Dynamic timing method for single-lane alternating traffic signal of partial section of two-lane highway

Abstract

The application discloses a double-lane highway local section single-lane alternate traffic signal dynamic timing method, which comprises the following steps: determining the local section traffic influence range of an event; collecting traffic flow data and analyzing traffic flow characteristics; calculating the equivalent amount of small vehicles based on delay and the adverse influence factor of large vehicles; and constructing a signal dynamic timing method for the alternate traffic of the event influence section of the double-lane highway. The application constructs a signal timing optimization model based on dynamic traffic flow characteristics, collects the traffic flow data of the event influence section in real time, including the actual traffic time, the vehicle type ratio and the actual arrival traffic volume, dynamically adjusts the signal cycle and the phase timing scheme, and is suitable for the special scene of the double-lane highway alternate traffic section. The method can quickly adapt to the traffic fluctuation of the alternate traffic section, reduces the vehicle delay under manual command, improves the vehicle traffic efficiency, and enhances the flexibility and dynamic adaptability of the signal timing of the double-lane highway alternate traffic section.

Description

Technical Field

[0001] This invention relates to the field of dynamic traffic signal timing technology, specifically to a dynamic timing method for alternating single-lane traffic signals on a partial section of a two-lane highway. Background Technology

[0002] Two-lane highways, as vital transportation infrastructure connecting urban and rural areas, often face severe traffic obstacles under specific geographical and natural conditions. In actual engineering projects, several high-risk scenarios exist that significantly reduce road capacity. For example, when a single-sided landslide occurs in a cut section or on the excavated side of a semi-cut / fill section, the large volume of the landslide makes timely reinforcement and removal impossible, directly impacting normal traffic flow. Secondly, embankment sections or semi-cut / fill sections may experience single-sided landslides or water damage, requiring road closures for construction. The extensive construction area and long repair time also severely restrict road capacity. These typical scenarios are particularly prevalent in remote and rural areas, where the road network consists mostly of national and provincial highways with a high proportion of curves. Narrow road sections often exhibit two characteristics: firstly, they are relatively long; secondly, although short, they have limited visibility. Therefore, traffic management is necessary to ensure road efficiency and traffic safety.

[0003] Currently, traffic control on one-way sections of two-lane highways primarily relies on traditional manual control. This involves stationing traffic controllers at both ends of narrow sections to direct traffic based on the situation. However, this approach has significant shortcomings. Firstly, traditional manual control relies heavily on experience, resulting in arbitrary and inefficient traffic flow organization, leading to long average vehicle delays and low overall traffic efficiency. Secondly, this method requires substantial human resources, resulting in high costs and potential safety hazards. Furthermore, manual control struggles to respond promptly to dynamically changing traffic flow characteristics and lacks adaptability to the differences between various vehicle types (such as trucks and cars), further limiting the traffic efficiency of typical two-lane highway scenarios.

[0004] Existing traffic signal timing schemes, especially those using the stop line method to calculate capacity at traditional intersections, are ill-suited to one-way traffic scenarios on two-lane highways with long or short-distance parallax. On one hand, alternating traffic on two-lane highways typically requires a long clearing time (yellow light duration), which in some extreme cases can exceed 50% of the entire cycle, significantly reducing capacity. On the other hand, alternating traffic sections exhibit typical single-lane convoy characteristics, with narrow roads and poor road conditions, resulting in significant differences in speed and traffic flow compared to normal road sections. Furthermore, different vehicle types exhibit significant differences in their performance on alternating traffic sections (e.g., start time, passage time, and speed for large and small vehicles), impacting the saturation flow of different approach lanes to varying degrees. This necessitates precise calibration of traffic control schemes based on actual traffic conditions. Simultaneously, the traffic volume characteristics of two-lane highways vary considerably across different time periods, requiring signal timing schemes to consider real-time performance and possess dynamic adaptability.

[0005] Patent CN201910603409.5, entitled "A Signal Timing Optimization Method for Intersections with Construction Zones," proposes a signal timing optimization model for intersections with construction zones. This model, based on the classic car-following model, introduces multiple parameters such as speed difference to calculate the saturation flow rate of island-type construction zones, the release rate state changes of each approach lane, and phase clearing time. Finally, it establishes an objective function and calculates the optimal solution as the signal timing for intersections with construction zones. However, this patent primarily targets island-type construction zone intersections, and the core optimization lies in the signal control of the approach and exit lanes. Typical two-lane scenarios usually do not involve complex signal interactions between multiple approach or exit lanes; instead, they require optimization of dynamic signal control for alternating release in a single direction. Furthermore, the calculation of saturation flow rate and clearing time is based on fixed geometric parameters and traffic flow characteristics, lacking the ability to dynamically adjust to real-time traffic conditions.

[0006] The patent CN202110461029.6, entitled "Traffic Control and Guidance Method for Construction Areas Based on Short-Term Dynamic Traffic Flow Prediction," utilizes a neural network model to construct a short-term traffic flow prediction model for key points of spatiotemporal traffic convergence. By acquiring real-time traffic information during the construction period, it analyzes the road service level load and formulates diversion schemes to alleviate road congestion. However, its focus is on the overall traffic control of the road network surrounding the construction area, addressing traffic distribution and guidance rather than specific signal control for alternating single-lane traffic. Furthermore, the model is highly complex and has limited applicability.

[0007] Patent CN109935092A, entitled "Adaptive Traffic Light Control System for Single-Lane Two-Way Traffic," proposes an adaptive traffic light control system suitable for single-lane two-way traffic in construction areas. It uses vehicle detectors to sense the queue length and arrival status of vehicles at both ends in real time and dynamically adjusts the traffic light timing using an adaptive algorithm. However, this patent primarily targets short-distance single-lane two-way traffic control in construction areas, failing to consider situations with long narrow road sections or limited visibility. Furthermore, it insufficiently considers differences in vehicle types (such as large vehicles versus small vehicles) and dynamic traffic flow characteristics (such as passing speed).

[0008] The paper, "Signal Control Method and Simulation Study for Two-Way Two-Lane Construction Zones," addresses the bottleneck and reduced traffic capacity issues caused by the closure of two-way two-lane highway construction sections by proposing a strategy of adding signal control. However, this patent utilizes Vissim simulation software to adjust different parameters, and the signal control model, based on preset parameter settings, lacks the ability to dynamically adjust to real-time traffic conditions. Furthermore, the paper assumes that the average speed passing through the construction zone is the same and that the saturation flow rate of different approach lanes is the same. However, in real-world scenarios, the passing speeds of different vehicle types vary significantly, and the saturation flow rate differs under different disaster scenarios.

[0009] Current research on traffic strategies for two-lane highway sections affected by disasters and road construction still has the following shortcomings:

[0010] (1) Currently, the main method for maintaining one-way traffic flow in two-lane highways affected by incidents is through manual traffic control. This method is highly arbitrary and slow in response, resulting in long average vehicle delay times and low overall traffic efficiency. In addition, existing technologies or models are mainly based on signal optimization or traffic control models for multi-lane roads, urban roads, or highway construction areas. Their effectiveness and applicability under two-lane conditions have been rarely verified, and the applicability of the models is limited.

[0011] (2) Current signal timing models are mostly based on the stop line method to calculate saturation flow rate, assuming that vehicles continue to accelerate after crossing the stop line. However, in the typical scenario of this invention, vehicles in alternating traffic sections exhibit obvious single-lane convoy characteristics, and due to poor road conditions, the speed differences between vehicles when passing through alternating traffic sections are large. Existing models are difficult to apply to long-distance one-way traffic scenarios.

[0012] (3) Many models employ complex traffic flow prediction methods (such as neural networks and genetic algorithms), relying on large amounts of historical and real-time data processing, which increases the difficulty of applying the strategies in emergency situations, especially on mountainous two-lane highways where data is limited or real-time requirements are high, making it difficult to meet the needs of rapid response. At the same time, the lack of comprehensive consideration of factors such as the start time, passing speed, and traffic volume differences of different vehicle types (such as trucks and cars) makes it difficult to meet the variable traffic demands in typical two-lane highway scenarios.

[0013] Therefore, a scientific and efficient signal timing method is urgently needed to address the issue of alternating traffic on narrow sections of two-lane highways during disasters, construction, planned traffic control, or other special scenarios. This method should dynamically adapt to actual traffic conditions, improve traffic efficiency, and ensure traffic safety. This invention addresses this need by proposing a dynamic signal timing method for alternating traffic on single lanes in local sections of two-lane highways. Through reasonable data collection and a scientific timing model, it achieves dynamic organization of traffic flow on narrow sections of two-lane highways, overcoming the shortcomings of existing technologies. Summary of the Invention

[0014] To address the problems of low efficiency in manual control, inapplicability of existing signal timing models, and insufficient dynamic adaptability in traffic strategies for two-lane highways under typical scenarios, this invention proposes a dynamic signal timing method specifically applicable to alternating traffic in local sections of two-lane highways. This method involves real-time collection of traffic flow data through a system-deployed data acquisition system, comprehensively considering differences in saturation flow rates at different approach lanes, and variations in start-up time, passing speed, and delays between large and small vehicles. The method dynamically calculates alternating traffic signal timing schemes to optimize traffic flow in local sections of two-lane highways under the influence of events, achieving safe and efficient alternating traffic for vehicles.

[0015] To solve the above-mentioned technical problems, the technical solution provided by the present invention is: a dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway, comprising the following steps:

[0016] (1) Obtain the event attribute characteristics of the affected local road sections and the basic information of the road sections where the event occurred, and determine the traffic impact range of the local road sections of the event;

[0017] (2) Deploy traffic flow collection equipment to collect traffic flow data of alternating traffic on local road sections under the influence of the event, and analyze the traffic flow characteristics of the alternating traffic sections;

[0018] (3) Using measured traffic flow data, calculate the average delay under the scenario of all small cars and the scenario of large cars mixed in based on SUMO simulation results. Calculate the equivalent quantity of small cars based on the delay difference between the two scenarios. Construct a prediction model of the equivalent quantity of small cars based on the large car mixing rate and the total traffic flow. Calculate the adverse impact factor of large cars based on the delay ratio.

[0019] (4) Observe the actual travel time of the convoy on the alternating traffic section, correct the saturation flow of different entrance lanes, and construct a dynamic signal timing method for alternating traffic on the two-lane highway affected by the event.

[0020] Preferably, step (1) specifically includes:

[0021] (1.1) Obtaining event attribute characteristics: Obtain the event type, location, duration, and length L0 of the road segment occupied by the event through on-site traffic survey;

[0022] (1.2) Collect basic information on the road section where the incident occurred: obtain the number of lanes, lane width, road design speed and road design capacity of the road section where the incident occurred through on-site traffic survey;

[0023] (1.3) Determine the traffic impact range L of the alternating traffic sections of the event. d .

[0024] Preferably, in step (1.3), L d The method for determining [the value] specifically includes the following steps:

[0025] (1.3.1) According to the provisions of the Highway Maintenance Safety Operation Procedures (JTG H30-2015), during construction, personnel should be set up at the upstream and downstream of L1 outside the work area, and warning signs should be set up on both sides of the affected road section. The distance between the signs should be determined according to the Highway Maintenance Safety Operation Procedures (JTG H30-2015).

[0026] (1.3.2) An additional length L2, determined based on the actual staff placement needs, road visibility conditions, safety and other factors of the alternating traffic sections, is used to ensure the staff's operating space and the safety and smoothness of traffic flow;

[0027] (1.3.3) The traffic impact range of the alternating traffic section under the influence of the event is defined as Ld:

[0028] Ld = L0 + 2L1 + 2L2.

[0029] Preferably, the method for determining L2 in step (1.3.2) specifically includes the following:

[0030] (1.3.2.1) Based on the operational needs of staff and the requirements for equipment placement, a temporary work area shall be designated within the available area of ​​the alternating traffic section. The length of the temporary work area shall be L. S ;

[0031] (1.3.2.2) To ensure that drivers can clearly see the work area and warning signs before entering the alternating traffic section, the visibility distance should meet the following formula:

[0032]

[0033] In the formula, L v It is the minimum sight distance in meters (m), V is the design speed in kilometers per hour (km / h), and T is the minimum sight distance in kilometers (m). r This refers to the driver's reaction time, typically taken as 2.5 seconds; the additional length for curved road sections is taken as 15-30 meters.

[0034] (1.3.2.3) Calculate the additional length of a single-lane alternating traffic section on a two-lane highway using the following formula:

[0035] L2 = L S +L V ;

[0036] Preferably, step (2) specifically includes:

[0037] (2.1) Deploy traffic flow data collection equipment: Deploy MetroCount traffic flow detectors at the free-flow and controlled sections of different entrances outside the traffic impact range of the alternating traffic sections; deploy drones over the midstream road sections affected by the event;

[0038] (2.2) Traffic characteristic parameters, including vehicle entry or exit time, vehicle type information, and speed, are collected by installing cross-sectional traffic flow detectors at different entrance lanes of the affected road section.

[0039] (2.3) Based on the time difference between the free-flow section and the control section of different entrances, the arrival traffic volume is statistically determined;

[0040] (2.4) Video data of the affected road section was collected by drones deployed in the middle of the affected road section, and three types of traffic flow characteristic parameters, namely, passing speed, acceleration and start time, were extracted by video analysis tools.

[0041] Preferably, step (3) specifically includes:

[0042] (3.1) Based on the collected traffic flow data, a simulation scenario of the impact of a two-lane highway event was constructed using SUMO simulation software. The collected traffic flow consisted entirely of small cars, and the average delay value of the small cars was calculated:

[0043]

[0044] In the formula, i = 1 and 2 represent different inlet channels, i = 1 represents the upstream inlet channel, and i = 2 represents the downstream inlet channel; d i,0 Q represents the average delay for each small car on different entry lanes. i,0 This represents the total traffic volume when all the entrance lanes are composed of small cars, expressed in vehicles per hour. (D) i,0Total delays when all imported vehicles are small cars;

[0045] (3.2) Based on the total delay collected under the scenario of large vehicles mixed in, calculate the average delay under the scenario of trucks mixed in:

[0046]

[0047] In the formula, d i,t For the average delay of large vehicles entering the scene from different import lanes, Q i,t D represents the total flow of large vehicles at different entrances, expressed in vehicles per hour. i,t Total delays caused by large vehicles from different import lanes mixing in;

[0048] (3.3) Calculate the mixing rate of large vehicles:

[0049]

[0050] In the formula, p i,H Q represents the mixing rate of large vehicles from different import lanes. i,t The total flow of large vehicles at different entrance lanes is expressed in vehicles per hour, and Qi is the total flow of large vehicles at different entrance lanes, also expressed in vehicles per hour.

[0051] (3.4) Considering the impact of large vehicles on the travel delay of a two-lane highway, calculate the equivalent quantity D_SVE of small vehicles based on the delay:

[0052]

[0053] (3.5) Based on the calculated D_SVE value, establish a relationship model between the equivalent quantity D_SVE of small vehicles and the mixing rate and total flow of large vehicles;

[0054]

[0055] In the formula, α i β is the coefficient for the mixing rate of large vehicles in different import lanes. i A coefficient representing the total flow rate at different inlets;

[0056] (3.6) The equivalent prediction model for small vehicles considering the delay of large vehicles is as follows:

[0057]

[0058] (3.7) The method for calculating the adverse impact factor of large vehicles on road sections affected by two-lane highway incidents is as follows:

[0059]

[0060] In the formula, p i,H D_SVE represents the mixing rate of large vehicles from different import lanes.i D_SVE is the equivalent value for small cars with different entry lanes;

[0061] Preferably, step (4) specifically includes:

[0062] (4.1) Calculate the phase clearing time of the affected road segment in a two-lane highway event;

[0063]

[0064] In the formula, L d p is the length of the traffic impact zone of an incident on a two-lane highway. i,H To account for the mixing rate of large vehicles from different import lanes, v i,H v represents the average passing speed of large vehicles in different entrance lanes. i,C The average passing speed of small cars in different entrance lanes;

[0065] (4.2) Considering the differences in start-up time and passage through event segments between large and small vehicles, calculate the total lost time W per signal cycle for the affected road segment of the two-lane highway event;

[0066]

[0067] In the formula, t T For the start-up time of large vehicles; t C For the start-up time of a small car, t i,AR The duration of full red for each phase of the road segment affected by events at different approach lanes;

[0068] (4.3) Based on the times when the last vehicle of the convoy enters and leaves the alternating traffic segment for 10-15 cycles collected by the cross-sectional traffic detector, the actual travel time of the convoy in the alternating traffic segment is obtained, and the 85th percentile value is used as the actual travel time Tc of the alternating traffic segment; the saturation flow of different entrance lanes of the alternating traffic segment is corrected by the actual travel time Tc, and the maximum value of the corrected saturation flow of different entrance lanes is taken as the final result; the calculation formula is as follows:

[0069]

[0070] In the formula, N i,c T represents the total number of vehicles at each entrance lane. i,c The actual observed convoy passage time at each entrance lane;

[0071] (4.4) Considering the impact of large vehicle delays, the arrival flow of different entrance lanes is corrected by the adverse impact factor of large vehicles, and the sum of the maximum flow ratios of each signal phase is calculated.

[0072]

[0073] In the formula, qi,c q represents the actual traffic volume of small vehicles at different entrances. i,t f represents the actual traffic volume of large vehicles at different entrance lanes. i,HV C is an adverse influencing factor for large vehicles. i,s Corrected saturation flow rates for different inlet channels;

[0074] (4.5) Calculate the optimal signal cycle for the affected road segment of a two-lane highway event:

[0075]

[0076] In the formula, W is the total loss time per cycle, and Y is the sum of the maximum flow ratios of each signal phase;

[0077] (4.6) Calculate the green light display time g for each phase. i,e ′.

[0078] (4.7) Calculate the red light duration for each phase:

[0079] R i,e =Tg i,e ′

[0080] In summary, the signal period duration T and the green light duration g for each phase are obtained. i,e and the duration of the red light (R) i,e Together, they constitute the signal timing scheme for the affected road sections of a two-lane highway incident.

[0081] Preferably, step (4.6) displays the green light time g. i,e The calculation method for ′ includes:

[0082] (4.6.1) Calculate the total effective green light time:

[0083] G e =T-2W

[0084] (4.6.2) Calculate the effective green time for each phase:

[0085]

[0086] (4.6.3) Calculate the green light display time for each phase:

[0087] g i,e ′=g i,e +t T +t C

[0088] In the formula, G e g represents the total effective green time per cycle. i,e g represents the effective green time for each phase. i,e′ represents the green light duration for each phase, and Y represents the sum of the maximum flow ratios of all signal phases constituting the cycle. y i The maximum flow ratio for phase i.

[0089] The advantages of this invention compared to the prior art are:

[0090] 1. This invention constructs a signal timing optimization model based on dynamic traffic flow characteristics. For the special scenario of alternating traffic sections on two-lane highways, it collects real-time traffic flow data of the affected sections, including actual travel time, vehicle type ratio, and actual arrival traffic volume, and dynamically adjusts the signal cycle and phase timing scheme. This method can quickly adapt to traffic fluctuations in alternating traffic sections, reduce vehicle delays under manual control, improve vehicle throughput, and enhance the flexibility and dynamic adaptability of signal timing in alternating traffic sections on two-lane highways.

[0091] 2. This invention considers the distance for sign placement, the operational needs of staff, the additional length for equipment installation, and the minimum line-of-sight to determine the traffic impact range of alternating traffic sections. It employs drones and cross-sectional sensors to comprehensively collect traffic flow characteristics of alternating traffic sections, accurately corrects the saturation flow of the approach lanes of these sections using the observation data, and calculates phase clearing times based on dynamic traffic flow characteristics, making signal timing more aligned with actual needs. Through dynamic signal control, it effectively solves the traffic management problem of alternating traffic under complex conditions such as limited visibility or long road sections.

[0092] 3. In view of the significant impact of large vehicles on traffic delays in alternating traffic sections of two-lane highways, this invention proposes a prediction model of the equivalent quantity of small vehicles based on delays, and introduces a dynamic correction signal timing scheme based on the adverse impact factors of large vehicles. This can effectively reduce the impact of large vehicle delays on overall traffic efficiency and improve the overall traffic flow in alternating traffic sections during the event.

[0093] 4. This invention employs real-time traffic data acquisition technology, combined with a dynamic signal timing optimization model, enabling rapid response to the impact of events on alternating traffic sections without relying on large amounts of historical data. This technology is particularly suitable for disaster scenarios on two-lane highways with sparse data and significant traffic flow fluctuations, providing efficient and reliable technical support for traffic management on complex and ever-changing road sections. Attached Figure Description

[0094] Figure 1 A dynamic timing method for alternating traffic signals in single lanes on local sections of a two-lane highway.

[0095] Figure 2 This is a diagram illustrating the alternating traffic flow in a single lane on a localized section of the road affected by a two-lane incident.

[0096] Figure 3This is a schematic diagram showing the deployment of data acquisition equipment for a dynamic timing scheme of alternating traffic signals for single lanes on a section of a two-lane highway.

[0097] Figure 4 Traffic volume statistics for different entrances to the affected sections of the Sichuan-Tibet G318 highway;

[0098] Figure 5 This is a composite diagram showing the sections of the Sichuan-Tibet G318 highway affected by the disaster.

[0099] Figure 6 This is a schematic diagram of the alternating traffic signal timing for one-way traffic on a two-lane highway affected by an incident. Detailed Implementation

[0100] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0101] Example:

[0102] This invention provides a dynamic timing method for alternating traffic signals in single lanes on partial sections of a two-lane highway, such as... Figure 1 As shown, this modeling method includes the following steps:

[0103] Step (1) Obtain the event attribute characteristics of the affected local road segment and the basic information of the road segment where the event occurred, and determine the traffic impact range of the local road segment of the event;

[0104] (1.1) Obtaining event attribute characteristics: Obtain the disaster event type, location, duration, and length L0 of the road segment occupied by the disaster event through on-site traffic survey;

[0105] The road network in Tibet mainly consists of national highways, provincial highways, and county roads. Due to geographical constraints and limited economic development, road infrastructure development has lagged behind. Furthermore, influenced by topographical and geological conditions, Tibet experiences frequent geological disasters, including landslides, floods, mudslides, and rockfalls. Therefore, this study focuses on the road network in Tibet, where two-lane highways constitute a significant proportion and disasters are frequent. Specifically, it analyzes a disaster-affected point on the Baxu-Bomi section of the G318 Sichuan-Tibet Highway as an example. Further, the characteristics of the disaster events observed during the field investigation are shown in Table 1.

[0106] Table 1. Characteristics of Disaster Events Found in On-site Investigations

[0107] Disaster event category Occurrence location Disaster event duration Disaster event section length L0 Large landslide Nearby No. 1 open cut tunnel of Niutuogou on Sichuan-Tibet Highway G318 4 months 1230m

[0108] (1.2) Collection of basic information on the road section where the incident occurred: The number of lanes, lane width, design speed, and design capacity of the road section where the incident occurred were obtained through on-site traffic surveys. Furthermore, the on-site investigation revealed a large-scale landslide geological disaster on the Basu-Bomi section of the G318 Sichuan-Tibet Highway. Basic information on the road section where the incident occurred is shown in Table 2.

[0109] Table 2 Basic Information on the Road Section Where the Incident Occurred

[0110] Number of lanes Lane width Number of occupied lanes Road design speed (km / h) Road design capacity (vehicles / hour / lane) 2 3.75m 1 40 1000

[0111] (1.3) Determine the traffic impact range Ld of the disaster event, including the following steps:

[0112] (1.3.1) Determine the marker placement distance L1:

[0113] According to the "Safety Operation Procedures for Highway Maintenance" (JTGH30-2015), the road construction and maintenance area consists of four sections: warning area → upstream transition area → work area → downstream transition area. Figure 2 As shown.

[0114] Secondly, the investigation revealed that in this embodiment, one traffic control personnel was stationed 5 meters upstream and downstream of the disaster event area, and cones were used to temporarily close the two-lane highway. Speed ​​limit signs of 20 km / h were also set up on both sides of the disaster event affected area. Therefore, L1 = 5m.

[0115] (1.3.2) Based on the actual staff placement needs, road visibility conditions, safety, and other factors of the alternating traffic section, the additional length L2 of the work area for the alternating traffic section is determined:

[0116] (1.3.2.1) According to the on-site survey, based on the operational needs of the staff and the equipment placement requirements for the construction and renovation of the No. 1 Mingdong Tunnel of Basu-Bomi Niutagou on G318, a temporary work area was delineated in the available area of ​​the alternating traffic section, with a length of Ls = 55m.

[0117] (1.3.2.2) To ensure that drivers can clearly see the work area and warning signs before entering the alternating traffic section, the minimum visibility distance for the G318 Basu-Bomi alternating traffic section is:

[0118]

[0119] (1.3.2.3) Finally, the traffic impact range of this disaster event was determined to be L. d :

[0120] L d =L0+2L1+2L2=1230+2*5+2*(55+28)=1406m.

[0121] Step (2) Deploy traffic flow acquisition equipment to collect traffic flow data of alternating traffic on local road sections under the influence of the event, and analyze the traffic flow characteristics of the alternating traffic sections;

[0122] (2.1) Deploy traffic flow data collection equipment: Deploy MetroCount traffic flow detectors at the free-flow sections and control sections of different entrances outside the traffic impact range of alternating traffic sections; deploy drones over the midstream road sections affected by disaster events;

[0123] (2.2) Traffic characteristic parameters, including vehicle entry or exit time, vehicle type information, and speed, are collected by installing cross-sectional traffic flow detectors at different entrance lanes of the affected road section.

[0124] (2.3) Based on the time difference between the free-flow section and the control section of different entrances, the arrival traffic volume is statistically determined;

[0125] First, referring to the vehicle dimensions in the "Technical Standards for Highway Engineering" (JTGBO1-2014), vehicles with a total length of 6m or more are classified as large vehicles, and vehicles with a total length of less than 6m are classified as small vehicles; the vehicle classification standards are shown in Table 3.

[0126] Table 3 Classification Standards for Different Vehicle Models

[0127] Vehicle type Vehicle type classification standard Small vehicle Vehicle total length ≥ 6 m Large vehicle Vehicle total length < 6 m

[0128] Secondly, using traffic flow data collected by MetroCount, the number of vehicles passing through two sections of the event-affected area—the Basu free-flow end (traffic flow sensor #1) and the Basu control end (traffic flow sensor #2)—was extracted from the data for each time period. This yielded the actual arrival traffic volume information for the Basu entrance at each time interval, as follows: Figure 4 As shown; similarly, based on the number of vehicles at the two sections of Bomi free-flow end (traffic flow sensor #3) and Bomi control end (traffic flow sensor #4), the actual arrival traffic volume at the Bomi entrance at each time interval is obtained.

[0129] (2.4) Video data of the affected road sections are collected by drones deployed in the middle reaches of the road sections affected by the disaster, and traffic flow characteristic parameters such as passing speed, acceleration, and start time are extracted by video analysis tools;

[0130] First, because the affected road section was quite long, a single drone flight could not cover it completely. Therefore, a segmented overlapping photography method was used to collect data on the entire affected road section. The drone took photos in segments along its flight path to ensure appropriate overlap between adjacent photos. Significant landmarks or structural features of the affected road section, such as curbs, markers, or construction equipment, were marked in the collected photos as reference points for stitching. Image processing software was used to stitch the overlapping photos according to key feature points, forming a continuous image of the affected road section. The stitched image of the Niutagou No. 1 Excavation Site affected by the disaster is shown below. Figure 5 As shown.

[0131] Then, the video trajectory extraction software DataFromSky was used to automatically identify and track the vehicle's movement trajectory. The data revealed that the average speed of large vehicles in the disaster-affected area was 10 km / h, and their acceleration was 1.0 m / s²; the average speed of small vehicles was approximately 15 km / h, and their acceleration was 2.0 m / s². 2 .

[0132] Next, using two frames of photos taken by a drone at the same location, and using the scale of the photos of the disaster event road section after stitching them together, the displacement of large and small vehicles between the stationary and starting frames was converted into actual distances. Combined with the timestamps of the photos, the starting delay of the large vehicle was calculated to be 6 seconds and the starting time of the small vehicle was 3 seconds.

[0133] Finally, based on the collected data, the off-peak traffic volume of the eastbound approach lane (Bomi-Basu) was 95 vehicles / hour / lane, and the peak traffic volume was 131 vehicles / hour / lane; the off-peak traffic volume of the westbound approach lane (Basu-Bomi) was 175 vehicles / hour / lane, and the peak traffic volume was 215 vehicles / hour / lane. The truck mixing rate on the westbound approach lane (Basu-Bomi) was 43%, while the truck mixing rate on the eastbound approach lane (Bomi-Basu) was 0.31%.

[0134] In summary, the characteristic parameters of the road sections affected by the disaster event are shown in Table 4.

[0135] Table 4 Basic characteristic parameters of road sections affected by disasters on two-lane highways

[0136]

[0137]

[0138] Step (3) Using measured traffic flow data, considering the impact of different vehicle types on traffic delay, calculate the equivalent quantity of small vehicles based on delay, construct a prediction model for the equivalent quantity of small vehicles, and calculate the adverse impact factor of large vehicles.

[0139] (3.1) Based on the collected traffic flow data, a simulation scenario of the impact of a disaster event on a two-lane highway was constructed using SUMO simulation software. The total delay of the collected traffic flow was based on all small cars, and the average delay value of each small car was calculated:

[0140]

[0141] In the formula, i = 1 and 2 represent different inlet lanes, i = 1 represents inlet lane 1, and i = 2 represents inlet lane 2; d i,0 Q represents the average delay for each small car on different entry lanes. i,0 D represents the total traffic volume (vehicles / hour) when all entrance lanes consist of small cars. i,0 The total delay when all the different import lanes consist of small cars.

[0142] (3.2) Based on the total delay collected under the scenario of large vehicles mixed in, calculate the average delay for each truck mixed in:

[0143]

[0144] In the formula, d i,t For the average delay of large vehicles entering the scene from different import lanes, Q i,t D represents the total flow of large vehicles (vehicles / hour) at different entrance lanes. i,t Total delays caused by large vehicles from different import lanes mixing in.

[0145] (3.3) Calculate the mixing rate of large vehicles:

[0146]

[0147] In the formula, p i,H Q represents the mixing rate of large vehicles from different import lanes. i,t Qi represents the total flow of large vehicles (vehicles / hour) at different entrance lanes.

[0148] (3.4) Considering the impact of large vehicles on the travel delay of a two-lane highway, calculate the equivalent quantity D_SVE of small vehicles based on the delay:

[0149]

[0150] (3.5) Existing research has shown that vehicle delays are proportional to the relative number of large vehicles in traffic flow; therefore, it is assumed that a linear relationship exists. Based on the calculated D_SVE value, a model is established to show the relationship between the equivalent quantity of small vehicles (D_SVE) and the mixing rate of large vehicles and the total traffic flow.

[0151]

[0152] In the formula, α i β is the coefficient for the mixing rate of large vehicles in different import lanes. i This is a coefficient representing the total flow rate at different inlets.

[0153] (3.6) The equivalent prediction model for small vehicles considering the delay of large vehicles is as follows:

[0154]

[0155] The best-fit result (R² ≥ 0.85) is selected as the final value of the fitting parameters. In this embodiment, the best-fit parameters are α = -0.32204, β = 0.02763, and R² = 0.893. Therefore, the prediction model for the equivalent quantity of small vehicles considering the delay of large vehicles is as follows:

[0156]

[0157] (3.7) Based on the small vehicle equivalent quantity prediction model, calculate the adverse impact factor of large vehicles on road sections affected by disaster events on two-lane highways;

[0158]

[0159] In the formula, p i,H D_SVE represents the mixing rate of large vehicles from different import lanes. i Let D_SVE be the equivalent value for small cars with different entry lanes.

[0160] Based on the small vehicle equivalent quantity prediction model, the method for calculating the adverse impact factor of large vehicles on road sections affected by disaster events in this embodiment is as follows:

[0161]

[0162] Step (4) Observe the actual travel time of the convoy in the alternating traffic section, correct the saturation flow of different entrance lanes, and construct a signal timing optimization model for alternating traffic on the road section affected by a two-lane highway disaster event.

[0163] Based on the Webster signal timing method, and considering truck delays, an arrival flow rate adjustment coefficient is applied using a large vehicle adverse impact factor. Combined with the actual situation of single-lane traffic control, a signal control method suitable for alternating one-way traffic on partially closed sections of a two-way, two-lane highway due to disasters, road construction, etc., is proposed. A schematic diagram of the signal control for alternating one-way traffic on partially closed sections of a two-lane highway is shown below. Figure 6As shown, when phase 1 is green, phase 2 is red, and vehicles in phase 1 can proceed. When phase 1 turns red, the last vehicle that has passed the stop line in phase 1 is allowed to proceed, and phase 2 remains red. Therefore, there is no yellow light period on a two-lane highway affected by a disaster. The green light interval is the start time plus the time it takes for the last vehicle to pass through the disaster-affected traffic zone, i.e., the phase clearing time.

[0164] (4.1) Calculate the phase clearing time for road sections affected by disaster events on two-lane highways:

[0165] Phase clearing time of the Bomi-Basu entrance channel:

[0166]

[0167] Phase clearing time of the entrance channel from Baxu to Bomi:

[0168]

[0169] (4.2) Considering the differences in start-up time and passage through disaster-affected road sections for large and small vehicles, calculate the total lost time W per signal cycle for the affected road sections of a two-lane highway affected by a disaster:

[0170] W = max{∑(t) T +t C +t i,AR )}=max{354.08,367.07}=367.07s

[0171] In the formula, t T For the start-up time of large vehicles; t C For the start-up time of a small car, t i,AR The duration of full red for each phase of the road segment affected by disaster events at different entrances;

[0172] (4.3) For long-distance alternating traffic sections, the saturation flow calculated based on the passage time of a single vehicle cannot directly reflect the traffic capacity. Therefore, we should improve the saturation flow calculation method based on stop lines by focusing on the traffic capacity of the convoy per unit time (i.e., convoy throughput).

[0173] First, based on the data collected from the cross-sectional traffic detectors, the times of the first vehicle entering and the last vehicle leaving the G318 Basu-Bomi alternating traffic section were recorded for 10 cycles. The actual travel time of the alternating traffic section was then obtained, and the 85th percentile value was used as the actual travel time Tp. The actual travel time at the Basu-Bomi entrance was 18 minutes, and the actual travel time at the Bomi-Basu entrance was 13 minutes.

[0174] Then, the saturation flow of different entrance lanes of the alternating traffic segment is adjusted according to the actual travel time Tp.

[0175] The corrected saturation flow rate of the Bomi-Basu inlet channel is:

[0176]

[0177] The corrected saturation flow rate of the Basu-Bomi inlet channel is:

[0178]

[0179] In summary, the corrected saturation flow rate for the alternating traffic sections of the G318 Sichuan-Tibet Highway is:

[0180]

[0181] In the formula, N i,c T represents the total number of vehicles at each entrance lane. i,c This refers to the actual observation time of the convoy passing through each entrance lane.

[0182] (4.4) Considering the impact of large vehicle delays, the arrival flow rates of different inlet lanes are corrected using the adverse impact factor of large vehicles, and the sum of the maximum flow rate ratios of each signal phase is calculated.

[0183]

[0184] In the formula, q i,c q represents the actual traffic volume of small vehicles at different entrances. i,t f represents the actual traffic volume of large vehicles at different entrance lanes. i,HV C is an adverse influencing factor for large vehicles. i,s Corrected saturation flow rate for different inlet channels.

[0185] (4.5) Calculate the optimal signal cycle for the road segment affected by a disaster event on a two-lane highway.

[0186]

[0187] In the formula, W is the total loss time per cycle, and Y is the sum of the maximum flow ratios of each signal phase.

[0188] (4.6) Calculate the green light display time g for each phase. i,e ′;

[0189] First, calculate the total effective green time for each cycle:

[0190] G e =T-2W=1585.65-2×367.07=851.49(s)

[0191] Then, calculate the effective green time for each phase:

[0192] ①Effective green light time for each phase of the Bomi-Basu entrance:

[0193]

[0194] ②Effective green light time for each phase of the Basu-Bomi entrance:

[0195]

[0196] Next, calculate the green light duration for each phase:

[0197] ① Green light times displayed for each phase of the entrance road from Bomi to Basu:

[0198] g 1,e ′=g 1,e +t T +t C =241.30 + 6 + 3 = 250.31 (s)

[0199] ② Green light times for each phase of the Basu-Bomi entrance road:

[0200] g 2,e ′=g 2,e +t T +t C =610.19 + 6 + 3 = 619.19 (s)

[0201] (4.7) Calculate the red light duration for each phase.

[0202] ① Red light times for each phase of the entrance road from Bomi to Basu:

[0203] R 1,e =Tg 1,e ′=1585.65-250.31=1335.35(s)

[0204] ② Red light times for each phase of the entrance road from Baxu to Bomi:

[0205] R 2,e =Tg 2,e ′=1585.65-619.19=966.46(s)

[0206] In summary, based on the proposed optimization model for alternating traffic signal timing for road sections affected by disasters on two-lane highways, and using traffic flow characteristic parameters extracted from measured data, the optimal signal cycle length for a disaster-affected point on the G318 Sichuan-Tibet Highway (Basu-Bomi section) is calculated to be 26.4 min. The signal timing scheme is shown in Table 5.

[0207] Table 5. Signal Timing Scheme for Road Sections Affected by a Disaster Event on G318

[0208]

[0209] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway, characterized in that, Includes the following steps: (1) Obtain the event attribute characteristics of the affected local road sections and the basic information of the road sections where the event occurred, and determine the traffic impact range of the local road sections of the event; (2) Deploy traffic flow collection equipment to collect traffic flow data of alternating traffic on local road sections under the influence of the event, and analyze the traffic flow characteristics of the alternating traffic sections; (3) Using measured traffic flow data, considering the impact of different vehicle types on traffic delay, calculate the equivalent quantity of small vehicles based on delay, construct a prediction model for the equivalent quantity of small vehicles, and calculate the adverse impact factor of large vehicles. Specifically: (3.1) Based on the collected traffic flow data, a simulation scenario of the impact of a two-lane highway event was constructed using SUMO simulation software. The collected traffic flow consisted of total delays with all small cars, and the average delay value of small cars was calculated: ; In the formula, i=1 and i=2 represent different inlet channels, i=1 represents the upstream inlet channel and i=2 represents the downstream inlet channel; The average delay for each small car at different entry lanes. This represents the total traffic volume when all the vehicles entering the road are small cars, expressed in vehicles per hour. Total delays when all imported vehicles are small cars; (3.2) Based on the total delay collected under the scenario of large vehicles mixed in, calculate the average delay under the scenario of trucks mixed in: ； In the formula, The average delay for scenarios where large vehicles from different import lanes mix. This represents the total flow of large vehicles at different entrances, expressed in vehicles per hour. Total delays caused by large vehicles from different import lanes mixing in; (3.3) Calculate the mixing rate of large vehicles: ； In the formula, To reduce the mixing rate of large vehicles from different import lanes, This represents the total flow of large vehicles at different entrances, expressed in vehicles per hour. Total traffic flow at different entrances, in vehicles per hour; (3.4) Considering the impact of large vehicles on the traffic delay of a two-lane highway, calculate the equivalent quantity D_SVE of small vehicles based on the delay: ； (3.5) Based on the calculated D_SVE value, establish a relationship model between the equivalent quantity D_SVE of small vehicles and the mixing rate and total flow of large vehicles; ； In the formula, The coefficient represents the mixing rate of large vehicles from different import lanes. A coefficient representing the total flow rate at different inlets; (3.6) The equivalent prediction model for small vehicles considering the delay of large vehicles is as follows: ； (3.7) The method for calculating the adverse impact factor of large vehicles on road sections affected by two-lane highway incidents is as follows: ； In the formula, To reduce the mixing rate of large vehicles from different import lanes, D_SVE is the equivalent value for small cars with different entry lanes; (4) Observe the actual travel time of the convoy on the alternating traffic section, correct the saturation flow of different entrance lanes, and construct a dynamic signal timing method for alternating traffic on the two-lane highway affected by the event.

2. The dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway according to claim 1, characterized in that, Step (1) specifically includes: (1.1) Obtaining event attribute characteristics: Obtain the event type, location, duration, and length L0 of the road segment occupied by the event through on-site traffic survey; (1.2) Collect basic information on the road section where the incident occurred: obtain the number of lanes, lane width, road design speed and road design capacity of the road section where the incident occurred through on-site traffic survey; (1.3) Determine the traffic impact range L of the alternating traffic sections of the event. d .

3. The dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway according to claim 2, characterized in that, In step (1.3) L d The method for determining [the value] specifically includes the following steps: (1.3.1) According to the provisions of the Highway Maintenance Safety Operation Procedures JTG H30-2015, during construction, traffic control personnel should be set up upstream and downstream of L1 outside the work area, and warning signs should be set up on both sides of the affected road section. The distance between the signs should be determined according to the Highway Maintenance Safety Operation Procedures JTG H30-2015. (1.3.2) An additional length L2, determined based on the actual staff placement needs, road visibility conditions, and safety factors of the alternating traffic sections, is used to ensure the staff's operating space and the safety and smoothness of traffic flow; (1.3.3) Determine the traffic impact range of the alternating traffic sections under the influence of the event as L. d : L d = L0+2L1+2L2; In step (1.3.2), the method for determining L2 specifically includes the following: (1.3.2.1) Based on the operational needs of staff and the requirements for equipment placement, a temporary work area shall be designated within the available area of ​​the alternating traffic section. The length of the temporary work area shall be L. S ; (1.3.2.2) To ensure that drivers can clearly see the work area and warning signs before entering the alternating traffic section, the visibility distance should meet the following formula: ； In the formula, L V It is the minimum sight distance in meters (m), V is the design speed in kilometers per hour (km / h), and T is the minimum sight distance in kilometers (m). r This refers to the driver's reaction time, which is set at 2.5 seconds; the additional length for curved road sections is set at 15-30 meters. (1.3.2.3) Calculate the additional length of a single-lane alternating traffic section on a two-lane highway using the following formula: L2=L S +L V 。 4. The dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway according to claim 1, characterized in that, Step (2) specifically includes: (2.1) Deploy traffic flow data collection equipment: Deploy MetroCount traffic flow detectors at the free-flow sections and control sections of different entrances outside the traffic impact range of the alternating traffic sections; deploy drones over the midstream road sections affected by the event; (2.2) Traffic characteristic parameters, including vehicle entry or exit time, vehicle type information and speed, are collected by installing cross-sectional traffic flow detectors at different entrance lanes of the affected road section. (2.3) Based on the time difference between the free-flow section and the control section of different entrances, the arrival traffic volume is statistically determined; (2.4) Video data of the affected road section was collected by drones deployed in the middle of the affected road section, and three types of traffic flow characteristic parameters, namely, passing speed, acceleration and start time, were extracted by video analysis tools.

5. The dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway according to claim 1, characterized in that, Step (4) specifically includes: (4.1) Calculate the phase clearing time of the affected road segment in a two-lane highway incident; ； In the formula, The length of the traffic impact zone for an incident on a two-lane highway. To reduce the mixing rate of large vehicles from different import lanes, The average passing speed of large vehicles in different entrance lanes. The average passing speed of small cars in different entrance lanes; (4.2) Considering the differences in start-up time and passage through the event section between large and small vehicles, calculate the total lost time W per signal cycle for the affected section of the two-lane highway event; ； In the formula, For the start-up time of large vehicles; For small cars, The duration of full red for each phase of the road segment affected by events at different approach lanes; (4.3) Based on the times when the last vehicle of the convoy enters and leaves the alternating traffic segment for 10-15 cycles collected by the cross-sectional traffic detector, the actual travel time of the convoy in the alternating traffic segment is obtained, and the 85th percentile value is used as the actual travel time Tc of the alternating traffic segment; the saturation flow of different entrance lanes of the alternating traffic segment is corrected by the actual travel time Tc, and the maximum value of the saturation flow of different entrance lanes after correction is taken as the final result; the calculation formula is as follows: ； In the formula, This represents the total number of vehicles at each entrance lane. The actual observed convoy passage time at each entrance lane; (4.4) Considering the impact of large vehicle delays, the arrival flow rates of different inlet lanes are corrected by the adverse impact factor of large vehicles, and the sum of the maximum flow rate ratios of each signal phase is calculated. ； In the formula, The actual traffic volume of small vehicles at different entrance lanes. The actual traffic volume of large vehicles at different entrance lanes. For large vehicles, Corrected saturation flow rates for different inlet channels; (4.5) Calculate the optimal signal cycle for the affected road segment of a two-lane highway event: ； In the formula, The total lost time per cycle, This is the sum of the maximum flow ratios of each signal phase; (4.6) Calculate the green light display time for each phase. ; (4.7) Calculate the red light duration for each phase: ； In summary, the signal period duration is obtained. The display of green light duration for each phase and display red light duration Together, they constitute the signal timing scheme for the affected road sections of a two-lane highway incident.

6. The dynamic timing method for alternating traffic signals in a single lane on a partial section of a two-lane highway according to claim 5, characterized in that, The step (4.6) displays the green light time. The calculation method specifically includes: (4.6.1) Calculate the total effective green light time: ； (4.6.2) Calculate the effective green light time for each phase: ； (4.6.3) Calculate the green light display time for each phase: ； In the formula, The total effective green light time for each cycle. The effective green time for each phase, The display of green light time for each phase. It is the sum of the maximum flow ratios of all signal phases that make up the period, and , The maximum flow ratio for phase i.

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