Award type：Award from international society, conference, symposium, etc.  Country：Portugal

Language：Japanese   Publisher：Computer Systems Science and Engineering  

Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians' sudden appearance in the vehicle's path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision digital map of the parking lot, pedestrians' smart device's sensing data, and attribute information of pedestrians can be used to detect the position of pedestrians in the parking lot. However, this subject has not been studied and explored in existing studies. To fill this void, this paper proposes a pedestrian tracking framework integrating multiple information sources to provide pedestrian position and status information for vehicles and protect pedestrians in parking spaces. We also evaluate the proposed method through real-world experiments. The experimental results show that the proposed framework has its advantage in pedestrian attribute information extraction and positioning accuracy. It can also be used for pedestrian tracking in parking spaces.

DOI： 10.32604/csse.2023.029005

Web of Science

Scopus

Language：Japanese   Publisher：The Japan Joint Automatic Control Conference  

DOI： 10.11511/jacc.66.0_1147

CiNii Research

Language：Japanese   Publisher：International Journal of Intelligent Transportation Systems Research  

In the early stages of the spread of autonomous vehicles, it is conceivable to operate an automated valet parking system in parking lots where autonomous vehicles and non-autonomous vehicles coexist. Since non-autonomous vehicles may park beyond the parking space, it is necessary to estimate parking space conditions three-dimensionally. This paper proposes a method to estimate the parking space conditions using multiple 3D-LiDARs that can detect the space three-dimensionally. In the evaluation experiment, multiple 3D-LiDARs were installed in the parking lot of a public facility, and the estimation accuracy of the proposed method was evaluated in various situations.

DOI： 10.1007/s13177-022-00300-w

Web of Science

Scopus

Language：Japanese   Publisher：Journal of Navigation  

Vehicle state estimation and path prediction, which usually involve Kalman filter and motion model, are critical tasks for intelligent driving. In vehicle state estimation, the comparative performance assessment, regarding accuracy and efficiency, of the unscented Kalman filter (UKF) and the extended Kalman filter (EKF) is rarely discussed. This paper is devoted to empirically evaluating the performance of UKF and EKF incorporating different motion models and investigating the models' properties and the affecting factors in path prediction. Extensive real world experiments have been carried out and the results show that EKF and UKF have roughly identical accuracy in state estimation; however, EKF is faster than UKF generally; the fastest filter is about 2â 6 times faster than the slowest. The path prediction experiments reveal that the velocity estimate and the used motion model affect path prediction; the more realistically the model reflects the vehicle's driving status, the more reliable its predictions.

DOI： 10.1017/S0373463321000370

Web of Science

Scopus

Language：Japanese   Publisher：IEEE Internet of Things Journal  

The Internet of Things plays an indispensable role in the development of connected vehicles, which will pave the way for road safety applications. In recent years, the concept of a cooperative collision warning system (CCWS) has been introduced and developed to enhance road safety, and it has been seen as a typical Internet-of-Vehicles application. In most CCWSs, it is vital to have a detection mechanism based on trajectory predictions where the uncertainties associated with vehicular state and motion are complex. However, most available approaches in this regard did not consider these uncertainties. Hence, this article proposes a new collision risk assessment (CRA) method where sigma trajectories that include multiple possible trajectories considering multiple aspects of vehicular motion are designed to cope with vehicular uncertainties. Our method is implemented in a novel server-based architecture, which is different from the commonly used vehicle-based controlled CCWSs. The CRA is provided as a service by a cloud server. The proposed method and architecture are validated and evaluated through extensive real-world experiments. Experimental results show that our method outperforms a referenced method in terms of CRA and achieves better robustness in tolerating communication delays and dropouts. Latencies in CRA service were analyzed, and it was found that powerful computing resources provided by cloud servers can significantly decrease computational cost, which will indirectly compensate for communication costs in the future. Based on our high-performance CRA method, the proposed architecture can be regarded as a novel option for CCWS design.

DOI： 10.1109/JIOT.2021.3059222

Web of Science

Scopus

Event date： 2024.2 - 2024.3

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：愛知県   Country：Japan  

Event date： 2023.12

Language：Japanese   Presentation type：Poster presentation  

Venue：富山  

Event date： 2023.10

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東北大学川内キャンパス  

Event date： 2023.9

Event date： 2023.9 - 2923.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：仙台国際センター