Investigating impacts of various operational conditions on fuel consumption and stop penalty at signalized intersections

Field-Based Prediction Models for Stop Penalty in Traffic Signal Timing Optimization

“…Such primary conditions include vehicle type, proportion of heavy vehicles in the fleet (because of their heavy masses [25]), driving behavior, road gradient, cruising speed, and aerodynamic effect. The individual and combined impacts of all the previously mentioned conditions on the stop penalty, based on simulation results, were documented elsewhere [24,26]. However, the impact of two additional factors (idling FC rate (FC I /T I ) and deceleration duration (T D )) was not examined in the previous studies.…”

“…As mentioned previously, a recent simulation-based study [24] investigated the individual impact of multiple operating conditions (e.g., cruising speed and road gradient) on the K-factor (Figure 4). The study concluded that the K-factor varies significantly under various conditions.…”

“…As mentioned in the introduction, only a few studies have computed the stop penalty, either by using FC collected in the field or FC estimates from simulated vehicular trajectories. This subsection discusses the stop penalty values from various studies [13,15,16,21,23,24] to address how the outcomes of this research may improve practices and policies when optimizing signal timings in urban corridors.…”

“…Considering that most of the evaluated studies report only the cruising speed (as a factor associated with the reported stop penalties), we developed in Figure 11 (with our best effort as data from various studies may not be 100% consistent) a set of relationships between the stop penalty and cruising speed from seven sources, MGGP models developed in this paper; "Synchro"-a widely used signal timing optimization tool [21]; field-based stop penalties reported by Courage and Parapar [13], Akcelik [16], Stevanovic et al [23], and Robertson et al [15]; simulation-based stop penalties from Alshayeb et al [24]. Figure 11 shows that various studies show different trends, where most of them point to a positive impact of the speed on stop penalty.…”

“…Nowadays, some of the widely used signal timing optimization programs (e.g., Synchro) use the PI as the primary objective function for the optimization, not so much to reduce FC, but as a way to find a balance between two of the most crucial performance measures at signalized intersections, delays and stops [21,22]. Such optimization programs usually use a very low value for K (e.g., 10 s), which has been shown not to be appropriate if the goal is to minimize FC at signalized intersections [13,15,16,[23][24][25].…”