Study On Characterisitcs Of Mixed Bicycle Traffic Flow In Basic Sections Of Urban Road

With the increase of electric bicycles (E-bikes) and the decrease of regular bicycles (R-bikes) year by year in China, the E-bike trips have been higher than the R-bike trips in many cities. A mixed traffic flow has been formed including E-bikes and R-bikes in the separated bicycle path of urban road. It makes the urban road traffic flow become more complex and brings new troubles to the traffic management. Generally, E-bikes run a speed higher than the limit value of law. The speed difference between E-bikes and R-bikes is large. This is the main sticking point of the urban traffic problems. Therefore, it has important significance to the development of non-motor vehicle traffic flow theory and the solution to the urban traffic problems that the characteristics of the mixed bicycle traffic flow as well as the bicycle road capacity is studied. The urban road traffic flow is the subject of this research. The main research work is as flows:(1) The statistical characteristics of the mixed bicycle traffic flowThe static characteristics and dynamic characteristics of the two types of bicycles including E-bikes and R-bikes are analyzed, which are based on the field data of the mixed bicycle traffic flow on urban road. The speed characteristics of the mixed bicycle traffic flow are studied in this research and the influencing factors for it are also studied. Results show that E-bikes have a quite difference with the R-bikes in the static characteristics, especially the difference of the lateral width. E-bike is the main travel mode in non-motor travels of urban residents. From gender perspective, the male riders are the major part of the non-motor travelers. From the riders’age structure, the young riders are the major part of the non-motor travelers. The operation speed of bicycles is influenced significantly by the differences of bicycle types, rider genders and ages. But the operation speed is little influenced by the difference of the bicycles which carry something (men or objects) or not.(2) The speed characteristics of the mixed bicycle traffic flowIn this chapter, the individual bicycle speed is taken as the subject of our reseasrch. The mixed Gaussian distribution models of individual bicycle speeds are established, which include the distribution model of the R-bike speed, the E-bike speed and the mixed speed of the two, respectively. The velocity discreteness of the mixed bicycle traffic flow is studied in this chapter. Parameters for describing the discreteness of bicycle speed are normalized discreteness and coefficient of variation. The main influencing factors for the two parameters are also studied. The influencing factors for vehicle passing rate were studied. Regression models are established to determine the relationships between the main influencing factors and the passing rates. The results show that the field data can be fitted well by using the Gaussian mixture distribution with multivariables. There is a linear regression relation between the normalized discreteness as well as the coefficient of variation and both the factors including the bicycle lane width and the mean speed of the two types of bicycles. In addition, the results indicate that, there is linear regression relation between the total passing rate and both the factors including the average speed of electric-bicycles and the 15th percentile speed of traditional bicycles. There is also linear regression relation between the electric-bicycle passing rate and both the factors including the average speed of electric-bicycles and the vehicle speed variances.(3) The capacity of the bicycle way shared by E-bikes and R-bikesIn this chapter, eight traffic flow fundamental diagrams are developed for one-way bicycle way capacity estimation. A novel bicycle equivalent unit (BEU) estimation model and a verification method are also proposed, which are used to convert an E-bike to an R-bike equivalently. The results show that, there is a difference of estimated capacity between two or more different models of those eight traffic flow models. In addition, the results implied that the estimated capacity is affected by the statistical interval, the proportion of E-bikes and the proportion of the bicycles carrying men or objects. According to this study, the mean BEU for the E-bike is 0.66, and the converted capacities of pure regular bicycles and pure E-bikes are 1,800 and 2,727 bicycle/h per meter, respectively.(4) Models of the mixed bicycle traffic flowFrom a macro point of view, a volume-density relationship model of the mixed bicycle traffic flow is established based on the classical logistic model. The influence of the proportion of the E-bikes is studied. From a micro point of view, the Nagel-Schreckenberg (NS) cellular automaton (CA) model and the multi-value CA (M-CA) model are used to establish velocity-density model and volume-density model of the mixed bicycle traffic flow, respectively. The analysis and evaluation work of the two models are done in this chapter by using the field data. The results indicate that the macro model of the volume-density relationship can well describe the characteristics of the mixed bicycle traffic flow in different traffic states. The results also show that, the M-CA model is more suitable to describe the micro relations between the basic parameters of the mixed bicycle traffic flow.