Data-Driven City Traffic Planning Simulation

被引：1

作者：

Nguyen, Tam, V ^{[1
]}

Thanh Ngoc-Dat Tran ^{[2
]}

Viet-Tham Huynh ^{[2
]}

Bao Truong ^{[1
]}

Minh-Quan Le ^{[2
]}

Kumavat, Mohit ^{[1
]}

Patel, Vatsa S. ^{[1
]}

Mai-Khiem Tran ^{[3
]}

Minh-Triet Tran ^{[3
]}

机构：

[1] Univ Dayton, Dept Comp Sci, Dayton, OH 45469 USA

[2] Vietnam Natl Univ, Univ Sci, Ho Chi Minh City, Vietnam

[3] Vietnam Natl Univ, John von Neumann Inst, Univ Sci, Ho Chi Minh City, Vietnam

来源：

2022 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY ADJUNCT (ISMAR-ADJUNCT 2022) | 2022年

基金：

美国国家科学基金会;

关键词：

Data-driven; computer vision; simulation; user experience; evaluation; TIME;

D O I：

10.1109/ISMAR-Adjunct57072.2022.00185

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Big cities are well-known for their traffic congestion and high density of vehicles such as cars, buses, trucks, and even a swarm of motorbikes that overwhelm city streets. Large-scale development projects have exacerbated urban conditions, making traffic congestion more severe. In this paper, we proposed a data-driven city traffic planning simulator. In particular, we make use of the city camera system for traffic analysis. It seeks to recognize the traffic vehicles and traffic flows, with reduced intervention from monitoring staff. Then, we develop a city traffic planning simulator upon the analyzed traffic data. The simulator is used to support metropolitan transportation planning. Our experimental findings address traffic planning challenges and the innovative technical solutions needed to solve them in big cities.

引用

页码：859 / 864

页数：6

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