交通元胞机模型的Python实现
时间: 2023-11-29 19:53:50 浏览: 183
交通元胞机模型是一种用于模拟交通流动的计算模型,它基于细胞自动机模型,通过将道路划分成小的单元(细胞)来模拟车辆在道路上的运动。下面是一个简单的交通元胞机模型的Python实现:
```python
import numpy as np
import random
# 定义道路长度和车道数
length = 100
lanes = 3
# 定义车道宽度和车辆长度
lane_width = 4
vehicle_length = 5
# 定义车速和加速度
max_speed = 20
acceleration = 1
# 定义车辆密度和交通灯周期
density = 0.3
light_cycle = 10
# 定义道路状态
road = np.zeros((length, lanes))
# 定义车辆类
class Vehicle:
def __init__(self, lane, position, speed):
self.lane = lane
self.position = position
self.speed = speed
# 初始化车辆
vehicles = []
for lane in range(lanes):
for position in range(length):
if random.uniform(0, 1) < density:
speed = random.randint(0, max_speed)
vehicle = Vehicle(lane, position, speed)
vehicles.append(vehicle)
road[position, lane] = 1
# 定义交通灯状态
light = 0
# 定义车辆运动函数
def move(vehicles):
for vehicle in vehicles:
# 计算前方车辆距离和速度差
lead_distance = 0
lead_speed = 0
for i in range(1, max_speed):
if road[(vehicle.position + i) % length, vehicle.lane] == 1:
lead_distance = i - 1
lead_speed = vehicles[(vehicles.index(vehicle) + i - 1) % len(vehicles)].speed
break
speed_difference = lead_speed - vehicle.speed
# 根据速度差计算加速度
if speed_difference >= 0:
acceleration = min(speed_difference, vehicle.speed)
else:
acceleration = min(-speed_difference, max_speed - vehicle.speed)
# 更新车速和位置
vehicle.speed = min(vehicle.speed + acceleration, max_speed)
vehicle.position = (vehicle.position + vehicle.speed) % length
# 更新道路状态
road[:, vehicle.lane] = 0
for i in range(vehicle_length):
road[(vehicle.position + i) % length, vehicle.lane] = 1
# 定义交通灯函数
def toggle_light():
global light
light = (light + 1) % light_cycle
# 模拟车辆运动
for t in range(100):
if light == 0:
toggle_light()
for i in range(light_cycle):
move(vehicles)
if light == i:
vehicles = sorted(vehicles, key=lambda x: x.position)
for vehicle in vehicles:
if vehicle.position >= length - 5:
vehicles.remove(vehicle)
road[:, vehicle.lane] = 0
toggle_light()
```
上述代码使用numpy数组来表示道路状态,使用Python类来表示车辆,并通过move函数来模拟车辆的运动。同时,还定义了toggle_light函数来控制交通灯的状态,并在模拟过程中实现了对交通灯状态的切换。
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