US 12,462,675 B2
Traffic prediction system, traffic prediction method, and program
Masaki Yamada, Nagoya (JP); Yuji Tamura, Saitama (JP); Ryota Horiguchi, Matsudo (JP); and Koji Takahashi, Ichikawa (JP)
Assigned to TOYOTA JIDOSHA KABUSHIKI KAISHA, Toyota (JP)
Filed by TOYOTA JIDOSHA KABUSHIKI KAISHA, Toyota (JP)
Filed on Aug. 1, 2023, as Appl. No. 18/228,834.
Claims priority of application No. 2022-127344 (JP), filed on Aug. 9, 2022.
Prior Publication US 2024/0054889 A1, Feb. 15, 2024
Int. Cl. G08G 1/01 (2006.01)
CPC G08G 1/0125 (2013.01) 6 Claims
OG exemplary drawing
 
1. A traffic prediction system comprising:
hardware, including at least one memory configured to store a computer program and at least one processor configured to execute the computer program;
a traffic data acquisition unit, implemented by the hardware, configured to acquire traffic volume data indicating a relationship between a time and a traffic volume at a predetermined point;
a required time acquisition unit, implemented by the hardware, configured to acquire, for each of a plurality of routes, an actual value of a required time from a reference point of each of the plurality of routes to the predetermined point for a vehicle to arrive at the predetermined point via the route;
a traffic volume calculation unit, implemented by the hardware, configured to calculate an inflow traffic volume of vehicles flowing into each of the plurality of routes from the reference point for each of the plurality of routes, using the traffic volume data and the actual value of the required time;
a traffic state prediction unit, implemented by the hardware, configured to calculate, for each of the plurality of routes, a predicted value of the required time in view of the calculated inflow traffic volume and a predicted value of the required time when the inflow traffic volume is changed using a traffic model generated in advance; and
an amount of change calculation unit, implemented by the hardware, configured to calculate, for each of the plurality of routes, an amount of change in the predicted value of the required time when the inflow traffic volume is changed, wherein:
the traffic model is generated by adjusting parameters of the traffic model so as to reproduce the actual value of the required time in a case where the inflow traffic volume is input to the traffic model;
the parameters of the traffic model include a bottleneck capacity of each of the plurality of routes for each time, a value of the bottleneck capacity different each time; and
the traffic model reproduces the actual value of the required time including a holdup time obtained by dividing a first value, obtained by subtracting the outflow accumulated traffic volume from the inflow accumulated traffic volume, by the bottleneck capacity.