CAJ | 학술논문

车辆进入交叉口前的速度时间序列可用于预测车辆进入交叉口后若干步数速度值,利用车速预测值推算冲突方向车辆在交叉口内的行驶位移及其车间距离,可评估车辆发生碰撞的风险.针对交叉口附近车速分布符合随机序列特征,采用自回归滑动平均(ARMA)理论进行车速时序预测建模,步骤包括时序数据相关性检查、模型p-q定阶、解析式系数估计、适用性检验.试验结果表明:利用实测车速中的前40个时序数据建立ARMA模型,预测出的20个车速值与实测值贴近,冲突方向两车车速归一化平均绝对误差分别为0.006 56和0.003 4;利用全部60个实测数据建立预测模型,检测预测值残差自相关函数发现其绝对值均小于0.258 2,表明所建车速预测方法适用.
차량진입교차구전적속도시간서렬가용우예측차량진입교차구후약간보수속도치,이용차속예측치추산충돌방향차량재교차구내적행사위이급기차간거리,가평고차량발생팽당적풍험.침대교차구부근차속분포부합수궤서렬특정,채용자회귀활동평균(ARMA)이론진행차속시서예측건모,보취포괄시서수거상관성검사、모형p-q정계、해석식계수고계、괄용성검험.시험결과표명:이용실측차속중적전40개시서수거건립ARMA모형,예측출적20개차속치여실측치첩근,충돌방향량차차속귀일화평균절대오차분별위0.006 56화0.003 4;이용전부60개실측수거건립예측모형,검측예측치잔차자상관함수발현기절대치균소우0.258 2,표명소건차속예측방법괄용.
Speed time series collected as vehicles approaching an intersection can be used to predict several speed values as they subsequently entering it. Then, traveling tracks and spacing distances of the conflict vehicles are calculated by the predicted speed values, and the collision risk of them can be estimated. Because the speed distribution of a vehicle approaching to an intersection closes to the characteristics of random sequences, auto-regressive moving average (ARMA) theory is introduced to model the vehicle speed prediction. The modeling process includes time series data correlation test, p-q orders determination, formula coefficient estimation and model adaptability test. Test result shows that the ARMA model built by the previous 40 data of the observed speed time series could predict 20 values which are closed to the 20 observed ones. The other evidences of that are the normalized mean absolute errors of the conflict vehicles, which respectively equaled to 0.006 56 and 0.003 4. Further, the model built by all the 60 data of the observed time series is necessarily more applicable to predict vehicle speed, just as all the result values of the residual auto-correlation function test are less than 0.258 2.