Research on intelligent prediction of train operation adjustment

Jing Shi

doi:10.1117/12.2637026

8 May 2022 Research on intelligent prediction of train operation adjustment

Jing Shi

Proceedings Volume 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）; 122493G (2022) https://doi.org/10.1117/12.2637026
Event: 2022 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 2022, Xiamen, China

Abstract

The adjustment of train operation is the core issue of train dispatching and commanding. The train operation runs in the predetermined sequence, and the orderly operation sequence is the key to the safety, efficiency and punctuality of the train. However, during the actual operation of the train, the train may be delayed due to equipment failure, extreme weather or human-induced deviation of the train operation from the plan. In order to ensure that the train operation returns to normal as soon as possible, the train operation may be adjusted globally. Based on the big data of train operation, this paper builds an intelligent prediction model for train operation adjustment, and predicts whether the train needs to overrun and other adjustments. It has been verified that the prediction model can achieve a good prediction effect. Model realization The big data based on scheduling experience provides scheduling decision assistance for schedulers, which is the basis for the realization of intelligent scheduling.

Citation Download Citation

Jing Shi "Research on intelligent prediction of train operation adjustment", Proc. SPIE 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 122493G (8 May 2022); https://doi.org/10.1117/12.2637026

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available