基于元胞自动机的双车道换道行为模拟方法

news/2025/11/24 16:25:11/文章来源:https://www.cnblogs.com/y4353536666/p/19264674

一、模型框架设计

双车道元胞自动机基础架构
- 空间离散化：将双车道划分为等距元胞（如7.5m/元胞），每车道包含N个元胞
- 车辆状态定义：
```
vehicle_state = struct('lane', 1, 'pos', 1, 'vel', 0, 'max_vel', 120); % 车道、位置、速度、最大速度
```
- 初始化参数：车辆密度：ρ = M/(2*N)（M为总车辆数）最大速度：Vmax = 120 km/h 安全距离：d_safe = 2元胞

换道决策规则

换道动机判断：

function motivation = check_motivation(vehicle, front_dist, other_lane_front_dist)if front_dist < 1.5*Vmax && other_lane_front_dist > front_distmotivation = 1; % 强动机elseif front_dist < Vmax && other_lane_front_dist > 0.8*front_distmotivation = 0.5; % 弱动机elsemotivation = 0; % 无动机end

换道可行性验证：

目标车道前后车距需满足：

d_front = vehicle.other_lane_front_dist - vehicle.vel;
d_rear = vehicle.other_lane_rear_dist + vehicle.vel;
if d_front > d_safe && d_rear > d_safefeasible = true;
elsefeasible = false;
end

演化更新规则

跟驰模型：

function new_vel = update_velocity(vehicle, front_vel)gap = vehicle.front_dist - vehicle.vel;if gap < 0new_vel = max(vehicle.vel - 2, 0); % 紧急制动elsenew_vel = min(vehicle.vel + 1, vehicle.max_vel); % 加速end

换道执行：

换道概率与动机强度相关：

P_change = 0.3 * motivation + 0.1; % 动机强度加权
if rand < P_change && feasiblevehicle.lane = 3 - vehicle.lane; % 切换至对向车道
end

二、参数获取方法

速度分布统计

实时记录每辆车的瞬时速度，计算：

avg_speed = mean([vehicles.vel]);
speed_variance = var([vehicles.vel]);

换道次数计算

每时间步统计成功换道车辆数：

lane_change_count = sum(vehicle.motivation > 0.5 & vehicle.feasible);

交通流参数计算
- 流量：Q = Σ(vehicle.vel)/Δt
- 密度：ρ = M/(2*N)
- 空间占有率：
```
occupancy = sum(vehicle.pos < N) / (2*N);
```

三、MATLAB仿真实现

%% 参数设置
N = 1000; % 每车道元胞数
M = 200;  % 总车辆数
Vmax = 120; % km/h
dt = 0.1; % 时间步长(s)%% 初始化
vehicles = struct('lane',{1,1}, 'pos',{randi([1,N],M,1)}, 'vel',{Vmax}, 'max_vel',{120});
for i = 1:Mvehicles(i).pos = vehicles(i).lane * N + randi([1,N-1]);
end%% 仿真循环
for t = 1:1000for i = 1:M% 前车检测front_idx = find_vehicle_ahead(vehicles, i);front_dist = vehicles(front_idx).pos - vehicles(i).pos - 1;% 换道动机判断motivation = check_motivation(vehicles(i), front_dist, ... get_other_lane_front_dist(vehicles, i));% 换道可行性验证feasible = check_feasibility(vehicles, i);% 执行换道if rand < 0.3*motivation && feasiblevehicles(i).lane = 3 - vehicles(i).lane;end% 跟驰规则更新vehicles(i).vel = update_velocity(vehicles(i), front_vel);vehicles(i).pos = vehicles(i).pos + vehicles(i).vel*dt;end% 数据记录record(t) = struct('speed', mean([vehicles.vel]), ...'lane_changes', sum([vehicles.motivation]>0.5));
end%% 结果可视化
plot(record.speed);
xlabel('时间步'); ylabel('平均速度(km/h)');
title('双车道速度演化');subplot(2,1,2);
bar([sum(record.lane_changes)/1000, mean(record.speed)]);
legend('换道率', '平均速度');