宁波大学学报(理工版)
寧波大學學報(理工版)
저파대학학보(리공판)
JOURNAL OF NINGBO UNIVERSITY(NSEE)
2014年
2期
30-34
,共5页
交通流模型%元胞自动机%恶劣天气%驾驶行为%交通拥堵
交通流模型%元胞自動機%噁劣天氣%駕駛行為%交通擁堵
교통류모형%원포자동궤%악렬천기%가사행위%교통옹도
traffic model%cellular automaton%inclement weather condition%driving behavior%traffic congestion
基于 NaSch 模型提出了一个改进的元胞自动机交通流模型,旨在反映雨雪天气时道路湿滑能见度差的情况下司机驾驶车辆更加谨慎的特点。考虑谨慎司机的不同比例,通过数值模拟得到了一组基本图,发现含有不同比例的谨慎司机对交通流产生不同程度的影响。并通过车辆的时空演化图,从微观的角度对恶劣天气时交通流的非线性特性进行了细致的分析,揭示了在雨雪等恶劣环境下更容易出现交通拥堵的机理,与实际交通特征相吻合。因此模型能够部分地反映恶劣天气时交通流的微观特性,同时也证明了司机的驾驶行为对交通拥堵的形成确实具有重要的影响。
基于 NaSch 模型提齣瞭一箇改進的元胞自動機交通流模型,旨在反映雨雪天氣時道路濕滑能見度差的情況下司機駕駛車輛更加謹慎的特點。攷慮謹慎司機的不同比例,通過數值模擬得到瞭一組基本圖,髮現含有不同比例的謹慎司機對交通流產生不同程度的影響。併通過車輛的時空縯化圖,從微觀的角度對噁劣天氣時交通流的非線性特性進行瞭細緻的分析,揭示瞭在雨雪等噁劣環境下更容易齣現交通擁堵的機理,與實際交通特徵相吻閤。因此模型能夠部分地反映噁劣天氣時交通流的微觀特性,同時也證明瞭司機的駕駛行為對交通擁堵的形成確實具有重要的影響。
기우 NaSch 모형제출료일개개진적원포자동궤교통류모형,지재반영우설천기시도로습활능견도차적정황하사궤가사차량경가근신적특점。고필근신사궤적불동비례,통과수치모의득도료일조기본도,발현함유불동비례적근신사궤대교통유산생불동정도적영향。병통과차량적시공연화도,종미관적각도대악렬천기시교통류적비선성특성진행료세치적분석,게시료재우설등악렬배경하경용역출현교통옹도적궤리,여실제교통특정상문합。인차모형능구부분지반영악렬천기시교통류적미관특성,동시야증명료사궤적가사행위대교통옹도적형성학실구유중요적영향。
Based on the NaSch model of traffic flow, a modified cellular automaton traffic model is proposed. The model is attempted to reflect the characteristics of discreetness found in vehicle drivers under rain or snow weather condition. In the modeling process, the special driving condition of wet, slippery road and poor visibility are taken into account. The fundamental diagrams of traffic flow are obtained based on the numerical simulation, in which different percentage of discreet drivers is sampled. It is found that the percentile value of discreet drivers has effect on the traffic flow. By presenting the spatial-temporal profiles, the nonlinear properties of traffic flow in the inclement weather condition are analyzed thoroughly. It can be noted that traffic jams occur more frequently in rainy or snowy weather. It is in agreement with the actual traffic characteristics, so the presented model can also partly describe the microscopic characteristics of traffic flow in the inclement environment. The results demonstrate that the driver behavior has significant effect on the occurrence of traffic congestion.