摘要
A novel conditional cell transmission model (CCTM) is a potential simulation tool because it accommodates all traffic conditions from light condition to oversaturated condition.To test the performance of the CCTM,a series of experiments for sensitivity analysis were designed and performed for a multilane,two-way,three-signal sample network.Experiment 1 shows that the model is performed in a logical and expected manner with variations in traffic demand with time and direction.Experiment 2 shows when the possibility of the occurrence of a useful gap increases to 60% and 100%,the delays in left turns decrease by 5% and 15%,respectively.In Experiment 3,comparing the possibility of a conditional cell of 0 with 100%,delay of left turn and delay of the entire network were underestimated by 58% and 11%,respectively.Hence,sensitivity analysis demonstrates that by reflecting local drivers' behaviors properly,the CCTM provides an accurate representation of traffic flow in simulating oversaturated traffic conditions.
A novel conditional cell transmission model （CCTM） is a potential simulation tool because it accommodates all traffic conditions from light condition to oversaturated condition. To test the performance of the CCTM, a series of experiments for sensitivity analysis were designed and performed for a multilane, two-way, three-signal sample network. Experiment 1 shows that the model is performed in a logical and expected manner with variations in traffic demand with time and direction. Experiment 2 shows when the possibility of the occurrence of a useful gap increases to 60% and 100%, the delays in left rams decrease by 5% and 15%, respectively. In Experiment 3, comparing the possibility of a conditional cell of 0 with 100%, delay of left turn and delay of the entire network were underestimated by 58% and 11%, respectively. Hence, sensitivity analysis demonstrates that by reflecting local drivers＇ behaviors properly, the CCTM provides an accurate representation of traffic flow in simulating oversaturated traffic conditions.
基金
Project(51108343)supported by the National Natural Science Foundation of China
Project(06121)supported by University of Transportation Center for Alabama,USA
