Artificial Intelligence Techniques for Joint Sensing and Localization in Future Wireless NetworksView this Special Issue
Optimization of Emergency Transportation Organization of Holiday Tourism Traffic
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.
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 . 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 . Smallwood et al. studied the dynamic model of tourist flow and found that tourist flow strongly depends on the scenic transportation infrastructure network . 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 . Feng et al. studied the effect of the main traffic roads around the scenic spot on the evolution of regional tourism spatial structure . 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 . 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 .
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 , 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 Figure 1. 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.
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).
In the formula, represents predictive value. represents the weight coefficient of the model, . represents the predicted value of the model. 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 . 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 . 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.
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 . The predicted results are shown in Table 3.
The 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 possible
When 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 . 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:
The average overlimit of the branch road section about the maximum saturation:
The shortest average time required for a vehicle to travel out of an accident is
Among them, the flow of the road section , meets the following plan:
In Formulas (6) to (9), represents the number of paths between pair . represents the traffic of the path between pairs . represents link-path-related variables. If the link is on the path between the OD pairs , it is 1; otherwise, it is 0. represents the road resistance function, which is a strictly increasing function of the road section flow .
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 . For a given one-line plan , is the set of accident-congested road segment under road network . For any accident congested section , is the undirected section corresponding to in branch set , and its adjustment state can be determined by . If was originally a single line from to , adjust to a single line from to . Traverse all accident congested road sections in and their adjustable state to get the neighborhood system , where . Then, the neighborhood solution 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 Figure 3. 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 of the main road. represents the one-way traffic capacity of each branch, and represents the maximum expected saturation of the branch. Other relevant parameters are shown in Tables 4–6.
In the process of one-way traffic organization optimization, in order to investigate the influence of each evaluation index value, the values of and were fixed as 1, and 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 .
It can be seen from Table 7 that with the increase of the interval value of , 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 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 Table 8. The recommended scheme for one-way traffic organization optimization is shown in Figure 4.
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 Figure 4, 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.
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 Table 10.
It can be seen from Table 10 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.
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.
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this article.
The research was supported by the Key R&D Plan of Hebei Science and Technology Department (grant number 18275406D), Hebei Province Innovation Ability Promotion Project: Soft Science Research Project (grant number 19456002D), Science and Technology Project of Hebei Provincial Department of Transportation, Jijiao Technology (grant number 409 201816) and Science and Technology Project of Hebei Provincial Department of Transportation (grant number Y-201601).
G. Qiao, L. Ding, L. Zhang, and H. Yan, Accessible Tourism: A Bibliometric Review (2008–2020), Tourism Review (Association Internationale d'experts Scientifiques du Tourisme), 2021.
Z. Lv, L. Qiao, and I. You, “6G-enabled network in box for internet of connected vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 8, pp. 1–8, 2021.View at: Google Scholar
H. Wu and D. J. Liu, “Study on the coupling and coordination degree of transportation and tourism development in China,” Statistics and Decision Making, vol. 35, no. 17, pp. 143–146, 2019.View at: Google Scholar
C. B. Smallwood, L. E. Beckley, and S. A. Moore, “An analysis of visitor movement patterns using travel networks in a large marine park, North-Western Australia,” Tourism Management, vol. 33, no. 3, pp. 517–528, 2012.View at: Google Scholar
K. Jameel and S. Boopen, “The role transport infrastructure in international tourism development: a gravity model approach,” Tourism Management, vol. 29, no. 4, pp. 831–840, 2008.View at: Google Scholar
Z. Lv, R. Lou, and A. K. Singh, “AI empowered communication systems for intelligent transportation systems,” IEEE Transactions on Intelligent Transportation Systems, pp. 1–9, 2020.View at: Google Scholar
J. Chen, Q. Wang, J. Huang, and X. Chen, “Motorcycle ban and traffic safety: evidence from a quasi-experiment at Zhejiang, China,” Journal of Advanced Transportation, 13 pages, 2021.View at: Google Scholar
L. X. Feng, X. Z. Yang, H. Yao, and S. Lu, “Influence of backbone transportation infrastructure on regional tourism spatial pattern: a case study of Bohai Bay Cross Sea corridor,” Economic Geography, vol. 2, pp. 189–194, 2019.View at: Google Scholar
Y. L. Pei and Y. S. Lang, “Congestion mechanism analysis and countermeasure research based on dynamic traffic assignment. Journal of Huazhong University of science and technology.,” Urban Science, vol. 3, pp. 95–98, 2018.View at: Google Scholar
Q. Chen and W. Wang, “Temporal and spatial effects of emergencies on traffic flow in large-scale events,” Journal of Transportation Engineering, vol. 9, no. 3, pp. 81–85, 2018.View at: Google Scholar
Y. Han, W. Y. Li, and G. Yang, “Reliability analysis of traffic network in scenic spots based on node importance,” Traffic Information and Security, vol. 37, no. 6, pp. 128–138, 2019.View at: Google Scholar
Q. Huang, Y. E. Zheng, and Y. Q. Deng, “Research on road network flow prediction based on XGBoost holidays,” Highway, vol. 63, no. 12, pp. 229–233, 2018.View at: Google Scholar
Y. Li and Q. Jiang, “Demand forecasting and information platform in tourism,” Open Physics, vol. 15, pp. 247–252, 2017.View at: Google Scholar