Next Generation Simulation (NGSIM)
-Improved Simulation of Stop Bar Driver Behavior at Signalized Intersections-
Los Angeles, CA and Atlanta, GA Data Sets

Working Papers

The analyses conducted in this research were based on three methodologies for the field measurement of saturation headways. The first method (MI), the one on which most past studies were based, measured the characteristics of Vehicles 4 to 12 in a standing queue. M2, the method found in the Highway Capacity Manual (HCM), counted all vehicles in a standing queue, regardless of queue length. M3 included arrivals that joined the standing queue as long as vehicles were up to 140 ft from the stop line. This study focused on one approach of a high-design intersection with heavy, random arrivals. The large number of observations and the practically ideal traffic conditions enabled the acquisition of several statistically significant results on saturation flow (s), start-up lost time (SULT), and start-up response time (SRT): (a) when long queues are present, the typical field measurement of s based on the first 12 vehicles is an overestimate of s for through vehicles and an underestimate of s for protected left-turning vehicles; (b) the type of movement had a more dominant role in determining s than the level of saturation (or queue length); (c) SRT displayed a bigger variation than headways— the left-turning movement had a significantly shorter SRT than the through movement did; and (d) much higher SULTs were estimated in this study compared with those in the HCM.

This paper appears in the Transportation Research Record No. 1802 [Year of Publication 2002].

Summary

Introduction, background and experimental setup

In this paper, the authors tried to look at saturation headways, startup lost times (incl. startup reaction times) using three methods. The first method (M1) on which most of the past studies were based looks at these parameters for the 4^th through 12^th vehicles in a queue. The second method (M2) is suggested by the HCM and looks at the 4^th through 28^th vehicles in queue. The third method (M3) is proposed by the authors and looks at up to 36 vehicles, and includes arrivals that join the standing queue as long as the vehicles were up to 140ft from the stop line (where an advanced detector was placed). They also look at compression or elongation of headways for the last few vehicles of the queue. Vehicles for one through movement and one protected left-turn movement were observed. All observations were done for groups of four vehicles, and observations containing fewer than four vehicles at the end of a queue were not included.

Authors define SRT as the elapsed time between display of green and when the first vehicle begins to move. They then calculate the saturation headway by averaging the headways beyond the first four vehicles. Finally, they calculate the SULT based on the SRT, average headway of the first four vehicles and average saturation headway as follows:

SULT = SRT + 4*(H₄ - h)

Hence, SULT is the sum of the SRT and the additional time it took for the first four vehicles to discharge.

Observations, Inferences and Conclusions

The following were the significant observations of the authors in their study

• Saturation headways for the TH and LT movements differed significantly over the three methods. For TH movements, M1 and M2 overestimate the real saturation flow rate to a long standing queue in both undersaturated and near-saturated conditions. For LT movements and for over-saturated conditions (with queues obviously greater than 12 vehicles), M1 underestimates the saturation flow rate actually achieved by the whole standing queue. Since M3 looks at entire queues, it is much better at detailing their discharge characteristics. These differences have implications for capacity analyses, signal analyses and microsimulation modeling.
• Intermediate headways (for those between 5^th and 12^th vehicles) do not vary significantly with queue size.
• For turning movements, the turning movement itself has a more dominant role in determining the saturation headway than the saturation condition of the movement. However, the trend of headways for that turning movement is affected more by saturation condition than by turning movement.
• For TH movement, there was an elongation of headway for the last few vehicles. For LT movements, the headways for the last vehicles were compressed (probably as LT phases are (perceived to be?) shorter by drivers and they hence have a heightened state of awareness). Negative startup times were observed for several LT movement cycles.
• SULT has a weak negative correlation with queue length (equations are shown in the paper). It is lower for peak-hour observations, as expected. SRT is larger for TH movements than LT movements.