Traffic Flow Characteristic Parameter Models Of Urban Expressways Based On Physical Properties

ABSTRACT:With the development of road networks in megacities, expressways have become the urban traffic artery and played an irreplaceable role in urban transportation systems. Developing the dynamic traffic model and assessing the dynamic traffic states is the important foundation for the implementation of traffic management and optimization for not only expressway systems but the entire road network of a megacity as well. The determination of the calibration parameters of the road network supply capacity in the dynamic traffic model, e.g. the traffic flow characteristic parameters of each road section of expressways in the road network including the free flow speed, capacity, critical speed and jam density, is the key to the accurate assessment of dynamic traffic states. The traditional method in estimating traffic flow characteristic parameters needs to obtain 24h traffic flow data of sections, select traffic stream model which is suitable to describe the traffic flow characteristics of expressways, and conduct curve fitting. However, since most of road sections of expressways do not have detectors, and the traffic flow data sample could not be obtained in each traffic state in several detected road sections, the traditional method in estimating traffic flow characteristic parameters that has heavily relied on traffic flow data is hardly applied in practice. Moreover, since traffic characteristics of expressways are more complex than those of other classes of roads because of the high densities of ramps and bus stops, the applicability of existing traffic stream models, which have been developed primarily for freeways, should be examined.In this context, the research in this dissertation strives to develop traffic flow characteristic parameter models of urban expressways based on physical properties. After a quantitative analysis of traffic characteristics of expressways, it presents a new approach to deriving traffic flow characteristic parameters directly from physical characteristic parameters of expressways. As a result, the application-oriented traffic flow characteristic parameter models of expressways based on physical properties are developed. The research in the dissertation consists of the following accomplishments:1. Quantitative analyses of traffic flow characteristics of expressways are conducted, and formulas that transform the time mean speed to the space means speed and the occupancy to the density are proposed. Using the Van Aerde single-regime model, which is considered suitable for expressways, the dissertation analyzed and compared deterministic traffic flow characteristic parameters of the basic section, the section near ramps and the section near bus stops based on the comprehensive analysis of traffic flow characteristic parameters of expressways,. The algorithm for the selection of the range of capacities based on the Bound-line analysis is proposed and the stochastic distribution analysis of capacity is conducted. The analysis of the field data indicates that the capacity of expressways follows the Gamma distribution and Lognormal distribution.2. A framework for building traffic flow characteristic parameter models for expressways based on physical properties is established in order to identify direct functions between physical characteristic parameters and each of traffic flow characteristic parameters. The framework includes two essential modules, the character matrix cluster analysis of sections and the development of the traffic flow characteristic parameter models on expressways.3. The character matrix clustering model for sections on the expressway is established, attempting to select the sectional samples with a high correlation between physical and traffic flow characteristics. The relevant achievements include:(1) basic physical characteristic parameters of expressways that consider both series of ramps and transit facilities are identified; (2) based on the SAGA-K Means cluster algorithm, the character matrix cluster model of the section on the expressway is established; and (3) a cluster matching model for dual sources of data for expressways is developed by considering the physical characteristic data and traffic flow characteristic data as two sources of data,4. The traffic flow characteristic parameter models for the section on the expressway based on physical properties are developed. The relevant achievements include:(1) on the basis of basic physical characteristic parameters, the physical characteristic parameters incorporating the ramp comprehensive index and the transit comprehensive index are proposed; and (2) using samples with a high correlation, the multivariate models of physical characteristic parameters and traffic flow characteristic parameters are developed, and the parameter estimation and model validation are conducted.5. Using the dynamic traffic model of the western 3rd ring-road expressway corridor of Beijing as the basic platform, the proposed traffic flow characteristic parameter models are tested. The results indicate that, with the high densities of ramps and transit facilities and in the absence of valid observed traffic flow data, calibrating the dynamic traffic model by the proposed traffic stream model could better capture the traffic flow characteristics of expressways than could the traditional method that uses the uniform traffic flow characteristic parameters.