Conditional cell transmission model for two-way arterials in oversaturated conditions

Abstract

In 2007, congestion caused urban Americans to travel 4.2 billion hours more and to purchase an extra 2.8 billion gallons of fuel for a congestion cost of $87.2 billion - an increase of more than 50% over the previous decade. Urban arterials operating in oversaturated conditions are now very common and are expected to become even more prevalent. As a result, there is an urgent need to explicitly address oversaturation. Simulation of oversaturation plays an important role in addressing it. However, the previous research, including existing traffic simulation software and theoretical approaches, take full account of traffic flow on two way arterials in oversaturated conditions. Therefore, improvements of existing traffic flow model simulation techniques are necessary to adequate study such fully oversaturated arterials. The objective of this research is to develop a novel feature for traffic flow models, to simulate when traffic queues on two way arterials periodically extend until then block an upstream signal in oversaturated conditions. Such a model should be capable of delineating the dynamic of traffic flow created by the merging and diverging activities on two way arterials. In additional, it should have the capability of describing blockages, spillback and shock wave phenomena along the oversaturated arterials. The Cell Transmission model (CTM) is used in the dissertation, because it can accommodate all traffic conditions from light condition to oversaturated condition. However, it has limitations and has only recently been extended from one way two way arterials. Two way arterials have more diverge and merge activities at intersections, which make the coding of CTM more complex and time-consuming. Second, a noticeable inaccuracy in prior CTM research is the failure to simulate the blockages at intersections. They typically estimate the delay occurring on segments and ignore the delay occurring at intersections. These limitations affect CTM's accuracy and limit its use. To enhance CTM, a conditional cell transmission model (CCTM) is developed with two improvements. First, CTM is expanded for two-way arterials by taking account of all diverge and merge activities at intersections. Second, a conditional cell is added to simulate periodic spillback and blockages at an intersection. The cell exists conditionally, depending on whether or not there is a spillback at an intersection. In other words, if spillback happens, the conditional cell exists and stores the vehicles which spill back into the intersection; if there is no spillback, the conditional cell will not exist. In CCTM, users may input the probability of a conditional cell (drivers breaking the driving rule) and probability of occurrence of useful location of a gap to match the characteristics of local drivers' behavior. This is a unique contribution of CCTM. The CCTM traffic flow simulation was initially developed using evolutions of small model of six cell mode. It included (a segment cell, a diverge cell, a cell in front of an intersection, a cell in a left turn lane, a cell in the minor street and a conditional cell). They were loaded with light duty traffic, moderate duty traffic and heavy duty traffic respectively. To test the overall performance of CCTM, a series of experiments are designed and performed for a multilane, two-way, three-signal sample network. Experiments were conducted to give sensitivity analyses to four user-defined parameters including traffic demand, traffic signal timing, possibility of occurrence of a useful gap and possibility of a conditional cell. The results demonstrate that CCTM can accommodate various traffic demands and CCTM's accurate representation of traffic flow. Finally, to validate CCTM, it is compared with HCS (Highway Capacity Software 2000). Three scenarios of traffic demand are inputted into HCS and the results of travel speeds are compared with those of CCTM. The consistency between HCS 2000 and CCTM shows that CCTM is a reliable methodology of modeling traffic flow in oversaturated condition.