| The current road traffic in Chinese urban areas is characterized as a mixed flow, which is mainly composed of motor vehicles, bicycles, and pedestrians. Conventional traffic flow theories and urban transportation planning processes have been focused on motor vehicles by allocating most road resources to this travel mode. As a result, mutual exclusion among different travel modes has gradually occurred and could exacerbate the polarized tendency. The importance of bicycles in urban transportation has been recognized over the past decade, and many countries have developed transportation policies to encourage cycling trips as a means of reducing traffic congestion. Under this premise, a daunting challenge is to allocate reasonable right-of-ways for all transportation modes, thus a transportation system can be most efficient by taking advantages of different transportation modes.To achieve the above objective, it is necessary to investigate bicyclist's unique features and to develop models to address the bicycle behavioral dynamics. Computer simulation models need to be developed to demonstrate the efficient use of road resources from the macroeconomic perspective. Bicyclist microcosmic behavior research has been highly regarded in the academic field, thus the proposed activities should contribute to advancing both theories and practices by adopting a system engineering approach. The outcome of the research would increase the understanding of bicycle traffic characteristics, improve the theoretical connotation of traffic behavior, and enhance the knowledge of microscopic traffic simulation. Meanwhile, the research also has great significance for promoting social fairness, improving current transportation system structure, and relieving traffic congestion.Built on the foundations of both theories and practice, this dissertation research specifically focused on bicyclist microcosmic behavior. The framework used to analyze the micro-behavior is established. In the framework, the riding process is broken down into a chain procedure from sensory perception to action. Accordingly, the continuous force model, which is composed of two sub-models, is proposed for studying the bicycle dynamics. The behavioral experimental approach is designed to collect data for calibrating and validating the model. Furthermore, the dynamic model is applied for the case of road resource allocation to demonstrate its potential applications. The following provides summary and major conclusions from this research: (1) A major discussion is given to describe the essential differences among bicycles, automobiles, and pedestrians from several viewpoints. The unique behavior patterns of bicycles are characterized. As the cognition theory analyzes the changing process from cyclist's received information to response, this study further suggests that the cyclist's behavior is a chaining individual component. A further analysis of cyclist's micro-behavior is carried out to construct the general framework that includes the elements of perception, behavior choice, and action.(2) This study extracts the bicycle/rider unit as a fundamental element, which is represented as an elliptical individual. During any kinetic process, an individual's visual perception plays a particularly important role. Hence, it is necessary to model the visual field which is dependent on velocity. Considering the movement of a bicycle is anisotropic, two smaller fields named reactive range and perceptive range, are proposed. The former is a speed-dependent domain, which indicates that an individual may take actions to avoid potential collisions with obstacles invaded in its reactive range. The latter is an invariant region, which implies that the obstacles could be felt within this range. To treat the individual as a self-determined object, a continuous Psychological-Physical Force Model (PPFM) is proposed to describe the perception behaviors. And the Psychological Force is a long-range force, including four terms: driving force, collision avoidance force, boundary force, and some attractive force. The physical force is an external pressure, resulting from contact force and sliding friction force.(3) The bicycle acts can be described as a top down hierarchical progression structure by analyzing the cyclist's behavior selection mechanism. Different riding behaviors can also be assigned with priorities, and they are mutually exclusive at a node of the same level. There is only one active node at one moment. From the individual's mind characteristics, it should consider different temperament types and different selection behaviors. The different behaviors are manifested in the perception fields, the extent of reaction field, the duration time, the response factor and the collision force direction etc. in the path choice behavior of the individual. By transforming an operational boundary into an equivalent movement individual, Finite-State Machine (FSM) is used to select a behavior library for different temperament types of a scheduled track. When density within a perception field is smaller than its critical density, an individual will select both sides to move to where the density is smaller. When density within the perception fields is greater than its critical density, different temperament types of individuals have different select behaviors. Choleric temperament individual and melancholic temperament individual will select the direction with smaller density to move; sanguine temperament individual will select the direction of faster speed; and lymphatic temperament individual will select the direction of higher flow.(4) Traffic behavior experiments are designed for the purpose of collecting necessary data for model calibration and validation. The micro data for the calibration and the macro data for verification are collected using videos. The bicycle kinetic trajectories from the video footage are extracted using the video jockey software. Then the microscopic behavior database of different temperature types is established to get the static and dynamic behavioral data under different boundary conditions. The four types of parameters namely desired speed, reaction coefficient, duration time, and collision avoidance strength are calibrated separately. The computer simulation models developed in this research demonstrate that the dynamic model is capable of describing the nonlinear forces between individuals and represents well the characteristics of bicycles behavior patterns. Furthermore, the fundamental diagram shows that the simulation results are in good agreement with the empirical data, and the stopping density is consistent with the results from previous research.(5) From the perspective of bicycle facilities, it proposes that the microscopic behavior model could be applied at the macroscopic level. Through simulation, it is estimated that, the bicycle way's capacity is about2400bicycle/h/m. Moreover, using Entropy of Speed State (ESS) as a micro index and density as a macro-indicator, a new method is proposed to define the level of service (LOS) for bicycle facilities. The linkage between macroscopic quantity and microscopic quantity is established to divide the LOS into six levels based on density. All these outcomes lead to a new bicycle road resource allocation method. Taking C-class LOS as the basis for road traffic design, it recommends5.0m as the maximum width for an urban bicycle way. When traffic demand is less than1800bicycle/h, a placement marking is recommended to separate different transportation modes.
|
PDF Full Text Request