intersection is provided with a network-connected automatic vehicle lane, avoids interweaving of network-connected automatic vehicle flow and manual vehicle flow on the connected road section provided with the network-connected automatic vehicle lane at an intersection entrance, and improves intersection entrance safety in a mixed traffic environment; and optimizes an intersection signal timing scheme to improve intersection passing efficiency on the basis of ensuring internal operation safety of the intersection.

[0040] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure and serve to explain the principles of the present disclosure. It is apparent that the accompanying drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0042] Figure 1 A lane channeling diagram of a five-lane intersection in a mixed traffic environment is schematically shown;

[0043] Figure 2 A conflict diagram of a mixed traffic intersection is schematically shown;

[0044] Figure 3 A diagram schematically showing a NEMA phase structure is schematically shown;

[0045] Figure 4 A diagram schematically showing a method for configuring time and space resources of a multi-lane single intersection in a mixed traffic environment in an exemplary embodiment of the present disclosure is schematically shown;

[0046] Figure 5 A diagram schematically showing another method for configuring time and space resources of a multi-lane single intersection in a mixed traffic environment in an exemplary embodiment of the present disclosure is schematically shown;

[0047] Figure 6 A diagram schematically showing a system for configuring time and space resources of a multi-lane single intersection in a mixed traffic environment in an exemplary embodiment of the present disclosure is schematically shown;

[0048] Figure 7 A diagram schematically showing a composition of an electronic device in an exemplary embodiment of the present disclosure is schematically shown;

[0049] Figure 8 A diagram schematically showing a composition of a storage medium in an exemplary embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0050] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any number of manners, and are not limited to the examples described herein; rather, examples are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example implementations to those skilled in the art. Described features, structures, or characteristics can be combined in any suitable manner in one or more implementations.

[0051] Moreover, the drawings are not necessarily to scale. Like reference numerals can be used to denote like parts throughout the several views. Some of the block diagrams shown in the drawings are functional entities that can not necessarily correspond to physically or logically separate entities. These functional entities can be implemented in software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0052] In view of the disadvantages and deficiencies of the prior art, referring to Figure 4 In the example implementation shown, a method for configuring space-time resources of a multi-lane single intersection in a mixed environment is provided, including:

[0053] In step S1, the traffic flow of the network-connected automatic vehicles in each direction of the intersection to be analyzed, the traffic flow of the manual vehicles in each direction of the intersection to be analyzed, and the maximum and minimum allowable cycle time, the maximum and minimum allowable phase green time, and the green interval time of the intersection are determined.

[0054] In step S2, the saturation flow rates of the network-connected automatic vehicle lanes and the manual vehicle lanes, and the conversion coefficients of the left, straight, and right network-connected automatic vehicle flows and the manual vehicle flows are determined.

[0055] In step S3, in combination with the layout of the road segments connected to the intersection to be analyzed, a channelization scheme for the multi-lane intersection in the mixed environment corresponding to the intersection to be analyzed is determined.

[0056] The method for configuring space-time resources of a multi-lane single intersection in a mixed environment provided by the example implementation is for an intersection with four or more import lanes in each import direction for mixed traffic of network-connected automatic vehicles and manual vehicles, and network-connected automatic vehicle lanes and manual vehicle lanes are provided on the road segments connected to the intersection. A channelization scheme including network-connected automatic vehicle lanes and manual vehicle lanes is designed to separate the network-connected automatic vehicle flows and the manual vehicle flows at the multi-lane intersection in the mixed environment.

[0057] In step S1, the traffic flow of the network-connected automatic vehicles in each direction of the intersection to be analyzed, the traffic flow of the manual vehicles in each direction of the intersection to be analyzed, and the maximum and minimum allowable cycle time, the maximum and minimum allowable phase green time, and the green interval time of the intersection are determined.

[0058] In the example embodiment, the flow of the net-connected automatic vehicle in each direction, the flow of the manual vehicle in each direction, the maximum and minimum permitted cycle time of the intersection, the maximum and minimum permitted phase green time, and the green interval time can be determined.

[0059] Specifically, taking a typical five-lane cross signal intersection as an example, as shown in FIG. 1, four road sections connected with the intersection are each provided with two net-connected automatic vehicle lanes on the left side of the road section. Figure 1

[0060] The flow of the net-connected automatic vehicle in each direction and the flow of the manual vehicle are determined by field investigation, as shown in Tables 1 and 2.

[0061] The maximum and minimum permitted cycle time C of the intersection is determined based on manual experience, C = 120 s, C = 60 s, the maximum green time g = 80 s, the minimum permitted phase green time g = 6 s is determined based on the time demand of pedestrians crossing the street, and the green interval time w = 5 s is determined based on the principle of avoiding the “dilemma zone” of the intersection. max min max min

[0062]

[0063] Table 1: Flow of net-connected automatic vehicle (pcu / h)

[0064]

[0065] Table 2: Flow of manual vehicle (pcu / h)

[0066] In step S2, the saturation flow rate of the net-connected automatic vehicle lane and the manual vehicle lane, and the conversion coefficient of the left, straight, and right net-connected automatic vehicle flow and the manual vehicle flow are determined.

[0067] In the example embodiment, the saturation flow rate can be determined according to the theoretical model method and the measurement method. Specifically, the minimum following vehicle head time of the net-connected automatic vehicle and the manual vehicle at the intersection can be obtained by investigation and statistics, for example, the minimum following vehicle head time of the net-connected automatic vehicle and the manual vehicle in the example embodiment is η1 = 1.5 s and η2 = 2 s, respectively, and the saturation flow rate S of the net-connected automatic vehicle lane and the manual vehicle lane is determined based on the inverse relationship between the saturation flow rate and the minimum following vehicle head time, which is 2400 pcu / h and 1800 pcu / h, respectively.

[0068] The flow in the left, straight, and right directions is converted into an equivalent straight flow by using the conversion coefficient, so as to facilitate unified calculation. The conversion coefficient can be determined according to the theoretical model method, the capacity calculation method, the speed-flow calculation method, the overtaking rate method, the delay calculation method, and the vehicle head time method, etc. In the example embodiment, the conversion coefficient is determined according to the following formula: ​​​​​x e {L, T, R}, m e {A, H} are calculated, wherein is the conversion coefficient of the x-turning m-type vehicle; is the turning radius of the x-turning m-type vehicle, L, T, R represent left turn, straight and right turn respectively, and A, H represent the networked automatic vehicle flow and the manual vehicle flow respectively. In the embodiment, the turning radii of the left, straight and right networked automatic vehicle flows and the manual vehicle flows are the same, and are The conversion coefficients are calculated as

[0069] In step S3, the multi-lane intersection channelization scheme under the mixed traffic environment corresponding to the intersection to be analyzed is determined in combination with the layout of the road sections connected to the intersection to be analyzed.

[0070] In the example embodiment, the step S3 described above can include:

[0071] A certain entrance road section connected to the intersection is set as a networked automatic vehicle lane on the left side or the right side of the intersection, and other lanes are used for manual vehicle operation;

[0072] The networked automatic vehicle lane is provided with a pre-signal light and a pre-signal stop line, and a series control area between the pre-signal stop line and the intersection stop line;

[0073] The networked automatic vehicle lane on the upstream side of the pre-signal stop line close to the manual lane is configured as a parking queue area, and the other lane is configured as a passing area;

[0074] The left, straight and right three networked automatic vehicle flows on the two continuous networked automatic vehicle lanes are controlled in series by using the pre-signal;

[0075] According to the consistency principle of the left, straight and right turning vehicle flow ratio and the guide lane number ratio, the channelization scheme of the manual vehicle lane of the intersection to be analyzed is configured.

[0076] Specifically, the design of the multi-lane intersection channelization scheme under the mixed traffic environment mainly includes the following processes:

[0077] c31, a certain entrance road section connected to the intersection is set as a networked automatic vehicle lane on the left side or the right side of the intersection, and other lanes are used for manual vehicle operation; the number of networked automatic vehicle lanes and manual vehicle lanes is set according to the number of road lanes, the networked automatic vehicle flow and the manual vehicle flow; here, according to the networked automatic vehicle flow and the manual vehicle flow ratio, two continuous networked automatic vehicle lanes are set on the left side of each entrance direction, as shown in Figure 1 .

[0078] c32, the pre-signal lamp and the pre-signal stop line are arranged on the dedicated lane for the automatic connected vehicle, the pre-signal stop line and the intersection stop line are in series control area, the automatic connected vehicle flow stops and waits for the green light signal of the intersection, and then drives away from the intersection, as shown in Figure 1 The length of the series control area needs to accommodate any one of the left, straight, and right automatic connected vehicle flows in a period. B represents the series control area, which is calculated as follows:

[0079]

[0080] In the formula, and are the automatic connected vehicle flow in the left, straight, and right turning directions of the i import direction, respectively;

[0081] C is the signal period length;

[0082] is the average vehicle headway when the vehicle stops and queues.

[0083] c33, the pre-signal upstream near the artificial lane side of the dedicated lane for the automatic connected vehicle is set as a parking queue area, which is used for the non-permitted turning vehicle flow to stop and give way at the current time, and the length of the parking queue area needs to accommodate any two kinds of turning vehicle flow in a period. O represents the parking queue area, which is calculated as follows:

[0084]

[0085] In the formula, and are the green light lengths of the left, straight, and right turning automatic connected vehicle flows in the i import direction, respectively;

[0086] The other side lane is set as a passing area for the permitted turning automatic connected vehicle flow. Usually, one passing area is configured, and π-1 passing queue areas are configured.

[0087] The sum of the lengths of the series control area and the parking queue area should be less than the length of the road section.

[0088] c34, the pre-signal is used to control the left, straight, and right three automatic connected vehicle flows on two continuous automatic connected vehicle lanes in series, that is, the three vehicle flows use all the automatic connected vehicle lanes in the series control area to drive away from the intersection in turn;

[0089] c35, the channelization scheme of the artificial vehicle lane of the intersection is set according to the consistency principle of the left, straight, and right turning vehicle flow ratio and the number of guide lanes. Here, the consistency principle means that the difference between the left, straight, and right turning vehicle flow ratio and the corresponding guide lane number ratio is within a reasonable range.

[0090] When the left-turn artificial vehicle flow volume of the import direction i is in the following range, set n i,1 left-turn artificial lanes, otherwise, set 1 straight-left artificial lane, n i,1 -1 left-turn artificial lane;

[0091]

[0092] In the formula: λ1 and λ2 are two control scale parameters, respectively controlling the consistency range of the left-turn and straight-right-turn artificial vehicle flow volume ratio and the corresponding lane number ratio, which are pre-set according to artificial experience;

[0093] n i,2 is the sum of the straight and right-turn artificial lane numbers of the import direction i, and n i,2 =n i -n i,1 , n i is the number of lanes allowed for artificial vehicle operation of the import direction i;

[0094] and respectively represent the conversion coefficients of the left, straight, and right-turn of the artificial vehicle flow of the import direction i;

[0095] and respectively represent the left, straight, and right-turn flow of the artificial vehicle flow of the import direction i;

[0096] When the right-turn artificial vehicle flow volume of the import direction i is in the following range, set n i,3 right-turn artificial lanes, otherwise, set 1 straight-right artificial lane, n i,3 -1 right-turn artificial lane;

[0097]

[0098] In the formula: λ3 and λ4 are two control scale parameters, respectively controlling the consistency range of the right-turn and left-straight-turn artificial vehicle flow volume ratio and the corresponding lane number ratio, which are pre-set according to artificial experience;

[0099] n i,4 is the sum of the straight-left-turn artificial lane numbers or the straight artificial lane number of the import direction i, when the straight-left artificial lane is set for the import direction i, n i,4 is the sum of the straight-left-turn artificial lane numbers of the import direction i, n i,4 =n i -n i,3 ; when the straight-left artificial lane is not set for the import direction i, n i,4 is the straight artificial lane number of the import direction i, n i,4 =n i,2 -ni,3 , and let the above formula

[0100] The remaining lanes in the import direction i are all set as artificial straight lanes, allowing artificial straight traffic to run.

[0101] For example, since four road sections connected with the intersection are all equipped with two automatic vehicle lanes on the left side of the road section, the two left import lanes of each import direction of the intersection are set as automatic vehicle lanes, and the remaining three right import lanes are used for artificial traffic to run.

[0102] The automatic vehicle traffic is implemented in series control, that is, three traffic flows use all automatic vehicle lanes in the series control zone to leave the intersection in turn, for example, first, the pre-signal left turn green light signal is turned on to allow the left turn automatic vehicle traffic to enter the series control zone, then the intersection left turn green light signal is turned on and the pre-signal left turn green light signal is turned off, the left turn automatic vehicle traffic passes through all import lanes of the series control zone to leave the intersection; secondly, the intersection left turn green light signal is turned off and the pre-signal straight green light is turned on to allow the straight automatic vehicle traffic to enter the series control zone, then the intersection straight green light signal is turned on and the pre-signal straight green light signal is turned off, the straight automatic vehicle traffic passes through all import lanes of the series control zone to leave the intersection; finally, the intersection straight green light signal is turned off and the pre-signal right turn green light is turned on to allow the right turn automatic vehicle traffic to enter the series control zone, then the intersection right turn green light signal is turned on and the pre-signal right turn green light signal is turned off, the right turn automatic vehicle traffic passes through all import lanes of the series control zone to leave the intersection; the above process is periodically repeated to realize series control of the automatic vehicle traffic, as shown in Figure 1 .

[0103] According to the field investigation statistics, the average vehicle headway of the automatic vehicle queue in the embodiment is determined as The cycle length C can be the maximum cycle length or the actual implemented cycle length, and the green light length of each automatic vehicle phase g A The green light length can be obtained based on the maximum cycle length and the green split ratio, or the actual implemented green light length. In the example embodiment, the cycle length C and the green light length of each automatic vehicle phase g A The cycle length and the green light length are the actual implemented cycle length and green light length after optimization of the signal timing optimization model, therefore, the lengths of the series control zone and the parking queue zone are determined after the signal timing scheme is determined.

[0104] The four control dimension parameters λ1=1.5, λ2=2.5, λ3=1.0, λ4=1.5 in the import lane channelization scheme design of the artificial traffic are determined, and then n i,1 =1, n i,2 =2, ni,3 = 0, n i,4 = 2, i e {1, 2, 3, 4}, satisfying the consistency principle of left, straight, and right turning vehicle flow rate ratio and guide lane number ratio, that is, setting lane 3 of each import direction of the intersection as a left turning lane for artificial vehicles, setting lane 2 as a straight lane for artificial vehicles, and setting lane 1 as a straight and right lane for artificial vehicles.

[0105] Referring to Figure 5 In the example embodiment shown, a method for configuring time-space resources of a multi-lane single intersection in a mixed traffic environment is also provided, comprising:

[0106] Step S1, determining the network-connected automatic vehicle flow rate of each flow direction, the artificial vehicle flow rate of each flow direction, and the maximum and minimum allowable period length, the maximum and minimum allowable phase green light length, and the green light interval time of the intersection to be analyzed;

[0107] Step S2, determining the saturation flow rate of the network-connected automatic vehicle lane and the artificial vehicle lane, and the conversion coefficient of the left, straight, and right network-connected automatic vehicle flow and artificial vehicle flow;

[0108] Step S3, determining the channelization scheme of the multi-lane intersection corresponding to the intersection to be analyzed in the mixed traffic environment according to the layout of the connected road sections of the intersection to be analyzed.

[0109] Step S4, constructing a conflict set according to the relative positions of the network-connected automatic vehicle lane and the artificial vehicle lane and the running trajectories of each vehicle flow;

[0110] Step S5, constructing a mixed integer linear programming model based on the intersection channelization scheme to optimize the signal timing scheme of the intersection to be analyzed with the maximum traffic capacity and / or the minimum delay as the target.

[0111] In the example embodiment, in step S4, the conflict set includes intersection conflicts, merging conflicts, and series conflicts. Wherein, the conflict set is constructed according to the relative positions of the network-connected automatic vehicle lane and the artificial vehicle lane and the running trajectories of each vehicle flow, including:

[0112] According to the layout position of the network-connected automatic vehicle lane and the running trajectories of each vehicle flow, it is determined whether the running trajectories of two different turning vehicle flows intersect within the intersection, and the conflict vehicle flows that have intersection conflicts are added to the conflict set;

[0113] According to the layout position of the network-connected automatic vehicle lane and the running trajectories of each vehicle flow, it is determined whether the running trajectories of two different turning vehicle flows have merging conflicts at the exit lane, and the conflict vehicle flows that have merging conflicts are added to the conflict set;

[0114] The three streams of the networked automatic vehicle in the direction provided with the networked automatic vehicle special lane are paired two by two, and added to the conflict set as the series conflict traffic flow.

[0115] Specifically, first, the conflict traffic flow that occurs intersection conflict is determined, and the traffic flow is represented by (i, j, m), where i and j represent the entrance and exit lane numbers of the traffic flow, respectively, and m is the traffic flow type, m∈{A, H}. The conflict traffic flow of the artificial traffic flow and the networked automatic vehicle in each entrance direction is determined clockwise according to the left, straight, and right turning sequence, and the conflict traffic flow is added to the conflict set. For example Figure 2 The trajectory of the left-turn artificial traffic flow in the entrance direction 1 and the trajectories of the left-turn artificial traffic flow and the networked automatic vehicle in the entrance direction 2 occur intersection inside the intersection, and intersection conflict occurs, and the conflict traffic flows ((1, 2, H), (2, 3, H)) and ((1, 2, H), (2, 3, A)) are added to the conflict set.

[0116] Secondly, the conflict traffic flow that occurs merging conflict is determined, and all traffic flows in each exit lane are determined clockwise, and the traffic flow in which merging conflict occurs is determined. For example Figure 2 The trajectory of the right-turn networked automatic vehicle in the entrance direction 1 and the trajectory of the straight artificial traffic flow in the entrance direction 2 occur merging intersection at the exit lane of the entrance direction 4, and merging conflict occurs, and the conflict traffic flow ((1, 4, A), (2, 4, H)) is added to the conflict set.

[0117] Finally, the entrance direction provided with the networked automatic vehicle special lane is determined, and the three streams of the networked automatic vehicle in the direction are paired two by two, and added to the conflict set as the series conflict traffic flow. For example Figure 2 In the entrance direction 3, the networked automatic vehicle special lane is provided, and the left, straight, and right three streams of the networked automatic vehicle in the entrance direction 3 occur series conflict two by two, and are added to the conflict set.

[0118] In step S5, a mixed integer linear programming model is constructed based on the intersection channeling scheme, so as to analyze the intersection traffic capacity maximum and / or delay minimum as the target, and optimize the signal timing scheme of the intersection to be analyzed.

[0119] In the example embodiment, the step S5 described above can include:

[0120] The conflict traffic flow is separated from the time dimension according to the first constraint condition;

[0121] According to the second constraint condition, it is ensured that the allocated artificial traffic phase green light meets the phase structure requirement;

[0122] According to the third constraint condition, it is ensured that the artificial traffic flows in the same lane group have the same green light phase;

[0123] According to the fourth constraint condition, it is ensured that the phase saturation degree of the mixed intersection with the dedicated lane for the connected and automated vehicles meets the maximum saturation degree.

[0124] According to the fifth constraint condition, it is ensured that the optimized timing parameters are within the permitted range.

[0125] Based on the constraint conditions, a mixed integer linear programming model is constructed.

[0126] Specifically, the signal timing optimization model aiming at the maximum intersection capacity and / or the minimum delay includes a conflict separation module (the first constraint condition), an artificial traffic phase structure constraint module (the second constraint condition), a lane group constraint module (the third constraint condition), a saturation degree constraint module (the fourth constraint condition), a parameter range constraint module (the fifth constraint condition), and an optimization target module. The specific construction process includes:

[0127] In order to ensure the safety of intersection operation, it is necessary to separate the conflict traffic flow from the time dimension, ensure that the time of the conflict traffic flow passing through the intersection is separated from each other, and construct the following conflict separation module to realize that the conflict traffic flow is given the right to pass at different times by optimizing the signal phase sequence.

[0128] Specifically, the conflict separation module separates the conflict traffic flow from the time dimension through the following constraints:

[0129]

[0130]

[0131]

[0132]

[0133] Wherein, I represents a set of import direction numbers, and the import direction is numbered clockwise; Ω represents a set of conflict traffic flows; represents the green light starting time of the m type traffic flow (i, j), m∈{A, H}, wherein A represents the connected and automated vehicle flow, H represents the artificial traffic flow, and the traffic flow (i, j) represents the traffic flow from the i import direction to the j import direction. According to the different j import directions, the left, straight, and right turning traffic flows of the i import direction are represented.

[0134] represents the green light duration of the m type traffic flow (i, j); w represents the green light interval duration; M represents a large positive integer; represents the green light phase sequence of the m1 type traffic flow (i, j) and the m2 type traffic flow (t, v), which is a binary variable, The green light of the m1 type traffic flow (i, j) is earlier than the green light of the m2 type traffic flow (t, v), otherwise, the green light is later than the green light of the m2 type traffic flow (t, v).

[0135] Formula (1) ensures that the phase sequences of the conflicting traffic flows (i, j) and (t, v) are separated in time, eliminating the conflict; formula (2) ensures that the green light sequences of the conflicting traffic flows (i, j) and (t, v) are consistent; formula (3) ensures that there is a clearance time between the first phase of the new cycle and the last phase of the last cycle; and formula (4) is a binary constraint.

[0136] Specifically, the artificial traffic phase structure constraint module ensures that the green light of the assigned artificial traffic phase meets the phase structure requirements through the following constraints:

[0137]

[0138]

[0139]

[0140]

[0141]

[0142] Wherein, the import direction number The import direction number The import direction number

[0143] F represents a set of conflicting traffic flows constructed by referring to the front half-ring conflicting traffic flow and the rear half-ring conflicting traffic flow in the traditional NEMA phase structure, F = {((i, j), (j, t), (t, i), (j, t)), ((i, j), (d, j), (t, i), (d, j)), ((i, j), (j, t), (i, j), (d, j)), ((t, i), (j, t), (t, i), (d, j))}. f1, f2, f3, f4 respectively represent the four traffic flows in each element in the set F; and C represents the signal cycle length.

[0144] Formula (5) represents that the cycle length of the mixed traffic intersection is not less than the sum of the green light lengths of the four artificial traffic flows that conflict with each other in the artificial traffic phase structure; formula (6) represents that the cycle length of the mixed traffic intersection is not less than the green light time of the m type traffic flow (i, j); formulas (7) and (8) respectively represent that the sum of the straight and left turn green light times of the artificial traffic flows in the same road in the intersecting road is equal; and formula (9) represents that the phase sequence relationship of the conflicting traffic flows in the same road and the conflicting traffic flows in the intersecting road is the same.

[0145] For the phase structure of artificial vehicle flow at mixed intersection, its structure is similar to the traditional NEMA phase structure, double ring structure, that is, the left turn and straight phase of different import directions of the same road section are located in the same ring, and the left turn and straight phases of different import directions of the intersection section are located in different rings, for example Figure 3 The left turn and straight phases of east-west direction (phases 1, 2, 5, 6) are located in the front half ring, and the left turn and straight phases of south-north direction (phases 3, 4, 7, 8) are located in the rear half ring. In addition, there are differences, for example, when there is a straight right lane, and the net-connected automatic vehicle lane is arranged on the right side, due to the conflict between the right turn artificial vehicle flow and the straight net-connected automatic vehicle flow, the barrier 1, 3 outside potential straight net-connected automatic vehicle flow phase is adopted, the barrier 1, 3 inside potential straight net-connected automatic vehicle flow phase is deleted, and the green light time of the right turn net-connected automatic vehicle flow phase is given, at this time, the sum of the green light time of the artificial vehicle flow phase is not equal to the cycle time, and the green light end point of each artificial vehicle flow phase is not greater than the cycle time. When the net-connected automatic vehicle lane is arranged on the left side or there is no straight right lane, the barrier 1, 3 inside potential straight net-connected automatic vehicle flow phase is adopted, the barrier 1, 3 outside potential straight net-connected automatic vehicle flow phase is deleted, at this time, the sum of the green light time of the artificial vehicle flow phase is equal to the cycle time. The above-mentioned artificial vehicle flow phase structure is constructed by constructing the constraint.

[0146] Specifically, the lane group constraint module ensures that the artificial vehicle flows of the same lane group have the same green light phase through the following constraints:

[0147]

[0148]

[0149] Wherein, K is respectively a lane group set, and k is a certain lane group; g k represents the green light time of the lane group k.

[0150] Equations (10) and (11) ensure that the green light start point and the green light time of the two artificial vehicle flows (i, j) and (t, v) of the same lane group k are the same.

[0151] For different turning artificial vehicle flows belonging to the same lane group, the green light phases should be the same.

[0152] Specifically, the saturation constraint module ensures that the phase saturation of the mixed intersection where the net-connected automatic vehicle lane is arranged meets the maximum saturation constraint requirement through the following constraints:

[0153]

[0154] Wherein, represents the conversion coefficient of the m type vehicle flow (i, j), m∈{A, H};

[0155] N k denotes the number of lanes that lane group k has;

[0156] S k denotes the saturated flow rate of lane group k;

[0157] p k denotes the maximum saturation degree allowed by lane group k;

[0158] λ k denotes whether lane group k is a dedicated lane for connected and automated vehicles, if yes, λ k = 1, otherwise, λ k = 0.

[0159] For each phase, the green time allocated needs to ensure that the saturation degree of the phase under the time length scheme is not greater than the maximum saturation degree requirement, and the constraint is constructed to achieve the maximum saturation degree constraint requirement of the mixed intersection where the dedicated lane for connected and automated vehicles is laid out.

[0160] Specifically, the parameter range constraint module ensures that the optimized timing parameters are within the permitted range by the following constraints:

[0161]

[0162] C min ≤ C ≤ C max (14)

[0163] wherein g max and g min denote the maximum and minimum permitted green time respectively; C max and C min denote the maximum and minimum permitted cycle time respectively.

[0164] Equations (13) and (14) respectively ensure that the optimized green time and cycle time meet the maximum and minimum value requirements.

[0165] The optimization objective module achieves the objective of maximum intersection capacity and / or minimum vehicle delay by constructing an objective function. In this embodiment, the objective of maximum intersection capacity and minimum vehicle delay is taken, and the objective function is constructed as follows:

[0166]

[0167] wherein M denotes a sufficiently large positive integer.

[0168] Based on the principle that the longer the green time, the greater the capacity, and the smaller the cycle time, the smaller the vehicle delay, the objective function is constructed to achieve the objective of maximum intersection capacity and minimum vehicle delay.

[0169] Based on the above, in this example implementation, the method further includes: using the GAMS solver to solve the mixed-integer linear programming model to obtain the signal timing scheme under the designed lane channelization scheme that maximizes the intersection capacity and minimizes the delay.

[0170] Specifically, the above signal timing optimization model was solved using the GAMS solver to obtain the signal timing scheme under the designed lane channelization scheme with the maximum intersection capacity and the minimum delay. The results are shown in Table 3, with a cycle length of C = 106s.

[0171]

[0172] Table 3 Optimal Signal Timing Scheme for Five-Lane Intersections

[0173] Based on the cycle duration C, the lengths of the series control zone and parking queue zone for inlets 1-4 are determined as follows:

[0174] This disclosure provides a method for spatiotemporal resource allocation at a multi-lane single intersection in a mixed-traffic environment. It optimizes the intersection channelization scheme based on whether connected automated vehicle lanes (VLRs) are deployed on the connecting road segments, preventing the weaving of connected automated vehicle traffic and manual traffic at the intersection entrance on connected road segments with VLR lanes, thus improving intersection entrance safety in a mixed-traffic environment. Furthermore, it optimizes the intersection signal timing scheme through a constructed signal timing optimization model that aims to maximize intersection capacity and / or minimize delays, thereby improving intersection traffic efficiency while ensuring safe operation within the intersection.

[0175] Further reference Figure 6 As shown, this example implementation also provides a spatiotemporal resource allocation system 10 for a multi-lane single intersection in a mixed-traffic environment, including: a first parameter acquisition module 101, a second parameter acquisition module 102, and a channelization scheme configuration module 103. Wherein,

[0176] The first parameter acquisition module 101 is used to determine the traffic flow of each direction of the connected automatic traffic flow, the traffic flow of each direction of the manual traffic flow at the intersection to be analyzed, as well as the maximum and minimum permit cycle duration, the maximum and minimum permit phase green light duration, and the green light interval time of the intersection.

[0177] The second parameter acquisition module 102 is used to determine the saturation flow rate of the connected automated vehicle lane and the manual vehicle lane, as well as the conversion coefficients of the left, straight, and right connected automated vehicle flow and the manual vehicle flow.

[0178] The channelization scheme configuration module 103 is used to determine the channelization scheme for a multi-lane intersection under mixed traffic conditions by combining the layout of the road segments connected to the intersection to be analyzed.

[0179] Further, the multi-lane single intersection space-time resource configuration system 10 under the mixed traffic environment can further comprise:

[0180] A conflict set construction module is configured to construct a conflict set according to the relative positions of the automatic vehicle lane and the manual vehicle lane and the running trajectories of the vehicle flows.

[0181] A signal timing scheme determination module is configured to construct a mixed integer linear programming model based on the intersection channelization scheme, and optimize the signal timing scheme of the intersection to be analyzed with the maximum intersection capacity and / or the minimum delay as the target.

[0182] Further, the channelization scheme configuration module can comprise: setting π continuous lanes on the left side or the right side of a certain entrance road section connected with the intersection as the automatic vehicle lane, and setting other lanes for manual vehicle operation; setting a pre-signal for the automatic vehicle lane and a pre-signal stop line, and setting a series control zone between the pre-signal stop line and the intersection stop line; configuring the automatic vehicle lane on the upstream side of the pre-signal stop line close to the manual lane as a parking queue area, and configuring the lane on the other side as a passing area; controlling the left, straight, and right three automatic vehicle flows on the π continuous automatic vehicle lanes in a series manner by using the pre-signal; and configuring the channelization scheme of the manual vehicle lane of the intersection to be analyzed according to the consistency principle of the left, straight, and right turning vehicle flow flow rate ratio and the guide lane number ratio.

[0183] Further, the length of the series control zone is set according to the parking queue of any one of the turning vehicle flows in the automatic vehicle flow in one period, and the length of the parking queue area is set according to the parking queue of any two of the turning vehicle flows in the automatic vehicle flow in one period, and the sum of the length of the series control zone and the length of the parking queue area should be less than the length of the road section.

[0184] Further, the conflict set comprises: intersection conflict, merging conflict, and series conflict.

[0185] Further, the signal timing scheme determination module can be further configured to determine whether the running trajectories of two different turning vehicle flows intersect within the intersection according to the layout position of the automatic vehicle lane and the running trajectories of the vehicle flows, and add the conflict vehicle flows that will cause intersection conflict to the conflict set; determine whether the running trajectories of two different turning vehicle flows cause merging conflict at the exit lane according to the layout position of the automatic vehicle lane and the running trajectories of the vehicle flows, and add the conflict vehicle flows that will cause merging conflict to the conflict set; and pair the three automatic vehicle flows in the direction of the entrance direction with the automatic vehicle lane set in this direction two by two as series conflict vehicle flows and add them to the conflict set.

[0186] Further, the signal timing scheme determination module can further include: separating the conflict traffic flow from the time dimension according to a first constraint condition; ensuring that the distributed artificial vehicle flow phase green light meets the phase structure requirement according to a second constraint condition; ensuring that the artificial vehicle flow of the same lane group has the same green light phase according to a third constraint condition; ensuring that the phase saturation degree of the mixed intersection where the networked automatic vehicle lane is laid meets the maximum saturation degree according to a fourth constraint condition; ensuring that the optimized timing parameter is within the permitted range according to a fifth constraint condition; and constructing a mixed integer linear programming model based on the constraint conditions.

[0187] The specific details of the modules in the multi-lane single intersection space-time resource allocation system in the mixed environment have been described in detail in the corresponding multi-lane single intersection space-time resource allocation method in the mixed environment, and therefore will not be described here.

[0188] It should be noted that although several modules or units of the device for action execution are mentioned in the foregoing detailed description, such a division is not mandatory. Indeed, according to embodiments of the disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into several modules or units embodied.

[0189] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0190] Those skilled in the art can understand that various aspects of the present application can be implemented as a system, method or program product. Therefore, various aspects of the present application can be embodied as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" here.

[0191] The electronic device 400 according to this embodiment of the present application will be described below with reference to Figure 7 Figure 7 The electronic device 400 shown is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0192] As Figure 7 shown, the multi-lane single intersection space-time resource allocation system in the mixed environment is in the form of a general computing device. The components of the multi-lane single intersection space-time resource allocation system in the mixed environment can include but are not limited to: the at least one processing unit 410 described above, the at least one storage unit 420 described above, the bus 430 connecting different system components including the storage unit 420 and the processing unit 410. ​

[0193] The storage unit stores program codes which can be executed by the processing unit 410, so that the processing unit 410 performs the steps described in the above "Exemplary Methods" section according to various exemplary embodiments of the present application. For example, the processing unit 410 can perform the steps as shown in the above "Exemplary Methods" section. Figure 4

[0194] The storage unit 420 can include a readable medium in the form of volatile storage such as a random access memory (RAM) 4201 and / or cache memory 4202, and can further include a read-only memory (ROM) 4203.

[0195] The storage unit 420 can further include program / utility 4204 having a set of programs / modules 4205, including an operating system, one or more application programs, other programs, and programmatic data, each or any combination thereof, which can include implementation of a network environment.

[0196] The bus 430 can represent one or more of several types of bus structures, including a storage bus or bus controller, a peripheral bus, a graphics bus, a processor or local bus using any of a variety of bus architectures.

[0197] The multi-lane single intersection space-time resource configuration system under mixed traffic environment can also communicate with one or more external devices 300 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), and can further communicate with one or more devices that enable a user to interact with the load control system, and / or any devices (e.g., a router, a modem, etc.) that enable the load control system to communicate with one or more other computing devices. Such communication can be effected through the input / output (I / O) interface 450. Furthermore, the load control system can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or the public network, such as the Internet) through a network adapter 460. As depicted, the network adapter 460 communicates with the other modules of the load control system through the bus 430. The processing unit 410 is connected through the bus 430 to a display unit 440. It should be appreciated that, although not shown explicitly, other hardware and / or software modules can be used in conjunction with the load control system, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0198] ​Those skilled in the art can easily understand from the above description of the embodiments that the example embodiments described herein can be implemented by software or by software in combination with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash disk, a mobile hard disk, or the like) or on a network, and includes a number of instructions to make a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) execute the methods according to the embodiments of the present disclosure.

[0199] In the example embodiments of the present disclosure, a computer readable storage medium is also provided, on which a program product capable of implementing the above-mentioned methods of the present disclosure is stored. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program codes for causing a terminal device to perform the steps according to various example embodiments of the present disclosure described in the above-mentioned “example method” section of the present specification when the program product is run on the terminal device.

[0200] Reference Figure 8 As shown, a program product 500 for implementing the above-mentioned methods according to the embodiments of the present disclosure is described, which can take the form of a portable compact disc read-only memory (CD-ROM) and include program codes, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited to this, and in the present document, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device, or apparatus.

[0201] The program product can take any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, be but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0202] A computer readable signal medium can include a propagated data signal with computer executable code embodied therein. For example, a propagated signal can be an electromagnetic signal, an optical signal, and / or any other suitable type of signal. Such a propagated signal can be in the form of electrical magnetic waves, optical waves, and / or any other suitable type of waves upon which computer executable code is embodied. A suitable medium for storing and / or transmitting computer readable code includes one or more types of random access memory (RAM), magnetic storage, optical storage, and / or any other suitable type of storage.

[0203] Program code embodied on a computer readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0204] Computer readable program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider. The application program code can be downloaded to the user's computing device from an external computing device or server through any type of network, including a local area network, a wide area network, or the Internet using a browser or other applet.

[0205] Furthermore, the above-described figures are only schematic and are non-limiting. It is readily understood that the processes depicted in the figures are not necessarily performed in the order depicted. Further, it is readily understood that the processes can be performed synchronously or asynchronously, and that the processes can be performed in a different order than depicted in the figures.

[0206] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0207] It is to be understood that the application is not limited to the precise details of construction and the exemplary embodiments described above and illustrated in the drawings. Various modifications and changes can be made thereunto without departing from the scope of the application. The scope of the application is indicated by the appended claims rather than by the embodiments disclosed above.

Claims

1. A method for spatiotemporal resource allocation at a multi-lane single intersection in a mixed-traffic environment, characterized in that, The method includes: Determine the traffic flow of the connected automated traffic flow and the manual traffic flow for each direction at the intersection to be analyzed, as well as the maximum and minimum permit cycle duration, the maximum and minimum permit phase green light duration, and the green light interval time for the intersection. The saturation flow rates of the connected automated vehicle lanes and the manual vehicle lanes are determined, as well as the conversion coefficients for left-hand, straight-hand, and right-hand connected automated vehicle flows and manual vehicle flows. Among them, the minimum headway of connected automated vehicles and manual vehicles at the intersection is obtained based on survey statistics, and the saturation flow rates of the connected automated vehicle lanes and the manual vehicle lanes are determined based on the reciprocal relationship between the saturation flow rate and the minimum headway. Based on the layout of the road segments connected to the intersection to be analyzed, determine the channelization scheme for the multi-lane intersection under mixed traffic conditions corresponding to the intersection to be analyzed; The method further includes: constructing a conflict set based on the relative positions of the connected automated vehicle lane and the manual vehicle lane and the running trajectory of each traffic flow; constructing a mixed integer linear programming model based on the intersection channelization scheme, and optimizing the signal timing scheme of the intersection to be analyzed with the goal of maximizing the capacity of the intersection and / or minimizing the delay; Based on the intersection channelization scheme, a mixed-integer linear programming model is constructed. The goal is to maximize the capacity and minimize the delay at the intersection under analysis. The optimization of the signal timing scheme for the intersection includes: separating conflicting traffic flows in the time dimension according to a first constraint; ensuring that the allocated green light phases for manual traffic flows meet phase structure requirements according to a second constraint; ensuring that manual traffic flows in the same lane group have the same green light phase according to a third constraint; ensuring that the phase saturation at mixed-traffic intersections with connected automated vehicle lanes meets the maximum saturation requirement according to a fourth constraint; and ensuring that the optimized timing parameters are within permissible limits according to a fifth constraint. A mixed-integer linear programming model is then constructed based on these constraints. The following constraints ensure that the phase saturation at mixed-traffic intersections with dedicated lanes for connected automated vehicles meets the maximum saturation constraint requirement: in, Let m represent the conversion factor for type m traffic flow (i, j), where m ∈ {A, H}; This indicates the number of lanes in lane group k; This represents the saturation flow rate of lane group k; This represents the maximum saturation allowed for lane group k; Indicate whether lane group k is a lane for connected autonomous vehicles. If so, =1, otherwise, =0.

2. The method according to claim 1, characterized in that, The process of determining the channelization scheme for a multi-lane intersection under mixed-traffic conditions, based on the layout of the road segments connected to the intersection to be analyzed, includes: One of the π consecutive lanes on the left or right side of a certain entrance road section connected to the intersection is set up as a dedicated lane for connected automated vehicles, while the other lanes are for manual vehicles. The connected automated vehicle lane is equipped with pre-signal lights and pre-signal stop lines. The pre-signal stop line and the intersection stop line are connected in series control areas. The lane for connected automated vehicles upstream of the pre-signal stop line, closer to the manual lane, is designated as a parking queuing area, while the lane on the other side is designated as a passage area. The left, straight, and right traffic flows on π continuous connected automated vehicle lanes are controlled in series using pre-signals; Based on the principle of consistency between the ratio of left, straight, and right turning traffic flow and the ratio of the number of guiding lanes, a channelization scheme for the manual vehicle lane at the intersection to be analyzed is configured.

3. The method according to claim 2, characterized in that, The length of the series control zone is set to accommodate parking and queuing of any type of turning traffic flow in the connected automated traffic flow within one cycle. The parking queuing area is set to accommodate parking and queuing of any two types of turning traffic flow in the connected automated traffic flow within one cycle. The sum of the length of the series control zone and the length of the parking queuing area should be less than the length of the road segment.

4. The method according to claim 1, characterized in that, The conflict set includes: cross-conflicts, merging conflicts, and series conflicts.

5. The method according to claim 4, characterized in that, Based on the relative positions of the connected automated vehicle lanes and the manual vehicle lanes, and the trajectories of each traffic flow, a conflict set is constructed, including: Based on the location of the connected automated vehicle lanes and the trajectory of each traffic flow, determine whether the trajectories of two traffic flows with different directions intersect within the intersection, and add the conflicting traffic flows that intersect to the conflict set. Based on the location of the connected automated vehicle lane and the trajectory of each traffic flow, determine whether the trajectories of two traffic flows with different directions will merge and conflict at the exit lane, and add the conflicting traffic flows that have merged and conflicted to the conflict set. The three connected automated vehicle flows in the direction of the entrance are paired up and added to the conflict set as serial conflict flows.

6. A spatiotemporal resource allocation system for a multi-lane single intersection in a mixed-traffic environment, characterized in that, The system includes: The first parameter acquisition module is used to determine the traffic flow of connected automated traffic flow in each direction, the traffic flow of manual traffic flow in each direction at the intersection to be analyzed, as well as the maximum and minimum permit cycle duration, the maximum and minimum permit phase green light duration, and the green light interval time of the intersection. The second parameter acquisition module is used to determine the saturation flow rate of the connected automated vehicle lane and the manual vehicle lane, as well as the conversion coefficients for left, straight, and right connected automated vehicle flow and manual vehicle flow; wherein, based on the survey statistics, the minimum following headway of connected automated vehicles and manual vehicles at the intersection is obtained, and the saturation flow rate of the connected automated vehicle lane and the manual vehicle lane is determined based on the reciprocal relationship between the saturation flow rate and the minimum following headway; The channelization scheme configuration module is used to determine the channelization scheme for a multi-lane intersection in a mixed traffic environment, based on the layout of the road segments connected to the intersection to be analyzed. The system also includes: The signal timing scheme determination module is used to construct a conflict set based on the relative positions of the connected automated vehicle lane and the manual vehicle lane and the running trajectory of each traffic flow; and to construct a mixed integer linear programming model based on the intersection channelization scheme to optimize the signal timing scheme of the intersection to be analyzed with the goal of maximizing the capacity of the intersection and / or minimizing the delay. Based on the intersection channelization scheme, a mixed-integer linear programming model is constructed. The goal is to maximize the capacity and minimize the delay at the intersection under analysis. The optimization of the signal timing scheme for the intersection includes: separating conflicting traffic flows in the time dimension according to a first constraint; ensuring that the allocated green light phases for manual traffic flows meet phase structure requirements according to a second constraint; ensuring that manual traffic flows in the same lane group have the same green light phase according to a third constraint; ensuring that the phase saturation at mixed-traffic intersections with connected automated vehicle lanes meets the maximum saturation requirement according to a fourth constraint; and ensuring that the optimized timing parameters are within permissible limits according to a fifth constraint. A mixed-integer linear programming model is then constructed based on these constraints. The following constraints ensure that the phase saturation at mixed-traffic intersections with dedicated lanes for connected automated vehicles meets the maximum saturation constraint requirement: in, Let m represent the conversion factor for type m traffic flow (i, j), where m ∈ {A, H}; This indicates the number of lanes in lane group k; This represents the saturation flow rate of lane group k; This represents the maximum saturation allowed for lane group k; Indicate whether lane group k is a lane for connected autonomous vehicles. If so, =1, otherwise, =0.

7. A storage medium storing a computer program thereon, said program, when executed by a processor, implements the spatiotemporal resource allocation method for a multi-lane single intersection in a mixed-traffic environment according to any one of claims 1 to 5.

8. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; Wherein, the processor is configured to implement the spatiotemporal resource allocation method for a multi-lane single intersection in a mixed traffic environment according to any one of claims 1 to 5 when executing the executable instructions.

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