Lane problem identification method based on fusion of Internet data and intersection detector

Abstract

The invention discloses a lane problem identification method based on fusion of Internet data and an intersection detector. The method comprises the following steps: determining a problem intersection and an intersection direction needing to be optimized; judging whether the imbalance coefficient of the intersection is smaller than a threshold value; judging whether the entrance lane number is matched with the exit lane number; judging whether the left-turn traffic flow and the straight traffic flow of the entrance lane are matched with the attributes of the entrance lane; judging whether the left-turn traffic flow and the right-turn traffic flow of the entrance lane are matched with the attributes of the entrance lane; judging whether the mixed lane interference condition is greater than a threshold value or not according to the traffic flow state when the green light is over; and calculating the expected queue after the lane number adjustment, and determining a lane number adjustment scheme, thereby determining the problems existing in the lane. According to the method, the road network and the green wave scheme are combined to optimize lane setting, various data sources of the intersection are fused and applied, the found lane problems are comprehensive, and the reasonability of the optimization scheme is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic signal control, and in particular relates to a lane problem identification method based on the fusion of Internet data and intersection detectors. Background Art

[0002] Traffic flow is highly volatile, and the allocation of road resources will affect the public's travel experience; the lane division at the intersection is the spatial manifestation of road resources, and it is particularly important to promptly detect whether there are any problems with the lane configuration.

[0003] Existing technologies primarily address single issues, such as interference between left-turning and through-traffic flows in entrance lanes, or interference from left-turning vehicles like buses. Due to the limited spatial resources at intersections, lane management is a complex issue, requiring simultaneous consideration of the intersection's alignment with upstream and downstream traffic, the alignment of entrance and exit lanes, and the alignment of different traffic flows within entrance lanes. Current technologies utilize a relatively single data source, resulting in incomplete lane identification. Adjustment plans address interference in certain lanes while providing insufficient consideration for interference in other lanes. Summary of the Invention

[0004] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a lane problem identification method based on the fusion of Internet data and intersection detectors, so as to solve the problem that the prior art has a relatively single lane interference identification and does not comprehensively consider various types of interference.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] The present invention provides a lane problem identification method based on the fusion of Internet data and intersection detectors, comprising the following steps:

[0007] 1) Based on the intersection rating data and intersection direction rating data from the internet, combined with detector data, the number of main road stops, main road travel speed, and free flow speed are calculated to identify problem intersections and intersection directions that need to be optimized;

[0008] 2) Determine whether the imbalance coefficient of the intersection is less than a threshold. If so, calculate the minimum green light time recommended by pedestrians, and modify the timing plan based on the minimum green light time recommended by pedestrians and the traffic flow ratio to optimize it, and proceed to step 3); if not, directly proceed to step 3);

[0009] 3) Determine whether the number of import lanes matches the number of export lanes. If so, proceed to step 4); if not, modify the lane attributes and proceed to step 4);

[0010] 4) Determine whether the left-turn traffic flow and the straight traffic flow in the import lane match the attributes of the import lane. If so, proceed to step 5); if not, modify the lane attributes and proceed to step 5);

[0011] 5) Determine whether the left-turn traffic flow and the right-turn traffic flow in the import lane match the import lane attributes. If so, proceed to step 6); if not, modify the lane attributes and proceed to step 6);

[0012] 6) Based on the traffic flow status after the green light ends, determine whether the mixed lane interference situation is greater than the threshold. If so, modify the lane attributes and proceed to step 7); if not, directly proceed to step 7);

[0013] 7) Calculate the expected queue after the number of lanes is adjusted, determine the lane number adjustment plan, and thus identify the problems existing in the lanes.

[0014] Furthermore, the step 1) specifically includes:

[0015] 11) Determine the number of directions to be optimized for each intersection based on the intersection rating data in the internet data; if the intersection rating is D or E, the number of directions to be optimized is 2; if the intersection rating is C, the number of directions to be optimized is 1; if the intersection rating is A or B, the number of directions to be optimized is 0;

[0016] 12) Determine whether the intersection is a special point (including construction, accidents, etc.) or whether it is at a special time (including holidays, large-scale events, etc.). If so, change the number of directions to be optimized to 0 and proceed to step 13); if not, directly proceed to step 13);

[0017] 13) Based on the rating data of each direction of the intersection from the Internet data, sort the directions of the intersection according to the direction rating; considering the number of directions to be optimized at the intersection, select one or two directions with low ratings as the intersection directions to be optimized;

[0018] 14) Calculate the directional flow rate of the intersection based on the detector data, and use the green signal ratio to multiply the saturated flow rate to calculate the traffic capacity of the corresponding direction; if the ratio of directional flow rate to directional capacity is greater than 0.85, the intersection direction is deleted from the intersection direction to be optimized;

[0019] 15) Based on the detector data and in combination with the upstream and downstream road networks, the number of stops on the main road, main road travel speed, and free flow speed are calculated; road types are classified according to expressways, main roads, and secondary branches. When implementing the green wave plan, if the number of stops is less than 1, the travel speed on the expressway is greater than 55 km / h, the travel speed on the main road is greater than 40 km / h, the travel speed on the secondary branch is greater than 30 km / h, or the travel speed on the road is greater than 90% of the free flow speed, the intersection direction is removed from the list of intersection directions to be optimized; intersections with more than 0 directions to be optimized are counted and identified as problem intersections;

[0020] 16) Determine whether there is a long queue, excessive parking, or excessive delay in the direction of the intersection to be optimized. If so, start lane detection and go to step 2); if not, go to step 3).

[0021] Furthermore, the step 2) specifically includes:

[0022] 21) Calculate the standard deviation using the saturation to obtain the imbalance coefficient of the intersection. Determine whether the imbalance coefficient is less than 0.6. If so, proceed to step 22); if not, proceed to step 3). The formula for calculating the imbalance coefficient is as follows:

[0023]

[0024] Where δ is the imbalance coefficient, n is the number of entrance lanes at the intersection, and Y i is the saturation of import lane i, is the mean saturation value of each import lane;

[0025] 22) Calculate the recommended minimum green light time g′ for pedestrians based on the import lane data and the exit lane data min , the expression is as follows:

[0026]

[0027] Where lnum in is the number of import lanes, lnum out is the number of exit lanes, w i is the width of the i-th import lane, w j is the width of the j-th exit lane, v p is the pedestrian speed (w i 、w j The default value is 3.25m, v p The default value is 1.2m / s);

[0028] 23) Optimize the timing plan based on the minimum green light time and traffic ratio recommended by pedestrians.

[0029] Furthermore, the step 3) specifically includes:

[0030] 31) Determine whether there is overflow in the exit lane. If so, calculate the number of exit lanes and proceed to step 32); if not, directly proceed to step 32);

[0031] 32) Calculate the number of left-turn lanes, through-lanes, and right-turn lanes entering the exit lane based on lane attributes and channelization data, and save the maximum number of left-turn lanes, through-lanes, and right-turn lanes as the maximum number of entrance lanes in use at the same time;

[0032] 33) Determine whether the number of exit lanes is less than the maximum number of entry lanes in use at the same time. If so, there is a mismatch between the number of entry lanes and the number of exit lanes, and proceed to step 34); if not, proceed to step 4);

[0033] 34) Determine whether the manager agrees to widen the exit lane to determine the number of exit lanes. If so, add 1 to the number of exit lanes and proceed to step 4); if not, proceed directly to step 4).

[0034] Furthermore, the step 4) specifically includes:

[0035] 41) Based on the flow direction of the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of through-traffic vehicles in the queue is ≥ 3 and the number of through-traffic lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of a mismatch between the left-turn lane and the through-traffic lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane, and proceed to step 42). If not, proceed to step 5). The expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane is as follows:

[0036]

[0037] Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane;

[0038]

[0039] Where, is the average flow rate of a straight lane, lnum staraight is the current number of through lanes, v j is the flow rate of the j-th through lane;

[0040] 42) Calculate the average number of vehicles remaining in the left-turn queue and the average number of vehicles remaining in the straight-ahead queue when the lane attribute is changed from straight-ahead to left-turn. The expression is as follows:

[0041]

[0042] Where q′ left is the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane;

[0043]

[0044] Where q′ straight is the average number of remaining vehicles queuing for straight-going vehicles after adjustment, q j is the number of vehicles queuing in the j-th through lane;

[0045] 43) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the through lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current through lane If yes, it means that the left-turn traffic flow and the straight traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 44); if no, the process goes to step 5);

[0046] 44) Count the mismatches between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes for each cycle within 15 minutes, and determine whether the mismatch exists in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of through lanes by 1, and proceed to step 5); if not, proceed directly to step 5).

[0047] Furthermore, the step 5) specifically includes:

[0048] 51) According to the flow direction calculation at the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of right-turn vehicles in the queue is ≥ 3 and the number of right-turn lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of mismatch between the left-turn lane and the right-turn lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane, and proceed to step 52); if not, proceed to step 6); the expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane is as follows:

[0049]

[0050] Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane;

[0051]

[0052] Where, is the average flow rate of a right-turn single lane, lnum right is the current number of right-turn lanes, v k is the flow rate of the kth right-turn lane;

[0053] 52) Calculate the average number of left-turn vehicles remaining in the queue and the average number of right-turn vehicles remaining in the queue when the lane attribute is changed from right turn to left turn. The expression is as follows:

[0054]

[0055] Where q′ leftis the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane;

[0056]

[0057] Where q′ right is the average number of remaining right-turn vehicles in the queue after adjustment, q k is the number of vehicles queuing in the kth right-turn lane;

[0058] 53) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the right-turn lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current right-turn lane If the difference is yes, it means that the left-turn traffic flow and right-turn traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 54). If not, the process goes to step 6).

[0059] 54) Count the mismatches between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes for each cycle within 15 minutes, and determine whether mismatches exist in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of right-turn lanes by 1, and proceed to step 6); if not, proceed directly to step 6).

[0060] Furthermore, the step 6) specifically includes:

[0061] 61) Calculate the time difference Δt between the moment when the last vehicle passes through the mixed lane during the green light period of the current cycle and the moment when the green light ends green ,as follows:

[0062] Δt green =t greenend -t last

[0063] Where, t greenend is the green light end time, t last It is the moment when the last vehicle passes through the mixed lane during the green light period;

[0064] 62) Determine whether Δt exists green If the time is greater than 10 seconds and the number of vehicles in the mixed lane is greater than 3 when the green light ends, then it indicates that there is a mixed lane interference problem in the current cycle, and the process goes to step 63); if not, the process goes to step 7);

[0065] 63) Counting the mixed lane interference issues in each cycle within 15 minutes, determining whether interference issues exist in more than 60% of the cycles. If so, indicating that mixed lane interference issues exist at the intersection, the mixed lanes are split into single-attribute lanes and the process proceeds to step 64); if not, proceeding to step 7);

[0066] 64) Determine whether the manager agrees to widen the exit lane to determine the number of non-mixed lanes. If so, proceed to step 7); if not, subtract 1 from the number of non-mixed lanes and proceed to step 7).

[0067] Among them, the mixed lanes include: straight left lane, straight right lane, left straight right lane, left and right lanes.

[0068] Furthermore, the step 7) specifically includes:

[0069] 71) The remaining average number of vehicles in the queue after lane number adjustment is calculated based on lane attributes within 15 minutes. The expression is as follows:

[0070]

[0071] Where q′ dir is the average number of remaining queued vehicles in the lane with lane attribute dir after adjustment, q r,dir is the number of vehicles queuing in the rth lane with the attribute dir, is the average traffic volume of a single lane with lane attribute dir, lnum dir The number of lanes whose current lane attribute is dir;

[0072] The lane attributes dir include: left turn left, straight go straight, right turn right;

[0073] 72) Calculate the maximum value of each lane queue after adjustment according to the direction of the intersection, and determine whether the maximum value of the queue after the intersection direction adjustment is less than the maximum value of the queue before the adjustment. If so, then recommend adjustment. The expression for calculating the maximum value of the queue after the intersection direction adjustment is as follows:

[0074] q′ juncdir =max(q′ left ,q′ straight ,q′ right )

[0075] Where q′ juncdir is the maximum value of the queue after the intersection direction is adjusted, q′ left is the average number of remaining vehicles in the left-turn lane after adjustment, q′ straight is the average number of remaining vehicles in the through lane after adjustment, q′ right The average number of remaining vehicles in the queue in the right-turn lane after adjustment;

[0076] 73) For intersections with the same channelization adjustment plan in different time periods, adjustments shall be made according to the channelization adjustment plan. The problem period is the whole day. The lane problem is that the number of import lanes and export lanes corresponding to the channelization adjustment plan does not match, the left-turn and through traffic flow in the import lanes does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other; for intersections with different numbers of import lanes and export lanes in the channelization adjustment plan in different time periods, tidal lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the number of import lanes and export lanes does not match; for intersections with different attributes of import lanes in the channelization adjustment plan in different time periods, variable lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the left-turn and through traffic flow in the import lanes corresponding to the channelization adjustment plan does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other.

[0077] Beneficial effects of the present invention:

[0078] The present invention determines problem intersections and problem directions based on multiple types of data such as direction-level data, detector data, and green wave schemes in Internet data, and further diagnoses and discovers problems such as the matching of intersections with upstream and downstream, the matching of import lanes with export lanes, and the matching of different traffic flows in import lanes. An adjustment plan and the adjusted parameter changes are given to determine the modification plan. The method of the present invention optimizes lane settings by combining the road network and the green wave scheme, and integrates and applies various data sources at intersections. The lane problems discovered are more comprehensive, thereby improving the rationality of the optimization plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 This is a schematic diagram of the identification method of the present invention. DETAILED DESCRIPTION

[0080] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and drawings. The contents mentioned in the embodiments are not intended to limit the present invention.

[0081] Reference Figure 1 As shown, the lane problem identification method based on the fusion of Internet data and intersection detector of the present invention comprises the following steps:

[0082] 1) Based on the intersection rating data and intersection direction rating data from the internet, combined with detector data, the number of main road stops, main road travel speed, and free flow speed are calculated to identify problem intersections and intersection directions that need to be optimized. This includes:

[0083] 11) Determine the number of directions to be optimized for each intersection based on the intersection rating data in the internet data; if the intersection rating is D or E, the number of directions to be optimized is 2; if the intersection rating is C, the number of directions to be optimized is 1; if the intersection rating is A or B, the number of directions to be optimized is 0;

[0084] 12) Determine whether the intersection is a special point (including construction, accidents, etc.) or whether it is at a special time (including holidays, large-scale events, etc.). If so, change the number of directions to be optimized to 0 and proceed to step 13); if not, directly proceed to step 13);

[0085] 13) Based on the rating data of each direction of the intersection from the Internet data, sort the directions of the intersection according to the direction rating; considering the number of directions to be optimized at the intersection, select one or two directions with low ratings as the intersection directions to be optimized;

[0086] 14) Calculate the directional flow rate of the intersection based on the detector data, and use the green signal ratio to multiply the saturated flow rate to calculate the traffic capacity of the corresponding direction; if the ratio of directional flow rate to directional capacity is greater than 0.85, the intersection direction is deleted from the intersection direction to be optimized;

[0087] 15) Based on the detector data and in combination with the upstream and downstream road networks, the number of stops on the main road, main road travel speed, and free flow speed are calculated; road types are classified according to expressways, main roads, and secondary branches. When implementing the green wave plan, if the number of stops is less than 1, the travel speed on the expressway is greater than 55 km / h, the travel speed on the main road is greater than 40 km / h, the travel speed on the secondary branch is greater than 30 km / h, or the travel speed on the road is greater than 90% of the free flow speed, the intersection direction is removed from the list of intersection directions to be optimized; the number of intersections to be optimized is counted as greater than 0, and the problem intersections are obtained, where * is the multiplication sign;

[0088] 16) Determine whether there is a long queue, excessive parking, or excessive delay in the direction of the intersection to be optimized. If so, start lane detection and go to step 2); if not, go to step 3).

[0089] 2) Determine whether the imbalance coefficient of the intersection is less than a threshold. If so, calculate the minimum green light time recommended by pedestrians, and modify the timing plan based on the minimum green light time recommended by pedestrians and the traffic flow ratio to optimize and proceed to step 3). If not, directly proceed to step 3). Specifically, it includes:

[0090] 21) Calculate the standard deviation using the saturation to obtain the imbalance coefficient of the intersection. Determine whether the imbalance coefficient is less than 0.6. If so, proceed to step 22); if not, proceed to step 3). The formula for calculating the imbalance coefficient is as follows:

[0091]

[0092] Where δ is the imbalance coefficient, n is the number of entrance lanes at the intersection, and Y i is the saturation of import lane i, is the mean saturation value of each import lane;

[0093] 22) Calculate the recommended minimum green light time g′ for pedestrians based on the import lane data and the exit lane data min , the expression is as follows:

[0094]

[0095] Where lnum in is the number of import lanes, lnum out is the number of exit lanes, w i is the width of the i-th import lane, w j is the width of the j-th exit lane, v p is the pedestrian speed (w i 、w j The default value is 3.25m, v p The default value is 1.2m / s);

[0096] 23) Optimize the timing plan based on the minimum green light time and traffic ratio recommended by pedestrians.

[0097] 3) Determine whether the number of import lanes matches the number of export lanes. If so, proceed to step 4); if not, modify the lane attributes and proceed to step 4); specifically,

[0098] 31) Determine whether there is overflow in the exit lane. If so, calculate the number of exit lanes and proceed to step 32); if not, directly proceed to step 32);

[0099] 32) Calculate the number of left-turn lanes, through-lanes, and right-turn lanes entering the exit lane based on lane attributes and channelization data, and save the maximum number of left-turn lanes, through-lanes, and right-turn lanes as the maximum number of entrance lanes in use at the same time;

[0100] 33) Determine whether the number of exit lanes is less than the maximum number of entry lanes in use at the same time. If so, there is a mismatch between the number of entry lanes and the number of exit lanes, and proceed to step 34); if not, proceed to step 4);

[0101] 34) Determine whether the manager agrees to widen the exit lane to determine the number of exit lanes. If so, add 1 to the number of exit lanes and proceed to step 4); if not, proceed directly to step 4).

[0102] 4) Determine whether the left-turn traffic flow and the straight traffic flow in the import lane match the import lane attributes. If so, proceed to step 5); if not, modify the lane attributes and proceed to step 5); specifically, include:

[0103] 41) Based on the flow direction of the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of through-traffic vehicles in the queue is ≥ 3 and the number of through-traffic lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of a mismatch between the left-turn lane and the through-traffic lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane, and proceed to step 42). If not, proceed to step 5). The expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane is as follows:

[0104]

[0105] Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane;

[0106]

[0107] Where, is the average flow rate of a single lane going straight, lnum straight is the current number of through lanes, v j is the flow rate of the j-th through lane;

[0108] 42) Calculate the average number of vehicles remaining in the left-turn queue and the average number of vehicles remaining in the straight-ahead queue when the lane attribute is changed from straight-ahead to left-turn. The expression is as follows:

[0109]

[0110] Where q′ left is the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane;

[0111]

[0112] Where q′ straight is the average number of remaining vehicles queuing for straight-going vehicles after adjustment, q j is the number of vehicles queuing in the j-th through lane;

[0113] 43) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the through lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current through lane If yes, it means that the left-turn traffic flow and the straight traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 44); if no, the process goes to step 5);

[0114] 44) Count the mismatches between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes for each cycle within 15 minutes, and determine whether the mismatch exists in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of through lanes by 1, and proceed to step 5); if not, proceed directly to step 5).

[0115] 5) Determine whether the left-turn traffic flow and the right-turn traffic flow in the import lane match the import lane attributes. If so, proceed to step 6); if not, modify the lane attributes and proceed to step 6); specifically, include:

[0116] 51) According to the flow direction calculation at the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of right-turn vehicles in the queue is ≥ 3 and the number of right-turn lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of mismatch between the left-turn lane and the right-turn lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane, and proceed to step 52); if not, proceed to step 6); the expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane is as follows:

[0117]

[0118] Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane;

[0119]

[0120] Where, is the average flow rate of a right-turn single lane, lnum right is the current number of right-turn lanes, v k is the flow rate of the kth right-turn lane;

[0121] 52) Calculate the average number of left-turn vehicles remaining in the queue and the average number of right-turn vehicles remaining in the queue when the lane attribute is changed from right turn to left turn. The expression is as follows:

[0122]

[0123] Where q′ left is the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane;

[0124]

[0125] Where q′ right is the average number of vehicles remaining in the right-turn queue after adjustment, q k is the number of vehicles queuing in the kth right-turn lane;

[0126] 53) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the right-turn lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current right-turn lane If the difference is yes, it means that the left-turn traffic flow and the right-turn traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 54). If not, the process goes to step 6).

[0127] 54) Count the mismatches between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes for each cycle within 15 minutes, and determine whether mismatches exist in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of right-turn lanes by 1, and proceed to step 6); if not, proceed directly to step 6).

[0128] 6) Based on the traffic flow status after the green light ends, determine whether the mixed lane interference is greater than the threshold. If so, modify the lane attributes and proceed to step 7); if not, directly proceed to step 7); specifically including:

[0129] 61) Calculate the time difference Δt between the moment when the last vehicle passes through the mixed lane during the green light period of the current cycle and the moment when the green light ends green ,as follows:

[0130] Δt green =t greenend -t last

[0131] Where, t greenend is the green light end time, t last It is the moment when the last vehicle passes through the mixed lane during the green light period;

[0132] 62) Determine whether Δt exists green If the time is greater than 10 seconds and the number of vehicles in the mixed lane is greater than 3 when the green light ends, then it indicates that there is a mixed lane interference problem in the current cycle, and the process goes to step 63); if not, the process goes to step 7);

[0133] 63) Counting the mixed lane interference issues in each cycle within 15 minutes, determining whether interference issues exist in more than 60% of the cycles. If so, indicating that mixed lane interference issues exist at the intersection, the mixed lanes are split into single-attribute lanes and the process proceeds to step 64); if not, proceeding to step 7);

[0134] 64) Determine whether the manager agrees to widen the exit lane to determine the number of non-mixed lanes. If so, proceed to step 7); if not, subtract 1 from the number of non-mixed lanes and proceed to step 7).

[0135] Among them, the mixed lanes include: straight left lane, straight right lane, left straight right lane, left and right lanes.

[0136] 7) Calculate the expected queue after the number of lanes is adjusted, determine the lane adjustment plan, and thus identify any lane problems; specifically, include:

[0137] 71) The remaining average number of vehicles in the queue after lane number adjustment is calculated based on lane attributes within 15 minutes. The expression is as follows:

[0138]

[0139] Where q′ dir is the average number of remaining queued vehicles in the lane with lane attribute dir after adjustment, q r,dir is the number of vehicles queuing in the rth lane with the attribute dir, is the average traffic volume of a single lane with lane attribute dir, lnum dir The number of lanes whose current lane attribute is dir;

[0140] The lane attributes dir include: left turn left, straight go straight, right turn right;

[0141] 72) Calculate the maximum value of each lane queue after adjustment according to the direction of the intersection, and determine whether the maximum value of the queue after the intersection direction adjustment is less than the maximum value of the queue before the adjustment. If so, then recommend adjustment. The expression for calculating the maximum value of the queue after the intersection direction adjustment is as follows:

[0142] q′ juncdir =max(q′ left ,q′ straight ,q′ right )

[0143] Where q′ juncdir is the maximum value of the queue after the intersection direction is adjusted, q′ left is the average number of remaining vehicles in the left-turn lane after adjustment, q′ straight is the average number of remaining vehicles in the through lane after adjustment, q′right The average number of remaining vehicles in the queue in the right-turn lane after adjustment;

[0144] 73) For intersections with the same channelization adjustment plan in different time periods, adjustments shall be made according to the channelization adjustment plan. The problem period is the whole day. The lane problem is that the number of import lanes and export lanes corresponding to the channelization adjustment plan does not match, the left-turn and through traffic flow in the import lanes does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other; for intersections with different numbers of import lanes and export lanes in the channelization adjustment plan in different time periods, tidal lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the number of import lanes and export lanes does not match; for intersections with different attributes of import lanes in the channelization adjustment plan in different time periods, variable lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the left-turn and through traffic flow in the import lanes corresponding to the channelization adjustment plan does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other.

[0145] The present invention has many specific application paths. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principles of the present invention. These improvements should also be considered as the scope of protection of the present invention.

Claims

1. A lane problem identification method based on the fusion of Internet data and intersection detectors, characterized in that: Here are the steps: 1) Based on the intersection rating data and intersection direction rating data from the internet, combined with detector data, the number of main road stops, main road travel speed, and free flow speed are calculated to identify problem intersections and intersection directions that need to be optimized; 2) Determine whether the imbalance coefficient of the intersection is less than a threshold. If so, calculate the minimum green light time recommended by pedestrians, and modify the timing plan based on the minimum green light time recommended by pedestrians and the traffic flow ratio to optimize it, and proceed to step 3); if not, directly proceed to step 3); 3) Determine whether the number of import lanes matches the number of export lanes. If so, proceed to step 4); if not, modify the lane attributes and proceed to step 4); 4) Determine whether the left-turn traffic flow and the straight traffic flow in the import lane match the attributes of the import lane. If so, proceed to step 5); if not, modify the lane attributes and proceed to step 5); 5) Determine whether the left-turn traffic flow and the right-turn traffic flow in the import lane match the import lane attributes. If so, proceed to step 6); if not, modify the lane attributes and proceed to step 6); 6) Based on the traffic flow status after the green light ends, determine whether the mixed lane interference situation is greater than the threshold. If so, modify the lane attributes and proceed to step 7); if not, directly proceed to step 7); 7) Calculate the expected queue after the number of lanes is adjusted, determine the lane number adjustment plan, and thus identify the problems existing in the lanes.

2. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 1) specifically includes: 11) Determine the number of directions to be optimized for each intersection based on the intersection rating data in the internet data; if the intersection rating is D or E, the number of directions to be optimized is 2; if the intersection rating is C, the number of directions to be optimized is 1; if the intersection rating is A or B, the number of directions to be optimized is 0; 12) Determine whether the intersection is a special point or at a special time. If so, change the number of directions to be optimized to 0 and proceed to step 13); if not, proceed directly to step 13); 13) Based on the rating data of each direction of the intersection from the Internet data, sort the directions of the intersection according to the direction rating; considering the number of directions to be optimized at the intersection, select one or two directions with low ratings as the intersection directions to be optimized; 14) Calculate the directional flow rate of the intersection based on the detector data, and use the green signal ratio to multiply the saturated flow rate to calculate the traffic capacity of the corresponding direction; if the ratio of directional flow rate to directional capacity is greater than 0.85, the intersection direction is deleted from the intersection direction to be optimized; 15) Based on the detector data and in combination with the upstream and downstream road networks, the number of stops on the main road, main road travel speed, and free flow speed are calculated; road types are classified according to expressways, main roads, and secondary branches. When implementing the green wave plan, if the number of stops is less than 1, the travel speed on the expressway is greater than 55 km / h, the travel speed on the main road is greater than 40 km / h, the travel speed on the secondary branch is greater than 30 km / h, or the travel speed on the road is greater than 90% of the free flow speed, the intersection direction is removed from the list of intersection directions to be optimized; intersections with more than 0 directions to be optimized are counted and identified as problem intersections; 16) Determine whether there is a long queue, excessive parking, or excessive delay in the direction of the intersection to be optimized. If so, start lane detection and go to step 2); if not, go to step 3).

3. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 2) specifically includes: 21) Calculate the standard deviation using the saturation to obtain the imbalance coefficient of the intersection. Determine whether the imbalance coefficient is less than 0.

6. If so, proceed to step 22); if not, proceed to step 3). The formula for calculating the imbalance coefficient is as follows: Where δ is the imbalance coefficient, n is the number of entrance lanes at the intersection, and Y i is the saturation of import lane i, is the mean saturation value of each import lane; 22) Calculate the recommended minimum green light time g′ for pedestrians based on the import lane data and the exit lane data min , the expression is as follows: Where lnum in is the number of import lanes, lnum out is the number of exit lanes, w i is the width of the i-th import lane, w j is the width of the j-th exit lane, v p is the pedestrian walking speed; 23) Optimize the timing plan based on the minimum green light time and traffic ratio recommended by pedestrians.

4. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 3) specifically includes: 31) Determine whether there is overflow in the exit lane. If so, calculate the number of exit lanes and proceed to step 32); if not, directly proceed to step 32); 32) Calculate the number of left-turn lanes, through-lanes, and right-turn lanes entering the exit lane based on lane attributes and channelization data, and save the maximum number of left-turn lanes, through-lanes, and right-turn lanes as the maximum number of entrance lanes in use at the same time; 33) Determine whether the number of exit lanes is less than the maximum number of entry lanes in use at the same time. If so, there is a mismatch between the number of entry lanes and the number of exit lanes, and proceed to step 34); if not, proceed to step 4); 34) Determine whether the manager agrees to widen the exit lane to determine the number of exit lanes. If so, add 1 to the number of exit lanes and proceed to step 4); if not, proceed directly to step 4).

5. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 4) specifically includes: 41) Based on the flow direction of the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of through-traffic vehicles in the queue is ≥ 3 and the number of through-traffic lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of a mismatch between the left-turn lane and the through-traffic lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane, and proceed to step 42). If not, proceed to step 5). The expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single through-traffic lane is as follows: Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane; Where, is the average flow rate of a single lane going straight, lnum straight is the current number of through lanes, v j is the flow rate of the j-th through lane; 42) Calculate the average number of vehicles remaining in the left-turn queue and the average number of vehicles remaining in the straight-ahead queue when the lane attribute is changed from straight-ahead to left-turn. The expression is as follows: Where q′ left is the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane; Where q′ straight is the average number of remaining vehicles queuing for straight-going vehicles after adjustment, q j is the number of vehicles queuing in the j-th through lane; 43) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the through lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current through lane If yes, it means that the left-turn traffic flow and the straight traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 44); if no, the process goes to step 5); 44) Count the mismatches between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes for each cycle within 15 minutes, and determine whether the mismatch exists in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn traffic flow and the through-traffic flow in the import lane and the import lane attributes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of through lanes by 1, and proceed to step 5); if not, proceed directly to step 5).

6. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 5) specifically includes: 51) According to the flow direction calculation at the intersection, determine whether the average number of left-turn vehicles in the queue at the end of the green light minus the average number of right-turn vehicles in the queue is ≥ 3 and the number of right-turn lanes is ≥ 2 in the current cycle. If so, it indicates that there is a possibility of mismatch between the left-turn lane and the right-turn lane. Calculate the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane, and proceed to step 52); if not, proceed to step 6); the expression for calculating the average flow rate of a single left-turn lane and the average flow rate of a single right-turn lane is as follows: Where, is the average flow rate of a left-turn single lane, lnum left is the current number of left-turn lanes, v i is the flow rate of the i-th left-turn lane; Where, is the average flow rate of a right-turn single lane, lnum right is the current number of right-turn lanes, v k is the flow rate of the kth right-turn lane; 52) Calculate the average number of left-turn vehicles remaining in the queue and the average number of right-turn vehicles remaining in the queue when the lane attribute is changed from right turn to left turn. The expression is as follows: Where q′ left is the average number of vehicles remaining in the left-turn queue after adjustment, q i is the number of vehicles queuing in the i-th left-turn lane; Where q′ right is the average number of remaining right-turn vehicles in the queue after adjustment, q k is the number of vehicles queuing in the kth right-turn lane; 53) Determine whether the absolute value of the difference between the number of vehicles queued in the left-turn lane and the right-turn lane after adjustment is less than the current average number of vehicles queued in the left-turn lane Average number of vehicles queuing in the current right-turn lane If the difference is yes, it means that the left-turn traffic flow and right-turn traffic flow in the import lane in the current cycle do not match the import lane attributes, and the process goes to step 54). If not, the process goes to step 6). 54) Count the mismatches between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes for each cycle within 15 minutes, and determine whether mismatches exist in more than 60% of the cycles. If so, it indicates that there is a mismatch between the left-turn and right-turn traffic flows in the import lanes and the attributes of the import lanes in the direction of the intersection. Increase the number of left-turn lanes by 1, decrease the number of right-turn lanes by 1, and proceed to step 6); if not, proceed directly to step 6).

7. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 6) specifically includes: 61) Calculate the time difference Δt between the moment when the last vehicle passes through the mixed lane during the green light period of the current cycle and the moment when the green light ends green ,as follows: Δt green =t greenend -t last Where, t greenend is the green light end time, t last It is the moment when the last vehicle passes through the mixed lane during the green light period; 62) Determine whether Δt exists green If the time is greater than 10 seconds and the number of vehicles in the mixed lane is greater than 3 when the green light ends, then it indicates that there is a mixed lane interference problem in the current cycle, and the process goes to step 63); if not, the process goes to step 7); 63) Counting the mixed lane interference issues in each cycle within 15 minutes, determining whether interference issues exist in more than 60% of the cycles. If so, indicating that mixed lane interference issues exist at the intersection, the mixed lanes are split into single-attribute lanes and the process proceeds to step 64); if not, proceeding to step 7); 64) Determine whether the manager agrees to widen the exit lane to determine the number of non-mixed lanes. If so, proceed to step 7); if not, subtract 1 from the number of non-mixed lanes and proceed to step 7).

8. The lane problem identification method based on the fusion of Internet data and intersection detector according to claim 1 is characterized in that: The step 7) specifically includes: 71) The remaining average number of vehicles in the queue after lane number adjustment is calculated based on lane attributes within 15 minutes. The expression is as follows: Where q′ dir is the average number of remaining queued vehicles in the lane with lane attribute dir after adjustment, q r,dir is the number of vehicles queuing in the rth lane with the attribute dir, is the average traffic volume of a single lane with lane attribute dir, lnum dir The number of lanes whose current lane attribute is dir; The lane attributes dir include: left turn left, straight go straight, right turn right; 72) Calculate the maximum value of each lane queue after adjustment according to the direction of the intersection, and determine whether the maximum value of the queue after the intersection direction adjustment is less than the maximum value of the queue before the adjustment. If so, then recommend adjustment. The expression for calculating the maximum value of the queue after the intersection direction adjustment is as follows: q′ juncdir =max(q′ left ,q′ straight ,q′ right ) Where q′ juncdir is the maximum value of the queue after the intersection direction is adjusted, q′ left is the average number of remaining vehicles in the left-turn lane after adjustment, q′ straight is the average number of remaining vehicles in the through lane after adjustment, q′ right The average number of remaining vehicles in the queue in the right-turn lane after adjustment; 73) For intersections with the same channelization adjustment plan in different time periods, adjustments shall be made according to the channelization adjustment plan. The problem period is the whole day. The lane problem is that the number of import lanes and export lanes corresponding to the channelization adjustment plan does not match, the left-turn and through traffic flow in the import lanes does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other; for intersections with different numbers of import lanes and export lanes in the channelization adjustment plan in different time periods, tidal lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the number of import lanes and export lanes does not match; for intersections with different attributes of import lanes in the channelization adjustment plan in different time periods, variable lanes shall be set. The problem period is the period of the channelization adjustment plan. The lane problem is that the left-turn and through traffic flow in the import lanes corresponding to the channelization adjustment plan does not match the attributes of the import lanes, the left-turn and right-turn traffic flow in the import lanes does not match the attributes of the import lanes, or the mixed lanes interfere with each other.

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