To perform the reasonable traffic structure in the historical districts and effectively alleviate the contradiction between limited traffic supply and rapid growth of the traffic demand in historical districts, a dynamic game model of traffic competition is established in this paper, aiming at the green transportation and sustainable development. Firstly, the logit model reflecting the sharing rate of the traffic mode is established by using the generalized cost method to quantify all the factors that influence the travel mode selection. Accordingly, a dynamic game model of complete information is established for the trip mode of historical districts, taking into account the economic sustainability, environmental sustainability, and social sustainability of the traffic development. The model is based on the goal of maximizing the generalized profit, and modeling with environmental pollution, energy utilization, and road service level as the common constraints of various traffic modes. By iterating the Nash equilibrium solution of the model, the optimal structure and the optimal share of the traffic modes in the historical districts can be predicted. Finally, the model presented in the study is verified by the historical districts of Academy Street in Zhengzhou city, China, and the optimal structure and optimal traffic share of each traffic mode in the block are obtained. By changing the constraint conditions of the model, two sets of different governance policies are compared and analyzed, and some feasible suggestions on improvement of traffic structure are also put forward. The research results can be the important reference for traffic planning in historic districts.
Historical districts refer to the important positions in the history and culture of a certain area, representing the cultural context of the region and the building group reflecting regional characteristics [
The existing research on urban traffic structure mainly involves four aspects. The first research aspect is the development mode of urban spatial layout and traffic structure [
Overall, the study of traffic structure almost begins with the rapid development of urban motorization, which mainly focuses on the study of the relationship between land use and traffic structure, the optimization model of traffic structure, and the transformation strategy of different traffic modes. Additionally, the practical experiences of traffic management measures such as congestion pricing are investigated according to the specific application of cities in various countries. Quantitative analysis shows that the optimization model based on different objectives has been applied in traffic structure planning practice, but the determination and selection of relevant factors and model constraints are not comprehensive enough. Meanwhile, for the study of traffic structure, the subject investigated is more focused on conventional cities. At present, more and more attention has been paid to the traffic problems in historic urban areas, but few studies have been devoted to the traffic structure of historic urban areas. If the traffic structure optimization model is established directly without considering the road conditions, environmental pollution, protection and restriction of energy utilization, and traffic characteristics of historic districts, the calculation result of the model is unreasonable and cannot effectively improve the traffic environment of historical urban areas. According to the traffic characteristics and protection restrictions of historic urban area, by studying the reasonable traffic structure of historic urban area, the most effective use of urban traffic resources can be realized and the overall function and function of urban traffic system can be maximized. Moreover, most of the existing studies use multivariate linear mathematical models to establish in depth and accurate models for traffic structure optimization. The multivariate linear mathematical model, however, cannot reflect the coordination and competition relationships among traffic modes. Furthermore, because there are no obvious monetary expenditure characteristics such as fare and fuel charges, the existing models usually do not consider the two types of traffic, pedestrian and bicycle, or simply quantify the cost of these two types of traffic. Game theory, which studies the coordination between rational subjects, has become one of the standard analysis tools of economics and extensive applications in biology, economics, international relations, computer science, political science, military strategy, and many other disciplines. Meanwhile, the relationship between the travel modes in the historic district meets the basic elements of the game, and it is very suitable for describing with a noncooperative game under complete information. By solving the Nash equilibrium solution, the competition behavior between transportation modes can be obtained; moreover, under their own conditions and market demand conditions, the strategy set can be achieved when the game players maximize their interests. Therefore, considering the actual traffic situation, environment, and road constraints, the concept of generalized cost is proposed, and the impacts of travel factors on the travel cost of each transportation mode are quantified in the unified way, which can enrich the theory of traffic structure research.
In the past two decades, the concept of sustainable development of urban passenger transport has aroused great interest of researchers and practitioners. On the one hand, scholars actively study the connotation, basic concepts, main contents, performance characteristics, and development strategies of sustainable development of the urban passenger transport system. For example, Tara and Josias [
The distribution of the traditional elements in the Academy Street [
Furthermore, other widely advocated policies for urban sustainable transport include attaching importance to the integrated planning of transportation and land use, implementing the strategy of giving priority to public transport, improving the rationality of road network construction, improving the parking planning and charging system, and calling on citizens to save energy, protect the environment, and change the travel modes [
From the perspective of travelers, they pay for financial, physical, and energy expenses to purchase a travel service that suits them. When making travel decisions, travelers will choose the most cost-effective travel mode between cost and getting services according to their own needs. From the perspective of travel modes, the income amount depends on the costs paid by the traveler and the costs of the self-disbursement, assuming that there are
Since the influencing factors of the generalized costs are not of the same dimension, the concept of time value is utilized in the study to quantify the influencing factors. Equation ( Economic index Rapidity index Convenience Comfort Safety
In summary, general travel costs paid by the traveler choosing the travel mode
In a certain period of time, the total travel demand
The logit model is a commonly used nonaggregate selection model; in this paper, the market share of the traffic mode is described by using the logit model, and the benefit function of the model is defined by using the generalized cost [
For the user demand of a certain OD pair within a district, it can be known that the user demand for the
Therefore, the general profit
Various travel modes in the historic district can be used to increase market share through various competition strategies. To achieve sustainable development of the traffic structure in the neighborhood, the increase in the occupancy rate of various modes should be limited by the appropriate traffic volume
To maintain and improve the traffic status of historical districts, the environmental factors and social factors of sustainable development should be taken into account in the limiting of travel volume, which should not exceed the limits of environmental pollution and energy using limits and also the service level of roads in historic districts should also be taken as a constraint.
The limit model of motor vehicle traffic can be established by Equation (
The constraints on the traffic volume of motor vehicles take the minimum value among the environmental traffic pollution limits of motor vehicles, the traffic energy utilization limits, and the traffic volume based on road network service levels. It is difficult to determine the service level of the road network by the traffic volume of nonmotorized vehicles and pedestrians. Therefore, the traffic volume limit is determined based on the principle of “time-space consumption.”
The competition among different travel modes in the historic districts is a game process, in which both of them can maximize their own interests under the constraints of their own conditions and market requirements. Each travel mode is treated as a participant with bounded rationality, and the game goal is to maximize the profit of their respective broad sense. The constraint conditions are the limit traffic volume at the peak hour of each transportation mode under the premise of protecting the features of the historic districts. Therefore, the noncooperative dynamic game model of the travel modes in historic districts can be established by
In a strategy combination, Nash equilibrium means that everybody’s strategy at this time can get the maximum benefit without others changing the strategy. Therefore, based on the structure of the Nash equilibrium model, the competition model of the passenger transport market in the districts can be established. In other words, the optimal sharing amount for each travel mode should satisfy the following inequality group as
To calculate the model, the Lagrange multiplier
Therefore, under the current conditions, the optimal solution
Therefore, all modes of travel can maximize their own interests, and the Nash equilibrium solution of the game is
However, when the
Therefore, the game order is as follows: Under current conditions, the strategy Each participant makes new coping strategies based on the strategies adopted by other competitors and ensures that their own interests are always maximized If a strategy set In all equilibrium situations that satisfy the requirements, the equilibrium strategy set
To determine the optimal solution, the concept of relative satisfaction
If and only if the
Each game participant formulates the optimal strategy
Each participant calculates the income after
The satisfaction
The optimal solution
After several years of construction and development, the historic city road facilities have formed a relatively complete traffic network system, and there is little potential for the further development of infrastructure to mitigate traffic pressure due to the protection of landscape features. Therefore, it is necessary to change the existing modes of traffic development and find other alternative ways to solve urban traffic problems. The Academy Street is the most historic living residential district in Zhengzhou city. The boundaries of the Academy Street historical district are east to Chengdong Road, west to Shuncheng Street, north to Shangcheng Road, and south to Chengnan Road. Due to its location in the old city, the district has largely preserved its traditional historical features (Figure
Distribution of the traditional elements in Academy Street.
To predict the internal travel structure of the historic district of Academy Street, the demand for each OD pair in the district should be obtained first, and then the travel mode share of each OD pair is calculated based on the prediction model so as to achieve the demand of various travel modes in the whole historical district. Currently, there are two common methods to obtain OD matrix, one is obtained by large-scale traffic survey, but the process of traffic investigation is time-consuming and laborious, and the later data processing workload is huge. In the late 1970s, scholars put forward a method to estimate the OD matrix by road traffic volume, that is, the second method to obtain the OD matrix: OD matrix backstepping method. The OD matrix backstepping program in software TransCAD considers the randomness of road section survey, and the matrix estimation function can be realized using any allocation method through multiple iterations between traffic assignment and matrix estimation. The program is mainly based on Nielsen’s research results in 1993 and 1998: single path OD matrix estimation method (SPME) and multipath OD matrix estimation method (MPME) [
Firstly, a road network zoning model within the scope of the study is established using the TransCAD software. On the basis of the area and the main street, the districts will be divided into six districts (1–6). The selected research scope in the study, however, is not entirely closed. Considering the impact of trip activities on research results, including that travelers in the block travel outside the block and travelers outside the block travel inside the block, three virtual residential areas (7–9) are delimited to the west of Shuncheng Street and north of Shangcheng Road, which can reduce the error effect of transregional travel on the result. The southern and eastern side of the study area is a fully preserved ancient city wall of the Ming Dynasty, and there is no possibility of transregional travel, so no virtual residential area is established. The whole area of analysis is 242 hectares, the North-South length is 1100 m, and the East-West length is 2200 m (Figure
The division of the traffic areas of Academy Street.
In this case study, the iteration number of the OD matrix estimation procedure is set to 20, and the convergence criteria are set to 0.000001. The road section information input in TransCAD software includes road grade, capacity, free flow speed, and measured traffic volume (peak period). The traffic assignment method based on stochastic user equilibrium is used to estimate the OD matrix, which is considered to be the traffic assignment method with the minimum mean error in OD backstepping [
The current travel OD of the Academy Street (person/h).
O | D | ||||||||
---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
1 | 0 | 731.37 | 810.32 | 868.21 | 756.56 | 888.74 | 769.63 | 737.76 | 721.64 |
2 | 753.21 | 0 | 827.46 | 712.93 | 695.62 | 735.73 | 629.65 | 754.23 | 721.76 |
3 | 628.13 | 876.89 | 0 | 834.41 | 642.23 | 787.79 | 589.76 | 715.37 | 697.85 |
4 | 826.35 | 782.37 | 678.92 | 0 | 743.47 | 729.67 | 809.83 | 621.54 | 662.57 |
5 | 687.89 | 746.84 | 698.57 | 768.79 | 0 | 808.93 | 649.72 | 607.54 | 713.47 |
6 | 732.36 | 697.68 | 768.75 | 679.57 | 763.12 | 0 | 612.88 | 656.17 | 703.25 |
7 | 659.31 | 703.87 | 632.43 | 645.73 | 587.76 | 546.73 | 0 | 673.57 | 587.93 |
8 | 703.53 | 724.42 | 646.81 | 691.24 | 642.37 | 521.21 | 687.92 | 0 | 746.31 |
9 | 667.11 | 653.28 | 752.64 | 587.58 | 631.53 | 592.47 | 546.87 | 679.58 | 0 |
It is noteworthy that the object of the game model presented is the traveler, travel mode, and travel behavior in the historic districts. By analyzing the environmental characteristics of many well-known historic districts, the area of historic district is generally small, and the distance between OD pairs is generally short, which is generally no more than 3 km. Furthermore, according to the results of RP survey on travelers, most of the travelers in historic districts are traveling in a single mode. Therefore, the multimode trips of travelers need not be considered in the model presented. The model in this paper is not applicable to large urban areas with multimode trips or long OD pairs, as well as to regions where travelers generally employ multimode trips.
Logit model parameter calibration values for travel modes in Academy Street historic districts.
Travel mode |
|
|
|
|
|
---|---|---|---|---|---|
Walking | 0.09 | 0.36 | 0.09 | 0.10 | 0.36 |
Bicycle | 0.16 | 0.23 | 0.24 | 0.12 | 0.25 |
Car | 0.18 | 0.18 | 0.23 | 0.16 | 0.25 |
Bus | 0.19 | 0.17 | 0.23 | 0.18 | 0.23 |
The optimal share rate of bus travel in Academy Street historical districts.
|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
---|---|---|---|---|---|---|---|---|---|
1 | 0 | 0.2451 | 0.2618 | 0.2355 | 0.2348 | 0.2439 | 0.2127 | 0.2105 | 0.2260 |
2 | 0.2379 | 0 | 0.2350 | 0.2156 | 0.2055 | 0.2319 | 0.2436 | 0.2282 | 0.2241 |
3 | 0.2468 | 0.2473 | 0 | 0.2529 | 0.2412 | 0.2127 | 0.2642 | 0.2341 | 0.2085 |
4 | 0.2366 | 0.2139 | 0.2553 | 0 | 0.2114 | 0.2358 | 0.2222 | 0.2164 | 0.2614 |
5 | 0.2341 | 0.2139 | 0.2373 | 0.2080 | 0 | 0.2126 | 0.2243 | 0.2258 | 0.2286 |
6 | 0.2422 | 0.2322 | 0.2156 | 0.2384 | 0.2101 | 0 | 0.2615 | 0.2667 | 0.2531 |
7 | 0.2116 | 0.2485 | 0.2674 | 0.2164 | 0.2274 | 0.2555 | 0 | 0.2520 | 0.2680 |
8 | 0.2196 | 0.2238 | 0.2391 | 0.2209 | 0.2344 | 0.2686 | 0.2554 | 0 | 0.2445 |
9 | 0.2417 | 0.2213 | 0.2142 | 0.2702 | 0.2345 | 0.2409 | 0.2715 | 0.2353 | 0 |
Trip distribution of each travel mode.
The results of the game show that the soft modes have become the main travel mode in the traffic system of the Academy Street historical districts. The prediction results are summarized as follows: Except for the error factors, the shares of walking and bicycle increase by 5.99% and 9.09%, respectively. Meanwhile, the shares of car and bus decrease by 61.15% and 4.67%, respectively. Soft modes become the most important transportation mode for districts, with a market share of 76.29%. The share of bicycle travel has increased significantly, and its market share (53.41%) also occupies an absolute advantage, which shows that the traveler prefers to travel by a bicycle after restricting the traffic volume of motor vehicles. The share of walking travel increases in a small range, and the total travel volume are generally stable, which is related to poor travel comfort and slow travel speed. From the comparison of data, the share of walking is about 2% higher when the distance is less than 1.5 kilometers, compared with that when the distance is more than 1.5 kilometers. The share of bicycle within 2 to 4 kilometers is also about 2% higher than other travel distances.
The above noncooperative game models presented in the study are calculated by digital simulation. Through the change of the constraints, the change of Nash equilibrium solution is observed, which provides the basis for the formulation of the competition strategy in the noncooperative competition of the historical districts. Assuming that the travel volume
The OD value difference of each travel mode.
The results of the two game models and the current traffic results are compared and analyzed. The results are as follows: By comparing the results of the two game models, it can be seen that the market share allocation of the four modes is related to their traffic volume constraints, and the ratio of traffic volume constraints of each mode is equivalent to its market share. By comparing the traffic structure of programme 1 with that of programme 2, the share of motor vehicles will be greatly increased with the increase of traffic volume constraint in the game model, indicating that the automobile is still the favorite transportation mode in historic street for the travelers. If the volume of car traffic is not restricted, the market share of cars will continue to rise. By comparing programme 1 with the current traffic structure, it can be seen that only by strictly restricting the traffic volume of cars can the proportion of cars be effectively reduced. By comparing programme 2 with the current traffic structure, it can be seen that if the number of cars is not constrained, the proportion of cars will continue to increase. By comparing the results of the two game models, after increasing the restriction of vehicle traffic volume, the bicycle trip share is obviously reduced, while the bus trip share is relatively stable. It proves that the most preferred mode of transportation for travelers in historic districts is bicycle travel after giving up using cars. It also shows that the competition between car travel and bicycle travel is the most intense. By comparing programmes 1 and 2 with the current traffic structure, the sharing of walking trip and bus trip is relatively stable, while the other two modes of transportation have less influence on their share rates. Meanwhile, the total amount of walking trip and bus trip is stable, indicating that the traveling groups of the two modes are relatively stable. When the urban traffic demand OD is constant, the operation state of the road network will be significantly different under different traffic modes. As detailed in Table The total amount of traffic pollutants emitted by different structural systems is different from the total energy consumed, and there are huge differences in the impact on the environment. After investigation, the market share of the new energy bus in Zhengzhou City accounts for 83%. Therefore, 17% of the bus traffic volume is used to calculate its environmental indicators. For the two different traffic structures of programme 1 and programme 2 solved through the game model, as well as the current traffic structure, the respective environmental simulation results are calculated as shown in Table
Operational indicators of traffic flow under the two travel modes.
Programme 1 | Programme 2 | Current traffic structure | |||||||
---|---|---|---|---|---|---|---|---|---|
Service level classification | A | B | C | A | B | C | A | B | C |
Road section (length) (%) | 82.41 | 13.15 | 4.44 | 21.15 | 20.98 | 15.37 | 18.78 | 19.62 | 14.33 |
Intersection (number) (%) | 78.53 | 12.76 | 8.71 | 22.51 | 21.42 | 14.69 | 19.24 | 19.73 | 13.96 |
Environmental indicators under the two travel modes.
CO emission | NO |
HC emission | Energy consumption | Static occupied space area | |
---|---|---|---|---|---|
(g) | (g) | (g) | (MJ) | (m2) | |
Programme 1 | 308527 | 20455 | 68058 | 34969 | 120522 |
Programme 2 | 789311 | 51359 | 169635 | 75513 | 211272 |
Current traffic structure | 815008 | 56574 | 187441 | 80635 | 221483 |
By comparing the two traffic structures in this case, for the same scale of road network, different traffic modes correspond to different levels of road network service and different environmental indicators. The traffic structure generated by strict traffic volume constraint is less than second type of traffic structure in terms of pollutant emission, energy consumption, and space occupied area. As long as the traffic volume of motor vehicles is constrained, the road traffic operation and ecological environment can be effectively improved.
According to the above analysis, two different governance concepts are embodied in programmes 1 and 2. For programme 1, taking the ecological protection and sustainable development of historical blocks as the core, the traffic volume of cars must be strictly restricted to meet the environmental requirements of ecological protection so that the travel mode in the block gradually becomes the absolute subject of soft modes. The concept of traffic management in Zhengzhou historic districts at this stage is presented in programme 2; that is, the car traffic should be limited by a small margin, and, for example, the policy of limiting working days for motor vehicles is now being implemented. According to the calculation results of programme 2, the road operating environment and ecological environment can be effectively improved even if the traffic volume of motor vehicles is limited slightly; however, there is still a big gap from the standard of historical block protection conditions. For historical blocks in developing cities, because of land use and other reasons, there are still lots of residential areas in historical blocks. In addition, due to the poor infrastructure at the present stage, the choice of transportation modes is relatively small, and one-size-fits-all restrictions on car travel are still inappropriate. Therefore, in the process of implementing the traffic structure optimization of historic blocks, the two different governance concepts should be weighed carefully. According to the experience of international metropolitan development, each region has its own characteristics in the process of optimizing the traffic structure development. The formulation of traffic policy should be tailored to local conditions. Here are some suggestions that can help historic blocks improve their transport structures. Optimization and perfection of the street and lane system for historical blocks: the protection of road and lane system in historical street is an important part of protecting the historical environment, which can maintain the historical appearance of the block, including the maintenance of the nonmotorized traffic environment of the road and alley system through the proper renovation and renewal. It is necessary to protect the texture of streets and lanes and to achieve corresponding traffic and functionality. At the same time, we should weaken the vehicle system and reduce the attractiveness of car trips. The urban planners suggest that the blocks should be set up as pedestrian areas without motor traffic. However, cities should also meet the actual needs of modern life, especially for large-scale historical and cultural cities. It is not realistic to completely turn historic blocks into pedestrian areas, and it will also bring many inconveniences. Therefore, the road system (street system) of historic blocks should consider the mode of “the demand for motorized traffic is moderately satisfied on the basis of maintaining the historic nonmotorized traffic mode.” For example, considering the Radburn idea road traffic system, the core protected area is set up, and traffic streets are set around the core reserve. Scientific analysis and organization of traffic links between historic districts and outlying urban areas: according to the guiding ideology of “guidance,” the “guidance mode” is combined with the moderate “traffic control.” To coordinate the development of motorized traffic and the protection of historical and cultural environment, firstly, historic blocks should be designated as nonmotorized traffic areas in terms of planning layout. According to the scale and current situation of historic blocks, scientific arrangement and organization of motorized traffic that must enter the blocks should be carried out. To protect the traffic environment of the block from excessive motor traffic interference, the good connection between the block and the surrounding urban area should be also considered. It not only maintains the good service of motor traffic to the block but also relieves the traffic pressure of the peripheral urban area and forms a good road network and traffic environment. Specific measures can be taken. For smaller blocks, traffic of the historic district can be restricted and controlled by traffic organization, and pedestrian areas can be set up in the blocks. In order to guide and implement the protection of the traffic environment of the block, a protective trunk road is planned and constructed on the periphery of the block. For example, in the 1980s, Xi’an, China, in order to protect the environment of the Ming Dynasty city wall completely, the ancient city wall park began to be built, protecting the historical environment of the ancient city walls and moats in Ming Dynasty. At the same time, the road was built outside the city wall park, forming the first traffic protection ring of the ancient city, which played a role in separating and connecting the traffic environment inside the ancient city and the modern traffic environment outside the ancient city. Scientific implementation of traffic management measures: scientific TDM (traffic demand management) should be implemented to reduce the disorderly entry of vehicles into historical blocks. Accordingly, a tranquil and convenient transportation system supplemented by soft modes and low-carbon public transport can be established gradually. Specific measures can be taken: according to the tail number of the car license plate, a single day limit measure is adopted for cars. For the peak hours of working days or the peak tourist periods of historical blocks on festivals and holidays, traffic control signs and facilities can be set up at the main intersections entering the blocks, the policy of prohibiting the entry of transit traffic or adopting congestion charges can be implemented, and the entry of freight vehicles or other vehicles can be restricted. For the parking management measures, on the one hand, the supply of parking space in the block can be controlled, and parking facilities at the junction of urban arteries and traffic streets around the block should be set up. On the other hand, parking fees can be raised appropriately, and the number of cars entering the block can be controlled and gradually reduced. For example, congestion charges in central London and low emission zones were set up in 2008. Additionally, a market-oriented high parking fee policy was adopted to reduce the upper limit of the number of parking spaces allocated for construction, and many restrictions on the use of cars were employed. Encouraging the implementation of public transport optimization strategy: on the one hand, the convenience of bus trip can be improved by increasing the density of bus stops in the block. If the demand of long-term express bus is to be met, bus lanes should be set up as far as possible. On the other hand, the service level of public transport should be improved, such as the adoption of new energy vehicles and the placement of intelligent bus service settings. It is suggested to enrich the public transport systems as necessary, such as adding subway, light rail, and public bicycle. For instance, Stockholm’s block bus system is rich in traffic modes and offers a wide range of options for travelers, including trams, subways, buses, and public bicycles. Bus stations are evenly distributed, and the distance between stations is generally between 300 and 500 meters. Bus lanes are set up to facilitate travelers. Meanwhile, the level of public transport services has gradually improved with automatic takeoff and landing doors, intelligent arrival reminders, and other functions. Travelers would feel comfortable when they ride with interest in bus riding being greatly improved. For example, since 2009, Singapore has improved the quality of bus services by shortening the intervals, increasing stations and optimizing routes. Under a series of combined measures, the proportion of public transport trips has risen sharply.
Taking Zhengzhou Academy Street district as an example, a dynamic game model is established in the study, which presents the optimal sharing rate and optimal traffic structure of the various transportation modes in the blocks. The dynamic game model is suitable for travel in historical blocks of developing cities. Because of most of the travelers in historic districts are traveling in a single mode, the multimode trips of travelers are need not be considered in the model presented. The game model in this paper is not applicable to large urban areas with multimode trips or long OD pairs, as well as to regions where travelers generally employ multimode trips. The dynamic game model of generalized cost is established to simulate the competitive relationship among different travel modes in historical districts. The travel expenses of each travel mode, which quantified by the dynamic game model of generalized fees, overcome the shortcomings of the inability to quantify the costs of walking and bicycle travel in the traditional prediction model and can more fully reflect the competition relationship between soft modes and motor vehicle traffic. Through the comparison and analysis of two different traffic structures obtained by changing the constraints in the game model, the change in the share of each travel mode and the sharing rate of each mode of travel conform to the market laws, which proves the correctness of the model. The simulation results of the two traffic structures can also reflect the traveler’s travel preferences in the historical district. To effectively improve the traffic system and ecological environment of historical blocks in developing cities, it is necessary to formulate traffic policies scientifically, implement them prudently and comprehensively, and adjust measures to local conditions. To improve the traffic problems of historic blocks, we should mainly protect the environment of the blocks, adopt the guiding measures of “guidance,” and combine “guidance” with “traffic control” to optimize and adjust appropriately. By encouraging low-carbon and convenient transportation, the historic blocks will gradually be built into a quiet and convenient traffic system with soft modes as the main and low-carbon public transport as the supplement, which is guided by scientific and strict traffic management measures. We should deal with the relationship between the development of urban motorized traffic and the protection of historic districts so as to achieve a win-win situation between the protection of historic and cultural environment and modern traffic services. Through employing these measures, we can coordinate the relationship between the development of urban motorized traffic and the protection of historic districts so as to achieve a win-win situation between the protection of historic and cultural environment and modern traffic services.
The traffic data listed in this paper are measured and obtained from the investigation in the Zhengzhou Academy Street area, including current situation of road operation, traveler’s characteristic data, and travel characteristic data. The OD matrix data listed in this paper are obtained from the software TransCAD. The calculated data listed in this paper are obtained from the software MATLAB, including the optimal share rate of each travel mode and data of trip distribution.
The authors declare that there are no conflicts of interest regarding the publication of this article.
This work was financially supported by the National Natural Science Foundation of China (Grant No. 51278396).