Mr. Libin Zhu Profile

Libin Zhu

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Proceedings Article | 9 April 2024 Paper

Research on the calculation method of delay value for intelligent connected passenger vehicles

Yan Zhao, Cheng Zhang, Libin Zhu

Proceedings Volume 12989, 129890N (2024) https://doi.org/10.1117/12.3023981

KEYWORDS: Roads, Intelligence systems, Information operations, Transportation, Data processing, Telecommunications, Reflection, Operational intelligence, Machine learning, Data storage

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Externality is one of the important issues in the field of transportation economics research. With the development of intelligent connected vehicles, the efficiency of public transportation continues to improve. But congestion problems cannot be completely avoided, and congestion delays increase travel costs. How to accurately calculate the delay time of vehicles and effectively quantify the economic value of delay time is one of the important issues that need to be solved in the future development process of intelligent transportation systems. In order to effectively quantify the external costs of traffic congestion in the context of intelligent networking, this paper proposes a method for calculating the value of delay of intelligent connected passenger vehicles based on vehicle road collaboration data. By comparing the difference between the time when intelligent connected passenger vehicles pass through the starting and ending points of the road link at actual speed and the time when they travel at the speed limit of the road link, the delay time can be calculated based on the number of passengers carried by the passenger vehicle. The unit time price factor is calculated based on the annual per capita GDP of the region, and then the value of delay of intelligent connected passenger vehicles operation is solved. Finally, an example analysis was conducted on the road network of X city, and it was found that the average daily delay value generated by intelligent connected passenger vehicles passing through the road network was ¥28453, and the average congestion delay value generated per kilometer per hour was ¥6.23, thus verifying the rationality of the calculation method. This method provides a reference for formulating road congestion pricing strategies in the context of intelligent networking.

Proceedings Article | 9 April 2024 Paper

Autonomous driving expected functional safety hazard identification method based on the Mealy state machine

Tianyi Zhu, Libin Zhu, Tingting Wu, Wenchen Xu

Proceedings Volume 12989, 1298905 (2024) https://doi.org/10.1117/12.3023886

KEYWORDS: Autonomous vehicles, Safety, Hazard analysis, Autonomous driving, Logic, Control systems, Roads, Unmanned vehicles, Environmental sensing, Information security

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Aiming at the strong correlation between the hazards of the autonomous driving system of intelligent networked vehicles and the operating environment and control action, this paper proposes a method for identifying hazards of the expected functional safety of autonomous driving based on a mealy state machine. Firstly, the vehicle action rule base is determined by the operating environment of the vehicle and the available control action; secondly, the mapping between the mealy state machine and the vehicle operating state is established to simulate the vehicle state operation logic in the real scene; finally, by identifying the relationship between the vehicle state and the Conflicts between the operating environment and control actions identify potential hazards. In order to verify the effectiveness of the proposed method, this paper identifies 257 potential hazards through the identification of the expected functional safety hazards of the ACC system of a L2 vehicle, which is more efficient and convenient compared with the traditional STPA method.

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