Research on vehicle travel trajectory reconstruction method based on massive bayonet data

Jun Li

doi:10.1117/12.2636955

8 May 2022 Research on vehicle travel trajectory reconstruction method based on massive bayonet data

Jun Li

Proceedings Volume 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）; 122492J (2022) https://doi.org/10.1117/12.2636955
Event: 2022 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 2022, Xiamen, China

Abstract

The integrity of motor vehicle travel trajectory is widely used in macro traffic management, vehicle travel prediction and traffic problem analysis[1]. However, in reality, due to the lack of transportation equipment and the complexity of the road, it is difficult to obtain a complete vehicle travel trajectory. Based on massive bayonet data, aiming at the phenomenon of incomplete vehicle travel trajectory, combined with SUMO (traffic system simulation software) platform, this paper establishes a dynamic routing algorithm model based on Astar [2] and Dijkstra [3], The index data combined with bayonet data is introduced into the model to increase the practicability of the model. Finally, the accuracy of the model is verified through the comparison of actual cases. Provide reliable data support for further research on traffic travel scheme.

Citation Download Citation

Jun Li "Research on vehicle travel trajectory reconstruction method based on massive bayonet data", Proc. SPIE 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 122492J (8 May 2022); https://doi.org/10.1117/12.2636955

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