Toyota jidosha kabushiki kaisha (20240112571). CONGESTION PREDICTION DEVICE, CONGESTION PREDICTION METHOD, AND STORAGE MEDIUM simplified abstract

CONGESTION PREDICTION DEVICE, CONGESTION PREDICTION METHOD, AND STORAGE MEDIUM

Organization Name

toyota jidosha kabushiki kaisha

Inventor(s)

Ayumu Shiomi of Toyota-shi (JP)

Atsushi Miyagawa of Toyota-shi (JP)

Hiroki Takeuchi of Toyota-shi (JP)

Toshiyuki Kawai of Kariya-shi (JP)

Ryosuke Fukaya of Toyota-shi (JP)

Hiroyuki Tokita of Toyota-shi (JP)

Yusuke Ikenoue of Takahama-shi (JP)

Tsukasa Kato of Toki-shi (JP)

Katsuhisa Yoshikawa of Miyoshi-shi (JP)

Yuta Ichijyo of Toyota-shi (JP)

Takayuki Akaishi of Toyota-shi (JP)

Shintaro Kawai of Toyota-shi (JP)

CONGESTION PREDICTION DEVICE, CONGESTION PREDICTION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240112571 titled 'CONGESTION PREDICTION DEVICE, CONGESTION PREDICTION METHOD, AND STORAGE MEDIUM

Simplified Explanation

The patent application describes a congestion prediction device and method that utilizes machine learning to predict the degree of congestion in a specific area based on input variables related to congestion levels at regular time intervals.

• The mapping in the device outputs a variable indicating the degree of congestion in a specific area.
• Input variables include congestion variables representing congestion levels at regular time intervals within a specific period.
• The output variable predicts the degree of congestion after a lapse of the regular time interval from the end time of the specific period.

Potential Applications

This technology could be applied in traffic management systems, urban planning, and logistics to predict congestion levels in specific areas and optimize routes and schedules accordingly.

Problems Solved

This technology addresses the challenge of accurately predicting congestion levels in advance, allowing for better decision-making in managing traffic flow and resource allocation.

Benefits

The benefits of this technology include improved efficiency in transportation systems, reduced travel times, and enhanced overall traffic management strategies.

Potential Commercial Applications

A potential commercial application of this technology could be in the development of smart city solutions for traffic optimization and urban planning.

Possible Prior Art

One possible prior art for this technology could be existing traffic prediction systems that use historical data and algorithms to forecast congestion levels.

How does the device handle real-time data updates to improve prediction accuracy?

The patent application does not specify how the device incorporates real-time data updates to enhance congestion prediction accuracy. This could be a crucial aspect to consider for practical implementation in dynamic traffic environments.

What measures are in place to ensure data privacy and security in the congestion prediction process?

The patent application does not mention any specific measures for data privacy and security in the congestion prediction process. Ensuring the protection of sensitive information and compliance with data regulations would be essential for widespread adoption of this technology.

Original Abstract Submitted

a congestion prediction device, a congestion prediction method, and a storage medium are provided. a mapping outputs an output variable when input variables are input to the mapping. the output variable indicates a degree of congestion in a predetermined specific area. the mapping is learned in advance by machine learning. the input variables include congestion variables. each of the congestion variables indicates a degree of congestion in the specific area at regular time intervals within a specific period. the output variable indicates a degree of congestion after a lapse of the regular time interval from an end time of the specific period.