# Optimization of Emergency Transportation Organization of Holiday Tourism Traffic

Authors: Xiliang Wang; Yujing Tang; Qingyu Qi; Guomei Wang; Bowen Bi
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

The purpose of the optimization of holiday traffic emergency traffic organization is to solve the problem of serious traffic jams in holiday scenic spots. Based on the prediction of traffic volume and traffic mode division in the future years of the scenic spot, the traffic accident route is analyzed to provide theoretical support for the emergency traffic organization and planning of the scenic spot. This article takes the Shijiazhuang Jinta Bay scenic area as the research object, based on the traffic volume of the Jinta Bay tourist scenic area from 2009 to 2016, analyzes the traffic environment of the scenic area, predicts the traffic demand, and builds a one-way traffic organization double-layer optimization model. The simulated annealing algorithm is used to solve the model, an emergency transportation organization optimization plan is formulated, and the feasibility of the plan is verified through VISSIM simulation. The results of the study show that the one-way traffic organization method reduces the average vehicle delay by 32.2% and the average queue length by 14.5%. The one-way traffic organization based on branch diversion can more effectively solve the main road jamming and congestion caused by traffic accidents, prevent the occurrence of secondary accidents, and reduce the economic losses of scenic area managers. At the same time, the purpose of ensuring the tourist quality of tourists and the economic interests of scenic spot management departments is ensured.


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## Body

## 1. Introduction

With the rapid development of social economy, the number of tourists in China is increasing and tourists are pursuing a higher travel experience. In 2019, the number of trips per capita in China reached 4 times, and large passenger flow has gradually become a common and normal phenomenon [1–4]. Especially in the peak tourism period such as holidays and weekends, the tourists in the scenic spot are not evenly distributed, which leads to the overload of popular scenic spots and the congestion of traffic arteries and nodes. Therefore, the value of tourists’ tourism experience is not high. The size of the market continues to grow, increasing the contradiction between supply and demand. Short-term tourist gathering caused by emergencies such as large-scale tourism festival activities, sudden natural disasters, traffic, and transportation accidents of tourists, and the breakdown of scenic facilities not only leads to the decrease of tourists’ satisfaction and experience but also induces safety accidents, which puts the scenic spot management and tourism safety guarantee system under great pressure. Therefore, the research on holiday transportation emergency transportation organization becomes more and more urgent.Scholars at home and abroad have conducted a lot of research on holiday tourism transportation. Crouch et al. have made it clear that traffic factors have a more obvious impact on the overall travel experience. With the deepening of the research on traffic behavior in scenic spots, the research on the combination of transportation infrastructure layout and travel flow theory has become a new development direction [5]. Jameel and Boopen used the gravitational model to prove the important influence of scenic traffic infrastructure on the flow of tourists and explored the mechanism between the travel destination choice of tourists and the spatial distribution of scenic traffic infrastructure [6]. Smallwood et al. studied the dynamic model of tourist flow and found that tourist flow strongly depends on the scenic transportation infrastructure network [5]. Lv et al. studied the recreational spatial relationship of scenic spots through network analysis and GIS geographic analysis methods [7–9]. Brida et al. believed that no matter in the whole road network or in a single section or intersection, there was a location with the highest probability of traffic congestion, which was the root cause of traffic congestion [10]. Feng et al. studied the effect of the main traffic roads around the scenic spot on the evolution of regional tourism spatial structure [11]. Pei and Lang studied the emergency traffic evacuation method from the three aspects of accident section restriction, optimal evacuation path selection, and minimum vehicle circumambulation time and found that there was a certain internal relationship among the three [12]. They solved the optimal emergency traffic evacuation method by establishing a two-layer optimization model. Chen and Wang studied the spatiotemporal changes of the formation and dissipation of road network congestion and proved that the CTM-based quasidynamic traffic allocation method can quantitatively evaluate the effectiveness of traffic organization schemes under emergencies [13].It can be seen from this that the domestic and foreign scholars’ research on the emergency traffic organization scheme of tourism traffic mostly focuses on the urban road network and expressway network and rarely involves how to comprehensively construct road accident traffic accident emergency transportation organization schemes in tourist attractions. Therefore, on the basis of urban road network and expressway network traffic accident emergency traffic organization plan, combined with the characteristics of the scenic spot network, so as to build a holiday scenic spot network traffic accident congestion evacuation method [14], this article takes the Shijiazhuang Jinta Bay tourist scenic spot as an example, analyzes the traffic profile of the scenic spot, and predicts the traffic demand of the scenic spot during the peak holiday season. Then, this was used as a benchmark to establish a one-way traffic organization double-layer optimization model, formulate an emergency traffic organization optimization program, and verify its feasibility with simulation software, so as to provide a reference for the administrative department of the scenic spot to adopt emergency traffic organization scheme and emergency rescue measures after traffic accident and congestion occurs in the scenic spot in the future.


## 2. Traffic Demand Forecast for Jinta Bay Scenic Spot during Holidays

### 2.1. Traffic Environment of the Scenic Spot

The specific location of Jinta Bay Scenic Spot is shown in Figure1. The road network of Jinta Bay Scenic Area is shown in Figure 2. The scenic road network is formed by the intersection of four main roads and four branch roads. The four two-way driving roads outside the scenic area are the main road sections in the scenic area (the thick red line section in Figure 2 and are also the main evacuation paths for the traffic volume in the tourist area in Table 1. The branch road section (the thin green line section in Figure 2 inside the scenic area is prohibited from entering vehicles and is the main path for tourists to walk and ride. The part enclosed by the main road and the branch road is Jinta Bay Flower Sea, which is the main scenic spot of Jinta Bay Scenic Spot.Figure 1
The specific location of Jinta Bay Scenic Spot.Figure 2
The overall road network of Jinta Bay Scenic Spot.Table 1
Forecast value of annual traffic volume of Jinta Bay Scenic Spot (vehicles).
YearGrowth methodRegression predictionMoving average methodQuadratic exponential smoothingAverage valueCombined forecast20172 073 1871 914 5222 012 1731 916 1151 985 1161 961 24720182 298 1822 009 2812 143 8942 011 5272 115 4532 084 34220192 545 1772 101 8172 282 2952 113 6062 260 7242 216 38820202 820 0562 195 4652 422 9012 216 7952 413 8042 351 34520213 124 6222 289 6722 563 5062 319 9852 574 4462 490 95120223 462 0812 376 3912 704 1122 423 1752 741 4402 632 87120233 835 9852 501 2522 844 7172 526 3652 927 0802 793 60620244 007 5142 617 8132 984 2122 628 4443 061 4852 922 51520254 187 8812 762 7123 124 8172 731 6343 201 7613 061 24320264 376 3862 872 8123 265 4232 834 8243 337 3563 187 01620274 574 4842 980 1293 407 1392 939 1253 475 2193 315 78420284 780 3363 155 3823 547 7453 042 3153 631 0843 468 888


### 2.2. The Forecast of Annual Traffic Volume

Based on the traffic volume of Jinta Bay Scenic Spot in each month from 2009 to 2016, the traffic volume of Jinta Bay Scenic Spot in the future was predicted by the combined forecasting method. The prediction model is shown as follows in Formula (1).
(1)Y=∑i=1nwiyi.In the formula,Y represents predictive value. wi represents the weight coefficient of the i model, ∑i=1nwi=1. yi represents the predicted value of the i model. n represents the number of models.The combined forecasting method is used to combine the forecasting results of the four models of growth method, regression forecast method, moving average method, and quadratic exponential smoothing method [15]. The weight coefficients of these four models are 0.15, 0.35, 0.25, and 0.25, respectively.


### 2.3. Peak Day Traffic Forecast

There are obvious seasonal divisions in the tourist form of Jinta Bay Scenic Spot, which can be divided into the peak season of spring and autumn and the low season of winter and summer. According to the “Shijiazhuang Tourism Master Plan,” the proportion of tourists in the peak tourist season accounts for 80% of the annual tourist reception [16]. At the same time, considering the theory of life cycle of tourist destinations and the tourism capacity of Jinta Bay Scenic Spot, and considering the ratio of peak sunrise travel scale of scenic spot tourists to the total travel volume of the whole year under the current holiday management system in China, the peak daily traffic flow of Jinta Bay Scenic Spot in different years is predicted. The predicted results are shown in Table 2.Table 2
Forecast value of peak day traffic volume in Jinta Bay Scenic area (vehicles).
Year2016201820232028The peak day traffic volume21,18323,46130,05838,336


### 2.4. Forecast of Traffic Division

No vehicles are allowed to enter the subroads of the Jinta Bay Scenic Spot road network. Therefore, when traffic jams occur on the main road, tourists on foot or by bike can enter the subroad section of the road network to make a detour, so as not to affect the emergency traffic organization on the congested road section.Considering the growth of private car ownership and utilization rate in the planning years, as well as the improvement of bus service level, the structure of passenger flow in different years was predicted based on the current situation survey [17]. The predicted results are shown in Table 3.Table 3
Prediction of peak tourist flow pattern structure in Jinta Bay Scenic Spot (%).
YearPassenger carSmall car201810902023148620282278The above takes the Jinta Bay tourist area as an example to predict the traffic demand and obtains the specific traffic volume and traffic mode division data of the scenic area in the future years.


## 2.1. Traffic Environment of the Scenic Spot

The specific location of Jinta Bay Scenic Spot is shown in Figure1. The road network of Jinta Bay Scenic Area is shown in Figure 2. The scenic road network is formed by the intersection of four main roads and four branch roads. The four two-way driving roads outside the scenic area are the main road sections in the scenic area (the thick red line section in Figure 2 and are also the main evacuation paths for the traffic volume in the tourist area in Table 1. The branch road section (the thin green line section in Figure 2 inside the scenic area is prohibited from entering vehicles and is the main path for tourists to walk and ride. The part enclosed by the main road and the branch road is Jinta Bay Flower Sea, which is the main scenic spot of Jinta Bay Scenic Spot.Figure 1
The specific location of Jinta Bay Scenic Spot.Figure 2
The overall road network of Jinta Bay Scenic Spot.Table 1
Forecast value of annual traffic volume of Jinta Bay Scenic Spot (vehicles).
YearGrowth methodRegression predictionMoving average methodQuadratic exponential smoothingAverage valueCombined forecast20172 073 1871 914 5222 012 1731 916 1151 985 1161 961 24720182 298 1822 009 2812 143 8942 011 5272 115 4532 084 34220192 545 1772 101 8172 282 2952 113 6062 260 7242 216 38820202 820 0562 195 4652 422 9012 216 7952 413 8042 351 34520213 124 6222 289 6722 563 5062 319 9852 574 4462 490 95120223 462 0812 376 3912 704 1122 423 1752 741 4402 632 87120233 835 9852 501 2522 844 7172 526 3652 927 0802 793 60620244 007 5142 617 8132 984 2122 628 4443 061 4852 922 51520254 187 8812 762 7123 124 8172 731 6343 201 7613 061 24320264 376 3862 872 8123 265 4232 834 8243 337 3563 187 01620274 574 4842 980 1293 407 1392 939 1253 475 2193 315 78420284 780 3363 155 3823 547 7453 042 3153 631 0843 468 888


## 2.2. The Forecast of Annual Traffic Volume

Based on the traffic volume of Jinta Bay Scenic Spot in each month from 2009 to 2016, the traffic volume of Jinta Bay Scenic Spot in the future was predicted by the combined forecasting method. The prediction model is shown as follows in Formula (1).
(1)Y=∑i=1nwiyi.In the formula,Y represents predictive value. wi represents the weight coefficient of the i model, ∑i=1nwi=1. yi represents the predicted value of the i model. n represents the number of models.The combined forecasting method is used to combine the forecasting results of the four models of growth method, regression forecast method, moving average method, and quadratic exponential smoothing method [15]. The weight coefficients of these four models are 0.15, 0.35, 0.25, and 0.25, respectively.


## 2.3. Peak Day Traffic Forecast

There are obvious seasonal divisions in the tourist form of Jinta Bay Scenic Spot, which can be divided into the peak season of spring and autumn and the low season of winter and summer. According to the “Shijiazhuang Tourism Master Plan,” the proportion of tourists in the peak tourist season accounts for 80% of the annual tourist reception [16]. At the same time, considering the theory of life cycle of tourist destinations and the tourism capacity of Jinta Bay Scenic Spot, and considering the ratio of peak sunrise travel scale of scenic spot tourists to the total travel volume of the whole year under the current holiday management system in China, the peak daily traffic flow of Jinta Bay Scenic Spot in different years is predicted. The predicted results are shown in Table 2.Table 2
Forecast value of peak day traffic volume in Jinta Bay Scenic area (vehicles).
Year2016201820232028The peak day traffic volume21,18323,46130,05838,336


## 2.4. Forecast of Traffic Division

No vehicles are allowed to enter the subroads of the Jinta Bay Scenic Spot road network. Therefore, when traffic jams occur on the main road, tourists on foot or by bike can enter the subroad section of the road network to make a detour, so as not to affect the emergency traffic organization on the congested road section.Considering the growth of private car ownership and utilization rate in the planning years, as well as the improvement of bus service level, the structure of passenger flow in different years was predicted based on the current situation survey [17]. The predicted results are shown in Table 3.Table 3
Prediction of peak tourist flow pattern structure in Jinta Bay Scenic Spot (%).
YearPassenger carSmall car201810902023148620282278The above takes the Jinta Bay tourist area as an example to predict the traffic demand and obtains the specific traffic volume and traffic mode division data of the scenic area in the future years.


## 3. One-Way Traffic Organization Model

### 3.1. Construction of a Two-Layer Optimization Model for One-Way Traffic Organization

Holiday travel season network congestion has the traffic accident in the scenic spot, in order to at the same time guarantee the quality of tourist scenic area management and economic benefit, for traffic road network based on branch shunt one-way traffic organization is a good way to evacuate congestion, reduce the economic loss of the scenic area management, and ensure that visitors can enjoy the scenic spots in the shunt branch road. The optimization of one-way traffic organization should carry out optimization research for two goals at the same time, and finally reach a comprehensive optimal goal. The specific objectives are optimized as follows:(1)
The primary goal of implementing one-way traffic organization is to minimize the average saturation of main road sections and the average saturation of branch roads(2)
Congestion evacuation time is as little as possibleWhen establishing the optimization model of one-way traffic organization, the organization plan of emergency traffic organization in the road network of tourist attractions can be used as the upper decision-making variable, and the ultralimited saturation of the road network and the minimum vehicle running time can be used as the optimization objectives of the upper decision-making variables [18]. For the lower level optimization, the user equilibrium assignment model is used. The specific modeling process is shown as follows in the following:Average maximum saturation of arterial road sections:(2)∑a∈AlamaxSxa−S0a,0∑a∈Ala.The average overlimit of the branch road section about the maximum saturation:(3)∑a∈BxlamaxSxa−S0a,0∑a∈Bxla.The shortest average time required for a vehicle to travel out of an accident is(4)min∑a∈A∪BxqxaRxala∑a∈A∪Bxla.By assigning objective Formulas (2), (3), and (4) to different weight parameters ξ, a bilevel planning model optimized for one-way traffic organization can be obtained:
(5)minZx=ξ1∑a∈AlamaxSxa−S0a,0∑a∈Ala+ξ2∑a∈BlamaxSxa−S0a,0∑a∈Bla+ξ3∑a∈A∪BxqxaRxala∑a∈A∪Bxla.s.tSxa=qxaCxa,a∈A∪Bx,C0a≤Cxa≤Cmaxa,lrs=∑a∈A∪Bxlaδakrs;r,s=1,2,⋯,n.Among them, the flow of the road sectionqxa, a∈A∪Bx meets the following plan:
(6)min∑a∈A∪Bx∫0qxtawdw,s.t(7)∑k=1Lr,sfkrs=qrs;r,s=1,2,⋯,n,(8)qxa=∑r=1n∑s=1n∑k=1lr,sfkrsδakrs,a∈A∪Bx,(9)fkrs≥0,r,s=1,2,L,n,k=1,2,⋯,Lr,s.In Formulas (6) to (9), Lr,s represents the number of paths between OD pair r,s. fkrs represents the traffic of the k path between OD pairs r,s. δakrs represents link-path-related variables. If the link a is on the k path between the OD pairs r,s, it is 1; otherwise, it is 0. taqxa represents the road resistance function, which is a strictly increasing function of the road section flow qxa.


### 3.2. Algorithm for Solving Bidirectional Optimization Model of Unidirectional Organization

The simulated annealing algorithm can be used to simulate the bilevel programming problem with the thermal equilibrium of statistical mechanics, and the objective function can be used as an energy function to solve the problem according to the annealing treatment principle of solid matter in physics. The algorithm can make most of the random heuristics on the outer surface of the feasible solution set acceptable and guarantee that all the heuristics are feasible solutions, which can improve the reliability and computational efficiency in the solving process. Therefore, this paper decided to use simulated annealing algorithm to solve.The neighborhood system construction of the solution is one of the key problems in the implementation of the simulated annealing algorithm [19]. For a given one-line plan x, J=aa∈Bx,Sxa≥η is the set of accident-congested road segment under road network Nx. For any accident congested section a=vi,vj∈J, a¯vi,vj is the undirected section corresponding to a in branch set Bx, and its adjustment state xa¯ can be determined by x′a¯. If a¯ was originally a single line from vi to vj, adjust a¯ to a single line from vj to vi. Traverse all accident congested road sections a=vi,vj∈J in J and their adjustable state a=vi,vj∈J to get the neighborhood system X=x′a, where x′a=x−xa¯∪x′a¯. Then, the neighborhood solution x′ is constructed with random probability.


## 3.1. Construction of a Two-Layer Optimization Model for One-Way Traffic Organization

Holiday travel season network congestion has the traffic accident in the scenic spot, in order to at the same time guarantee the quality of tourist scenic area management and economic benefit, for traffic road network based on branch shunt one-way traffic organization is a good way to evacuate congestion, reduce the economic loss of the scenic area management, and ensure that visitors can enjoy the scenic spots in the shunt branch road. The optimization of one-way traffic organization should carry out optimization research for two goals at the same time, and finally reach a comprehensive optimal goal. The specific objectives are optimized as follows:(1)
The primary goal of implementing one-way traffic organization is to minimize the average saturation of main road sections and the average saturation of branch roads(2)
Congestion evacuation time is as little as possibleWhen establishing the optimization model of one-way traffic organization, the organization plan of emergency traffic organization in the road network of tourist attractions can be used as the upper decision-making variable, and the ultralimited saturation of the road network and the minimum vehicle running time can be used as the optimization objectives of the upper decision-making variables [18]. For the lower level optimization, the user equilibrium assignment model is used. The specific modeling process is shown as follows in the following:Average maximum saturation of arterial road sections:(2)∑a∈AlamaxSxa−S0a,0∑a∈Ala.The average overlimit of the branch road section about the maximum saturation:(3)∑a∈BxlamaxSxa−S0a,0∑a∈Bxla.The shortest average time required for a vehicle to travel out of an accident is(4)min∑a∈A∪BxqxaRxala∑a∈A∪Bxla.By assigning objective Formulas (2), (3), and (4) to different weight parameters ξ, a bilevel planning model optimized for one-way traffic organization can be obtained:
(5)minZx=ξ1∑a∈AlamaxSxa−S0a,0∑a∈Ala+ξ2∑a∈BlamaxSxa−S0a,0∑a∈Bla+ξ3∑a∈A∪BxqxaRxala∑a∈A∪Bxla.s.tSxa=qxaCxa,a∈A∪Bx,C0a≤Cxa≤Cmaxa,lrs=∑a∈A∪Bxlaδakrs;r,s=1,2,⋯,n.Among them, the flow of the road sectionqxa, a∈A∪Bx meets the following plan:
(6)min∑a∈A∪Bx∫0qxtawdw,s.t(7)∑k=1Lr,sfkrs=qrs;r,s=1,2,⋯,n,(8)qxa=∑r=1n∑s=1n∑k=1lr,sfkrsδakrs,a∈A∪Bx,(9)fkrs≥0,r,s=1,2,L,n,k=1,2,⋯,Lr,s.In Formulas (6) to (9), Lr,s represents the number of paths between OD pair r,s. fkrs represents the traffic of the k path between OD pairs r,s. δakrs represents link-path-related variables. If the link a is on the k path between the OD pairs r,s, it is 1; otherwise, it is 0. taqxa represents the road resistance function, which is a strictly increasing function of the road section flow qxa.


## 3.2. Algorithm for Solving Bidirectional Optimization Model of Unidirectional Organization

The simulated annealing algorithm can be used to simulate the bilevel programming problem with the thermal equilibrium of statistical mechanics, and the objective function can be used as an energy function to solve the problem according to the annealing treatment principle of solid matter in physics. The algorithm can make most of the random heuristics on the outer surface of the feasible solution set acceptable and guarantee that all the heuristics are feasible solutions, which can improve the reliability and computational efficiency in the solving process. Therefore, this paper decided to use simulated annealing algorithm to solve.The neighborhood system construction of the solution is one of the key problems in the implementation of the simulated annealing algorithm [19]. For a given one-line plan x, J=aa∈Bx,Sxa≥η is the set of accident-congested road segment under road network Nx. For any accident congested section a=vi,vj∈J, a¯vi,vj is the undirected section corresponding to a in branch set Bx, and its adjustment state xa¯ can be determined by x′a¯. If a¯ was originally a single line from vi to vj, adjust a¯ to a single line from vj to vi. Traverse all accident congested road sections a=vi,vj∈J in J and their adjustable state a=vi,vj∈J to get the neighborhood system X=x′a, where x′a=x−xa¯∪x′a¯. Then, the neighborhood solution x′ is constructed with random probability.


## 4. Formulation and Verification of Optimization Plan for Emergency Traffic Organization

### 4.1. Formulation of Optimization Plan for Emergency Traffic Organization

Take sections 1-5 as the accident section for analysis. The road network is shown in Figure3. Only considering that the traffic flowing in the clockwise direction on the main road in the scenic area can be diverted by the branch road, and the maximum expected saturation S0a=0.85 of the main road. C2a=1000pcu/h represents the one-way traffic capacity of each branch, and S0a=0.75 represents the maximum expected saturation of the branch. Other relevant parameters are shown in Tables 4–6.Figure 3
Example road network diagram.Table 4
Distribution of traffic demand (OD) between nodes.
Node123105926162483056237089530Table 5
Main parameters of each main road section.
SectionCapacity (pcu/h)Length (m)Free flow time (min)(1-5)2 5005780.868(5-6)2 5005620.842(6-2)2 5002380.353(2-10)2 5005240.787(10-14)2 5004370.607(14-4)2 5001960.296(4-16)2 5002110.314(16-15)2 5005330.800(15-3)2 5005050.758(3-11)2 5005190.775(11-7)2 5004580.636(7-1)2 5005070.763Table 6
Main parameters of each branch road section.
SectionCapacity (pcu/h)Length (m)Free flow time (min)(5-8)10006070.913(6-9)10005830.873(7-8)10005560.846(8-9)10005900.880(9-10)10002730.434(8-12)10003870.557(9-13)10004050.575(11-12)10005320.822(12-13)10006080.898(13-14)10003150.466(12-15)10004080.578(13-16)10003520.592In the process of one-way traffic organization optimization, in order to investigate the influence of each evaluation index value, the values ofξ1 and ξ2 were fixed as 1, and ξ3 comparative test was conducted by changing the values. Table 7 lists the size of each one-way organization optimization plan and its corresponding evaluation index value in different ranges of ξ3.Table 7
Comparison of various optimization schemes and their evaluation index values.
Plan numberValue range ofξ3Main road average saturation limitBranch saturation average over limitRoad network saturation total average over limitAverage evacuation time per vehicle/min1[0,2.5)0.063 20.007 40.068 319.652 22[2.5,14.5)0.067 80.008 20.073 114.677 13[14.5,56)0.081 20.012 30.087 48.846 54[56,+∞)0.089 30.016 50.099 20.000It can be seen from Table7 that with the increase of the interval value of ξ3, the average overrun of the saturation of arterial and branch roads corresponding to each one-way traffic organization scheme is increasing, while the average driving time per vehicle is decreasing. When ξ3 increases indefinitely, the average saturation limit of the road section in the corresponding scheme 4 reaches the maximum, but the evacuation time is zero. At this time, the road network is the original road network without any one-way traffic settings. Compared with option 4, the decrease in the average overrun of main road and branch saturation in option 1, option 2, and option 3 are: 29.2% and 55.1%, 24.0% and 5 1.5%, and 9.3% and 25.1%. It can be clearly seen that the degree of decline in the saturation limit of the branch road is higher than that of the main road.In option 1, the main road and branch road saturation limit is the largest. Although the average driving time per car reached 19.652 3 min at this time, for the sake of travel safety, this driving time is not long, and tourists are still acceptable. Based on the above analysis, choose option 1 as the recommended option for the one-way traffic organization of the road network. The road network flow and saturation distribution corresponding to Scheme 1 are shown in Table8. The recommended scheme for one-way traffic organization optimization is shown in Figure 4.Table 8
Road network flow and saturation distribution corresponding to option 1.
Arterial road sectionFlow/vehSaturationMain branch road sectionFlow/vehSaturation(1-5)332.70.693(7-8)257.71.074(5-6)590.41.230(8-5)257.71.074(6-2)590.41.230(10-9)115.50.481(2-10)556.81.160(9-13)115.50.481(10-14)441.30.919(13-12)115.50.481(14-4)410.70.856(12-15)115.50.481(4-16)445.50.928(16-15)445.50.928(15-3)647.11.348(3-11)597.90.831(11-7)597.90.831(7-1)374.70.521Figure 4
Optimization plan diagram (arrows indicate branch road sections with one-way diversion, and non-arrow main road sections are driven in both directions).


### 4.2. Establishment of Traffic Simulation Model

Based on MAC bay scenic area road network in the research of the tourist season, the scenic spot most of the traffic accident congestion occurs in four road sections of road network, and each road section traffic accident frequency and number of similar. Combined with the four road sections of roads and road structure are all the same, therefore, to 4 network of 1 ~ 5 section of the road section, take 1 ~ 5 segments within a circumference of lanes as simulation object, using the VISSIM simulation software simulation of the one-way traffic organization way, road network model uses the model shown in Figure4, each branch distributor roads and traffic as shown in Table 9. The duration of the accident is 200 s, and the proportion of cars and buses is 1 : 9. Traffic accident congestion traffic flow operation diagram is shown in Figure 5. The simulation results are shown in Figure 6. The data results are shown in Table 9.Table 9
Simulation results of one-way traffic organization.
Arterial road sectionFlow/vehVehicle delay (s)Average queue length (m)Main branch road sectionFlow/vehAverage delay/sAverage queue length (m)(1-5)332.723.50(7-8)257.730.411.5(5-6)590.432.80(8-5)257.730.411.2(6-2)590.432.813.2(10-9)115.510.73.7(2-10)556.831.712.5(9-13)115.510.73.7(10-14)441.329.611.2(13-12)115.510.74.5(14-4)410.726.510.5(12-15)115.510.63.9(4-16)445.530.511.8(16-15)445.530.811.8(15-3)647.134.916.7(3-11)597.923.80(11-7)597.932.813.2(7-1)374.732.813.0Figure 5
Traffic accident congestion traffic flow operation effect diagram.Figure 6
One-way traffic organization simulation results.It can be seen from the simulation results that when the branch area is evacuated in the one-way traffic organization mode, the node conflicts due to traffic accident congestion are reduced, and the conflicts with the opposite vehicles are eliminated. Vehicle delays and the average queue length of the entire scenic road network have also become very small, greatly improving the traffic capacity of each road section.In order to evaluate the rationality and effectiveness of the one-way traffic organization, this paper takes the Jinta Bay scenic road network as the research object and uses the VISSIM software to simulate and calculate the one-way traffic organization scheme based on branch diversion. The obtained simulation results are evaluated and analyzed and compared with the evacuation effect of the emergency traffic organization scheme based on trunk road diversion. The comparison results are shown in Table10.Table 10
Comparison of simulation results before and after optimization.
MeasuresTraffic flow/vehAverage delay (s)Average queue length (m)Traffic diversion organization30013.95.250039.37.060061.812.2One-way traffic organization method using tributary30010.33.750023.76.260042.611.8It can be seen from Table10 that the one-way traffic organization method reduces the delay of vehicles by 32.2% and the average queue length by 14.5% compared to the traffic diversion organization method. The one-way traffic organization based on branch diversion can more effectively solve the main road jamming and congestion caused by traffic accidents, prevent the occurrence of secondary accidents, and reduce the economic losses of scenic area managers. In addition, the optimized emergency transportation organization plan does not affect the beauty of tourists visiting the scenic area, and even tourists can visit the scenery that is not seen on the main road section. Therefore, the use of tributaries to divert and organize one-way traffic can not only achieve the intended purpose but also improve the tourist quality of tourists.


## 4.1. Formulation of Optimization Plan for Emergency Traffic Organization

Take sections 1-5 as the accident section for analysis. The road network is shown in Figure3. Only considering that the traffic flowing in the clockwise direction on the main road in the scenic area can be diverted by the branch road, and the maximum expected saturation S0a=0.85 of the main road. C2a=1000pcu/h represents the one-way traffic capacity of each branch, and S0a=0.75 represents the maximum expected saturation of the branch. Other relevant parameters are shown in Tables 4–6.Figure 3
Example road network diagram.Table 4
Distribution of traffic demand (OD) between nodes.
Node123105926162483056237089530Table 5
Main parameters of each main road section.
SectionCapacity (pcu/h)Length (m)Free flow time (min)(1-5)2 5005780.868(5-6)2 5005620.842(6-2)2 5002380.353(2-10)2 5005240.787(10-14)2 5004370.607(14-4)2 5001960.296(4-16)2 5002110.314(16-15)2 5005330.800(15-3)2 5005050.758(3-11)2 5005190.775(11-7)2 5004580.636(7-1)2 5005070.763Table 6
Main parameters of each branch road section.
SectionCapacity (pcu/h)Length (m)Free flow time (min)(5-8)10006070.913(6-9)10005830.873(7-8)10005560.846(8-9)10005900.880(9-10)10002730.434(8-12)10003870.557(9-13)10004050.575(11-12)10005320.822(12-13)10006080.898(13-14)10003150.466(12-15)10004080.578(13-16)10003520.592In the process of one-way traffic organization optimization, in order to investigate the influence of each evaluation index value, the values ofξ1 and ξ2 were fixed as 1, and ξ3 comparative test was conducted by changing the values. Table 7 lists the size of each one-way organization optimization plan and its corresponding evaluation index value in different ranges of ξ3.Table 7
Comparison of various optimization schemes and their evaluation index values.
Plan numberValue range ofξ3Main road average saturation limitBranch saturation average over limitRoad network saturation total average over limitAverage evacuation time per vehicle/min1[0,2.5)0.063 20.007 40.068 319.652 22[2.5,14.5)0.067 80.008 20.073 114.677 13[14.5,56)0.081 20.012 30.087 48.846 54[56,+∞)0.089 30.016 50.099 20.000It can be seen from Table7 that with the increase of the interval value of ξ3, the average overrun of the saturation of arterial and branch roads corresponding to each one-way traffic organization scheme is increasing, while the average driving time per vehicle is decreasing. When ξ3 increases indefinitely, the average saturation limit of the road section in the corresponding scheme 4 reaches the maximum, but the evacuation time is zero. At this time, the road network is the original road network without any one-way traffic settings. Compared with option 4, the decrease in the average overrun of main road and branch saturation in option 1, option 2, and option 3 are: 29.2% and 55.1%, 24.0% and 5 1.5%, and 9.3% and 25.1%. It can be clearly seen that the degree of decline in the saturation limit of the branch road is higher than that of the main road.In option 1, the main road and branch road saturation limit is the largest. Although the average driving time per car reached 19.652 3 min at this time, for the sake of travel safety, this driving time is not long, and tourists are still acceptable. Based on the above analysis, choose option 1 as the recommended option for the one-way traffic organization of the road network. The road network flow and saturation distribution corresponding to Scheme 1 are shown in Table8. The recommended scheme for one-way traffic organization optimization is shown in Figure 4.Table 8
Road network flow and saturation distribution corresponding to option 1.
Arterial road sectionFlow/vehSaturationMain branch road sectionFlow/vehSaturation(1-5)332.70.693(7-8)257.71.074(5-6)590.41.230(8-5)257.71.074(6-2)590.41.230(10-9)115.50.481(2-10)556.81.160(9-13)115.50.481(10-14)441.30.919(13-12)115.50.481(14-4)410.70.856(12-15)115.50.481(4-16)445.50.928(16-15)445.50.928(15-3)647.11.348(3-11)597.90.831(11-7)597.90.831(7-1)374.70.521Figure 4
Optimization plan diagram (arrows indicate branch road sections with one-way diversion, and non-arrow main road sections are driven in both directions).


## 4.2. Establishment of Traffic Simulation Model

Based on MAC bay scenic area road network in the research of the tourist season, the scenic spot most of the traffic accident congestion occurs in four road sections of road network, and each road section traffic accident frequency and number of similar. Combined with the four road sections of roads and road structure are all the same, therefore, to 4 network of 1 ~ 5 section of the road section, take 1 ~ 5 segments within a circumference of lanes as simulation object, using the VISSIM simulation software simulation of the one-way traffic organization way, road network model uses the model shown in Figure4, each branch distributor roads and traffic as shown in Table 9. The duration of the accident is 200 s, and the proportion of cars and buses is 1 : 9. Traffic accident congestion traffic flow operation diagram is shown in Figure 5. The simulation results are shown in Figure 6. The data results are shown in Table 9.Table 9
Simulation results of one-way traffic organization.
Arterial road sectionFlow/vehVehicle delay (s)Average queue length (m)Main branch road sectionFlow/vehAverage delay/sAverage queue length (m)(1-5)332.723.50(7-8)257.730.411.5(5-6)590.432.80(8-5)257.730.411.2(6-2)590.432.813.2(10-9)115.510.73.7(2-10)556.831.712.5(9-13)115.510.73.7(10-14)441.329.611.2(13-12)115.510.74.5(14-4)410.726.510.5(12-15)115.510.63.9(4-16)445.530.511.8(16-15)445.530.811.8(15-3)647.134.916.7(3-11)597.923.80(11-7)597.932.813.2(7-1)374.732.813.0Figure 5
Traffic accident congestion traffic flow operation effect diagram.Figure 6
One-way traffic organization simulation results.It can be seen from the simulation results that when the branch area is evacuated in the one-way traffic organization mode, the node conflicts due to traffic accident congestion are reduced, and the conflicts with the opposite vehicles are eliminated. Vehicle delays and the average queue length of the entire scenic road network have also become very small, greatly improving the traffic capacity of each road section.In order to evaluate the rationality and effectiveness of the one-way traffic organization, this paper takes the Jinta Bay scenic road network as the research object and uses the VISSIM software to simulate and calculate the one-way traffic organization scheme based on branch diversion. The obtained simulation results are evaluated and analyzed and compared with the evacuation effect of the emergency traffic organization scheme based on trunk road diversion. The comparison results are shown in Table10.Table 10
Comparison of simulation results before and after optimization.
MeasuresTraffic flow/vehAverage delay (s)Average queue length (m)Traffic diversion organization30013.95.250039.37.060061.812.2One-way traffic organization method using tributary30010.33.750023.76.260042.611.8It can be seen from Table10 that the one-way traffic organization method reduces the delay of vehicles by 32.2% and the average queue length by 14.5% compared to the traffic diversion organization method. The one-way traffic organization based on branch diversion can more effectively solve the main road jamming and congestion caused by traffic accidents, prevent the occurrence of secondary accidents, and reduce the economic losses of scenic area managers. In addition, the optimized emergency transportation organization plan does not affect the beauty of tourists visiting the scenic area, and even tourists can visit the scenery that is not seen on the main road section. Therefore, the use of tributaries to divert and organize one-way traffic can not only achieve the intended purpose but also improve the tourist quality of tourists.


## 5. Conclusion

According to the traffic composition and characteristics of Jinta Bay Scenic Spot, the combined forecasting method can be used to predict the traffic flow of holiday tourism scenic spots, and the method of combining analogy analysis and trend prediction can be used to predict the traffic patterns of holiday tourist scenic spots, thus, can get future year tourism scenic area of the peak day traffic flow and traffic mode structure. Solving the problem of establishing model data source, data accuracy is much higher than traditional yearbook data.The emergency transportation organization plan in the scenic road network is taken as the upper decision variable, and the saturation limit of the tourist road network segment is minimized and the vehicle travel time is minimized as the optimization goal of the upper decision variable. The user balance distribution model is used to optimize the lower layer, which can realize the construction of a double-layer optimization model and can be solved by using the simulated annealing algorithm.VISSIM verified the effectiveness of the emergency transportation organization plan developed by the double-layer optimization model, which can effectively reduce the delay of congested vehicles and the length of vehicle queues, and, at the same time, ensure the tourist quality of tourists and the economic benefits of scenic area management departments. The model has certain reference significance for the holiday traffic management of similar scenic spots.The study of tourist traffic emergency traffic organization at home and abroad mostly focuses on the scenic area outside the city road network and highway network. In this paper, with scenic road network as the research object, to the profit of the scenic area management and quality of visitors travel to emergency traffic organization goals. The accident area branch shunt one-way traffic organization method for evacuation can effectively reduce the node conflicts arise from congestion due to traffic accident, to eliminate and conflict to have car, can more effectively solve the scenic area due to traffic accident main road congestion and crowding, prevent secondary the happening of the accident. Vehicle delays and the average queue length of the entire scenic road network have also become very small, greatly improving the traffic capacity of each road section. Later, studies should consider threat factors such as natural disasters, health events, and public safety events and conduct emergency traffic organization optimization studies for traffic jams caused by each type of event.



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*Source: 2264876-2022-01-07.xml*