Systems and methods for enhanced cellular automata algorithm for traffic flow modeling
View Patent ↗An embodiment generally relates to systems and methods for enhanced cellular automata (CA) models. A processing module can generate a traffic model that comprises a set of vehicles. The traffic model can be processed according to the enhanced CA model. In particular, a perceived gap between vehicles in the set of vehicles can be identified. Further, a subsequent velocity of a following vehicle can be calculated based on metrics such as a maximum velocity, the perceived gap, and various time components.
1. A method of simulating traffic, the method comprising:
generating a traffic model comprising a leading vehicle and a following vehicle;
identifying, in the traffic model, a perceived gap between the leading vehicle and the following vehicle;
calculating a current velocity of the following vehicle at a current time;
selecting, as an output, a minimum of a set
{
Vg
n
(
t
)
T
*
,
v
n
(
t
)
+
a
,
V
}
,
wherein V corresponds to a maximum velocity of the following vehicle, g n (t) corresponds to the perceived gap, T′ corresponds to a specified time parameter, v n (t) corresponds to the current velocity of the following vehicle, and a corresponds to an allowable maximum velocity change in a single time step; and
calculating, by a processor, a subsequent velocity of the following vehicle at a subsequent time step based on the maximum velocity of the following vehicle, the perceived gap, and the specified time parameter.
2. The method of claim 1 , wherein the subsequent velocity of the following vehicle is calculated using an equation
Vg
n
(
t
)
T
*
.
3. The method of claim 1 , wherein the perceived gap is calculated using an equation x n-1 (t)−x n (t)−s n-1 , wherein x n-1 (t) corresponds to a position of the leading vehicle, x n (t) corresponds to a position of the following vehicle, and s n-1 corresponds to a length of the leading vehicle.
4. The method of claim 1 , further comprising:
providing the output to a user.
5. The method of claim 1 , further comprising:
identifying at least one additional vehicle in the traffic model;
repeating the identifying and the calculating for the at least one additional vehicle; and
generating a data set based on the repeating.
6. The method of claim 1 , further comprising:
iterating a time step;
repeating the identifying and the calculating according to the time step; and
generating a data set based on the repeating.
7. The method of claim 6 , further comprising:
processing the data set to simulate a traffic flow within the traffic model.
8. The method of claim 6 , further comprising:
storing the data set in memory.
9. The method of claim 1 , wherein the leading vehicle is stationary.
10. The method of claim 1 , wherein the traffic model is used to model a traffic flow in a transportation infrastructure.
11. A system for simulating traffic, the system comprising:
a processor coupled to memory and configured to perform actions comprising:
generating a traffic model comprising a leading vehicle and a following vehicle;
identifying, in the traffic model, a perceived gap between the leading vehicle and the following vehicle;
calculating a current velocity of the following vehicle at a current time;
selecting, as an output, a minimum of a set
{
Vg
n
(
t
)
T
*
,
v
n
(
t
)
+
a
,
V
}
,
wherein V corresponds to a maximum velocity of the following vehicle, g n (t) corresponds to the perceived gap, T′ corresponds to a specified time parameter, v n (t) corresponds to the current velocity of the following vehicle, and a corresponds to a maximum allowable velocity change in a single time step; and
calculating a subsequent velocity of the following vehicle at a subsequent time step based on the maximum velocity of the following vehicle, the perceived gap, and the specified time parameter.
12. The system of claim 11 , wherein the subsequent velocity of the following vehicle is calculated using an equation
Vg
n
(
t
)
T
*
.
13. The system of claim 11 , wherein the perceived gap is calculated using an equation x n-1 (t)−x n (t)−s n-1 , wherein x n-1 (t) corresponds to a position of the leading vehicle, x n (t) corresponds to a position of the following vehicle, and s n-1 corresponds to a length of the leading vehicle.
14. The system of claim 11 , wherein the processor is further configured to perform actions comprising:
providing the output to a user.
15. The system of claim 11 , wherein the processor is further configured to perform actions comprising:
identifying at least one additional vehicle in the traffic model;
repeating the identifying and the calculating for the at least one additional vehicle; and
generating a data set based on the repeating.
16. The system of claim 11 , wherein the processor is further configured to perform actions comprising:
iterating a time step;
repeating the identifying and the calculating according to the time step; and
generating a data set based on the repeating.
17. The system of claim 16 , wherein the processor is further configured to perform actions comprising:
processing the data set to simulate a traffic flow within the traffic model.
18. The system of claim 16 , wherein the processor is further configured to perform actions comprising:
storing the data set in memory.
19. The system of claim 11 , wherein the leading vehicle is stationary.
20. The system of claim 11 , wherein the traffic model is used to model a traffic flow in a transportation infrastructure.