Research on Data Fitting of key Model for Traffic Flow

نویسنده

  • Jian-ming Cui
چکیده

For the study of traffic flow, a number of factors for traffic flow is difficult to accurate description variables with specific parameters, but in similar circumstances, traffic flow volume change with approximately in the form of periodic changes, the development of change over time. Therefore, using the method of data fitting the traffic flow is forecast to be a more effective way to. In the article, fit the road resistance and road traffic flow, to accurately determine the parameters of the road resistance and the mathematical expressions of the traffic flow, fitting results are accurate response to changes in traffic flow values. The results facilitate the provision of traffic management on roads in different traffic flow control, to avoid the road congestion in the area. Improve prediction accuracy in the application of the road traffic.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways

The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...

متن کامل

The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways

The performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...

متن کامل

A neuro-fuzzy approach to vehicular traffic flow prediction for a metropolis in a developing country

Short-term prediction of traffic flow is central to alleviating congestion and controlling the negative impacts of environmental pollution resulting from vehicle emissions on both inter- and intra-urban highways. The strong need to monitor and control congestion time and costs for metropolis in developing countries has therefore motivated the current study. This paper establishes the applicatio...

متن کامل

Traffic Condition Detection in Freeway by using Autocorrelation of Density and Flow

Traffic conditions vary over time, and therefore, traffic behavior should be modeled as a stochastic process. In this study, a probabilistic approach utilizing Autocorrelation is proposed to model the stochastic variation of traffic conditions, and subsequently, predict the traffic conditions. Using autocorrelation of the time series samples of density and flow which are collected from segments...

متن کامل

Developing a Model of Heterogeneity in Driver’s Behavior

Intelligent Driver Model (IDM) is a well-known microscopic model of traffic flow within the traffic engineering societies. While it is a powerful technique for modeling traffic flows, the Intelligent Driver Model lacks the potential of accommodating the notion of drivers’ heterogeneous behavior whenever they are on roads. Concerning the above mentioned, this paper takes the lane to recognize th...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • JDCTA

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2010