The Effect of Traffic Facilities Accessibility on Residents’ Travel under Block Scale

The development of urbanization and motorization has changed the way of life of residents. It greatly increases residents’ dependence on motor vehicles, thus causing a series of traffic travel problems. The development of road traffic has become an important research perspective. Especially, the influence of traffic facilities accessibility on residents’ travel is of great significance. Based on the questionnaire and SPSS analysis software, this paper discusses the influence of traffic facilities accessibility on the travel mode and distance of residents under the influence of their individual social attributes. The results show that whether the residents own cars, their occupation and their monthly income have influence on the travel distance. Under the influence of control, the number of bus lines, the number of intersections, the distance from the nearest bus station and the distance from the residents travel are negatively correlated, that is, the more bus lines, the more intersections, the farther away from the nearest bus station, the shorter the travel distance of residents. And the way of residents travel is basically determined by the factors of residents’ social attributes and residents’ travel distance. Traffic construction needs to fully consider the needs of different residents.

convenience on residents' travel has become a hot topic in traffic research. Therefore, this paper takes gaoshui district of mianyang city as an example to explore the relationship between the two impacts and summarize the analysis results, so as to provide a partial basis for future traffic planning and a research direction for future carbon emission reduction. Over the years, scholars and policy makers from different fields have been seeking effective ways to solve the problem of traffic congestion and improve the quality of residents' travel, Zhan et al. (2018). In 2016, the CPC Central Committee and the State Council issued "some opinions of the CPC Central Committee and the State Council on further strengthening the management of urban planning and construction" pointed out that it is necessary to strengthen the planning and construction of blocks and establish the concept of urban road layout with "narrow roads and dense road networks" (Wang, 2018). Then "narrow road, dense road network and community life circle" is widely used as an important means to manage urban problems.
On the basis of solving urban problems, scholars at home and abroad take the design of road space as one of the focus of attention. There have also been a series of related theoretical works, such as "City Image", "the death and life of big cities in the United States", "Urban Design" and so on. Most studies are based on the establishment of traffic convenience indicators. Some scholars compare and study the subjective traffic convenience evaluation and objective traffic related data to analyze the traffic convenience within the study area (Wang & Yang, 2012). Some scholars are to directly evaluate the convenience of urban public transport, select the convenience evaluation index such as bus station coverage and average speed of transportation, and construct the evaluation index system of urban public transport convenience (Ren et al. 2015). On this basis, scholars began to explore the impact factors of road traffic. Taking Beijing as an example and combining the objective data of built environment such as block scale with the subjective data of residents' traffic evaluation survey, Zhan et al. (2018) used an orderly multi-classification logic model to explore the influence of block scale characteristics on residents' subjective traffic convenience evaluation and traffic safety evaluation. In terms of bus facilities, Wu (2009) Craig et al. (2002) and others have also proved that the proportion of intersection, the form of road layout and the travel environment are also closely related to the choice of residents' travel mode while studying residents' behavior. Frank et al. (2005) studied the relationship between residents' daily travel patterns in Atlanta and the neighborhood environment around their homes, and believed that the more intersections around their homes, the more likely they would choose to walk. Other studies have shown a link between home and the distance to the nearest bus stop and travel. For example, Kitamura et al. (1997) found that the proportion of car trips was positively correlated with the convenience of parking lots and the distance from bus stations.

Research Area
This paper takes the high water area of Mianyang city as an example, divided by many urban roads, and selects 6 residential areas with the urban block as the basic analysis unit ( Figure 2). The survey settlements include Jialai Shengshui Home, Garden Xinghe Bay, Cui Man Ting, Changhong Century City, Changxing Pingzheng Anju District and East Wall Street.

Data Sources
The data of this paper are derived from the questionnaire survey of residents'

Research Methodology
The main research methods were correlation analysis and multiple logistic regression analysis. Correlation analysis is to judge whether there is a connection between social and economic attributes, residents' travel behavior and road traffic convenience, grasp the direction and degree of correlation, and provide a basis for the use of multiple logistic regression analysis for progress. Multiple logistic regression is also called multiple logistic regression. Based on the analysis of the influence of road traffic convenience on residents' travel distance, the variable of residents' travel distance was taken as the dependent variable and the variable of residents' social attributes as the independent variable. In the study of the impact of road traffic convenience on residents' travel mode, the residents' travel mode is taken as the dependent variable, and the residents' travel distance, road traffic convenience and residents' social attributes are taken as the independent variables.
First of all, the paper makes a statistical analysis of the residents' economic and social attributes, travel behavior and the present situation of road traffic facilities in the questionnaire survey. By analyzing the correlation between residents' social and economic attributes, road traffic convenience and residents' travel behavior through SPSS software, the multivariate regression model of residents' social attribute factors and residents' travel distance was established. By establishing multiple logistic regression model, the paper discusses the influence of road traffic convenience and residents' social attributes on residents' travel mode.

Results and Analysis
According to the above methods, the data is analyzed, which is mainly about the residents' personal attributes and travel characteristics. The correlation and multiple regression analysis of the relationship between the road traffic convenience, travel distance and travel mode were carried out. By observing the fitting degree of the model and the significance degree of residents' social attributes, the influence relationship was analyzed.

Impact of Road Traffic Convenience on Travel Distance of Residents
Correlation analysis was used to analyze the relationship between traffic convenience and travel distance of residents in high water area of Mianyang City.  On the basis of analyzing the influence of road traffic convenience on residents' travel distance, the multivariate linear regression model between residents' social attributes and residents' travel distance is established. Among them, the resident travel distance variable is the dependent variable, and the resident social attribute variable is the independent variable. By observing the fitting degree of the model and the remarkable degree of the residents' social attribute, the influence of the residents' social attribute factors on the residents' travel distance is analyzed. Table 3 shows that the fitting degree of the model is 42.1%. The sig.
values in Table 4 show that the ownership of cars, residents' monthly income and residents' occupational variables are significant, and the established regression model is effective.
The estimated results of the model are shown in Table 5. Whether the residents own cars, the residents' monthly income and the residents' occupation have an impact on the residents' travel distance. And whether the residents own cars and the residents' occupation regression coefficient is −0.693 and −0.087, respectively, which is negatively correlated with the residents' travel distance. The monthly income coefficient of residents is 0.206, which is positively correlated     On the basis of the regression analysis model, the partial correlation between road traffic convenience and travel distance was analyzed based on the control variables of car ownership, monthly income and occupation. Table 6 shows that under the influence of controlling the social attribute factors of the residents, the number of bus lines, the number of intersections, the distance of the nearest bus stop are significantly correlated with the distance of the residents' travel, and all of them are negatively correlated. That is, the more bus lines, the more intersections, the farther the nearest bus stop distance, the shorter the residents travel distance, and vice versa. The higher the number of intersections indicates that the more convenient the residents are in the blocks, the better the accessibility of the road network, which leads to the reduction of the residents' dependence on private cars and the reduction of the residents' travel distance. There may be two reasons for the number of bus routes and the distance from the nearest bus station. First, the number of bus lines in the land use mix is relatively high, service facilities are relatively complete. The surrounding facilities can meet the basic needs of residents, the farther away from the nearest bus stop from the residential area will reduce the choice of bus travel, so the probability of long distance travel is less. Second, according to the field investigation area found that the convenience of public transport facilities and the abundance of service facilities is one of the conditions for residents to choose housing. According to the questionnaire, most of the activities of local residents are carried out around the residential area, so the influence of personal preference is great.  travel as the dependent variable, the distance of residents' travel, the convenience of road traffic and the social attributes of residents are independent variables. By observing the fitting degree of the model and the remarkable degree of road traffic convenience, the influence of road traffic convenience on residents' travel distance is analyzed. As shown in Table 7, the significant value is less than 0.05 in the model fitting information, and the model has statistical significance. In general, the fit degree of the model is affected by the number of samples (Yao, 2015). The larger the number of samples, the weaker the interpretation degree of the model to the variables and the smaller the fitting degree. But the stability of the model will be better, considering this reason, the sample size is moderate, the R square value is on the high side, indicating that the model has a high degree of interpretation of the original variables (Table 8).

Impact of Road Traffic Convenience on Travel Patterns of Residents
It can be seen from

Conclusion
According to the field investigation data, this paper analyzes the impact of road traffic convenience on residents' travel in high water area of Mianyang city, and provides the basis for optimizing traffic environment and improving travel quality. The study found that road traffic convenience and residents travel distance significantly correlated, but the impact on residents travel mode is relatively small. The main conclusions are: 1) In the high water area of Mianyang, the travel mode of residents is less affected by road traffic convenience, but it is significantly related to the social attributes of residents. Age, occupation, and ownership of a car all affect residents' choice of travel style. Residents pay more and more attention to the quality of life. The way of daily travel is personal preference. And different occupations also determine the economic situation of residents, so that they affect whether to own cars, thus affecting the distance residents travel.
2) The degree of road traffic convenience has a significant negative impact on the travel distance of residents. More road intersections will improve the road network accessibility, increase the setting of public transport stations, greatly reduce the dependence of residents on cars, resulting in a relative reduction in the travel distance of residents. Generally speaking, the land use mix is higher in places with high road traffic convenience, and the farther away from the nearest bus stop in the residential area, the closer the travel distance is when the surrounding facilities basically meet the needs of the residents.
3) In terms of travel distance variables, residents travel distance and travel mode have a significant correlation, and the coefficient is positive. This shows that when the travel distance is large, the probability of residents choosing private car travel mode and bus travel mode is greater than that of walking, bicycle and electric vehicle travel mode.
Of course, the factors that affect residents' travel behavior include not only road traffic convenience factors, but also block scale, road width, building density, volume ratio and other residential development and construction factors. Due to the focus of this paper and the limitation of data, other influencing factors cannot be included in the model together. In addition, in order to improve the traffic environment and the quality of residents' travel, it is necessary to set up the location of public transport stations and the number of lines reasonably, increase the number of road intersections, actively create a small block, dense road network environment, reduce residents' travel distance, reduce residents' travel carbon emissions.