Overview of Intelligent Transportation Systems

Ulsoy, A. Galip; Peng, Huei; Çakmakçı, Melih

doi:10.1017/cbo9780511844577.022

Automotive Control Systems 2012

DOI: 10.1017/cbo9780511844577.022

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Overview of Intelligent Transportation Systems

A. Galip Ulsoy

Huei Peng

Melih Çakmakçı

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Cited by 2 publications

References 13 publications

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The Urban Arterial Traffic Flow Forecasting Based on BP Neural Network

Cao

Feng

2014

2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control

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Predictive analytics of the traffic flow is paid more attention by the traffic engineering experts and relevant departments. However, how to forecast traffic volume still is an important problem affecting the traffic theoretical and practical analysis. Firstly, this paper set up a three layers BP neural network basing on the actual situation to introduce the modeling process of the neural network in detail, and forecast the short-term traffic volume by the means of rolling forecast. Secondly, taking the Hailar Street in Hohhot for example, two groups of test data from the same time of different days and sequent time of the same day were trained and forecast. in addition, predicting results and actual results were compared, and the correlations between test data and predicting result was analyzed and disclosed. Finally, the conclusion shows the error is acceptable and BP Neural Network constructed is practical when prediction accuracy is not very high.

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The Urban Arterial Traffic Flow Forecasting Based on BP Neural Network

Cao

Feng

2014

2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control

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An Improved Actuated Signal Control of Intersection Based on VISVAP

Guo

2016

Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering

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Traffic congestion has become an inevitable problem in modern society, and the signal control of intersection plays an important role to ensure the effective operation of urban transport. The paper proposes an improved actuated signal control model to improve the running efficiency of intersection. In order to verify the effectiveness of the improved algorithm，the paper uses VISSIM to simulate the operating condition of different durations under timing control, actuated signal control and improved actuated signal control based on actual traffic flow, signal timing and other data of intersection. The simulation result shows that travel time and delay time are both reduced under the control of actuated signal in different time periods. And the improved actuated signal control is more effective than other signal controls.

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Overview of Intelligent Transportation Systems

Cited by 2 publications

References 13 publications

The Urban Arterial Traffic Flow Forecasting Based on BP Neural Network

The Urban Arterial Traffic Flow Forecasting Based on BP Neural Network

An Improved Actuated Signal Control of Intersection Based on VISVAP

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