Three national first prizes!Tongji students, good!

Recently, the 17th National College Student Transportation Technology Contest, hosted by the China Traffic Education Research Association and the Ministry of Education's Transportation Professional Teaching Guidance Committee, has come to a successful conclusion. Excellent works from colleges and universities across the country stand out, and 37 first prizes, 74 second prize works, and 101 third prize works. Among them, Tongji University won three first prizes and 3 second prizes.

The theme of this competition is "Digital Wisdom Transportation, Low -Carbon Transport", and there are "traffic engineering and comprehensive transportation", "navigation technology", "road transportation and engineering", "waterway transportation and engineering", "railway transportation and engineering" "Engineering" and seven categories of theme competition "Digital Wisdom Transportation and Low -Carbon Transport".

Tongji

First prize work

01

Transportation engineering and comprehensive traffic works

Project name: "Method for the construction of vehicle trajectory construction under highway under non -complete perception data"

(Effective completion of the lack of vehicle trajectory, empowering vehicle road collaboration)

instructor:

Professor Du Yuchuan (School of Transportation Engineering)

Associate Researcher Zhao Cong (School of Transportation Engineering)

team member:

Zhong Lingyun, Zeng Zimu, and Bian Qingjie of the School of Transportation Engineering 2019

Wang Shirui, a 2019 undergraduate student of the School of Electronics and Information Engineering

Project Description:

The actual situation of this project for the East China Sea Bridge, according to the video and radar data collected by the road -side perception unit, combine the classic theory and artificial intelligence of traffic flow, using sensor integration, vehicle heavy recognition and vehicle trajectory prediction technology, and proposed a set of road -based road -based ways The trajectory reconstruction method of the global vehicle trajectory with non -complete perception information has solved the three major problems: difficulty fusion in the existing research, the difficulty of cross -domain tracking of the vehicle, and the difficulty of completing the overall trajectory. It can provide data quality improvement in massive road sensors and service construction services to promote high -quality development of vehicle and road coordination.

02

Theme competition "Digital Wisdom Transportation, Low -Carbon Transportation" works

Project name: "Public Transport" Vision " -Recognition of Delay Factors based on machine vision"

(Real -time detection of bus delays environmental elements, automated identification delay causes)

instructor:

Professor Yuxiong (School of Transportation Engineering)

team member:

Grade 2020 undergraduate students at the School of Transportation Engineering

Lu Yali, Zheng Dani, Chai Yuezhang, Deng Liuying, Li Jizheng

Project Description:

This project focuses on the frequent issue of ground buses. It proposes to make full use of the existing vehicle monitoring video data to effectively make up for the defects that cannot obtain operating environment information in real time. The project adopts the multi -target tracking of YOLO network and monocular camera distance measurement and other machine visual technologies. It is targeted at the low -speed period of the bus and in -vehicle monitoring videos of the bus operation. The accurate "automatically recognizes the delays of the bus operation, providing an important basis for the accurate formulation of public transportation management and control strategies and scheduling.

In addition, the project has set up data processing, analysis and visualization platforms, and based on Jiading 9 bus videos to conduct testing and verification of the project content. Verification shows that the results of the project can not only feedback the delayed delays in real time, but also provide reliable technical support for real -time and offline applications for the timely and offline applications of the prompt response and processing of emergencies, the optimization of site selection and layout.

03

Transportation engineering and comprehensive traffic works

project name:

"Research on the Reaction Mechanism and Performance Optimization of Novice Drivers in the L3 Level Level Level Autonomous Driving Environment" (in -depth analysis of the novice driver's reception mechanism to help the development of autonomous driving safety)

instructor:

Associate Professor Chai Chen (School of Transportation Engineering)

team member:

School of Transportation Engineering 2019 undergraduate students

Lian Yanxi, Zhao Yiyue, Weng Shixuan

Project Description:

This project conducts a joint driving experiment based on the driving simulation platform to carry out an emergency cut -off scenarios, and extracts the physiological and behavioral data of novice drivers. First of all, the significant factor affecting the receiving process was judged. Secondly, based on the structural causal model, the novice driver took over the reaction mechanism, and finally improved the risk perception of novice drivers through cognitive intervention.

The project research results have widespread prospects in the aspects of driving test training test improvement and the improvement of autonomous driving product user manuals.

Source: School of Transportation Engineering

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