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A journey into the Dilemma Zone with Econolite

Indecision on the road can kill. Econolite’s Sunny Chakravarty and Vincent Mayeda present new data-driven dilemma zone and intersection safety strategies for a Vision Zero future
January 16, 2025 Read time: 10 mins
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Despite advances in roadway design and planning, safety in the “dilemma zone” remains operationally problematic. According to Gazis, Herman and Maradudin’s original 1960s research, a dilemma zone is defined as the section of the roadway when approaching an intersection in which a driver is unable to stop safely before the stop bar or proceed through before the signal turns red. (1)

This area is known as the “Type I” dilemma zone. In the 1970s, further research by Zegeer and Deen and others considered distances from an intersection for “likely stop” and “likely go” scenarios relative to vehicle velocity and driver behaviour, which led to the concept of the “Type II” dilemma zone. (2) 

This refers to the section of the roadway approaching an intersection in which a driver has to decide to either stop or proceed through the intersection before the signal turns red, and each individual driver may potentially make a different decision when presented with the yellow signal indication. This “decision” zone is a critical point to ensuring safety at the intersection for all roadway users. (Figures 1-2: Type I and II dilemma zone diagrams)

Figure 1. Diagram of the Type I dilemma zone

The enormous impact of vehicle collisions, particularly at intersections, is a major global challenge to Vision Zero. It is well-documented that crashes claim around 1.35 million lives annually with approximately 50 million people sustaining serious injuries and living with long-term health consequences. (3)

This negatively impacts economies, healthcare systems, transportation networks and quality of life. New strategies for dilemma zone protection are needed to help reach a Vision Zero future. 

 

 

Dilemma zone’s dilemma 

Intersection collisions and conflicts are, for the most part, due to driver misjudgment of the traffic signal transition from green-to-yellow-to-red. The misjudgment most often occurs when the driver perceives the traffic signal change to yellow and must decide to stop before the intersection or proceed through it, possibly violating a red signal. That is the classical “dilemma zone” problem. Key statistics from sources such as the latest report from the Insurance Institute for Highway Safety (IIHS) underscore the importance of dilemma zone protection. According to the IIHS, red-light running collisions caused 1,109 deaths in the US in 2021, along with approximately 127,000 injuries. (4)

Half of the fatalities were other vulnerable roadway users, including pedestrians, bicyclists and other motor vehicle occupants hit by drivers who violated the red signal. These findings emphasise the challenge and importance of dilemma zone safety. 

Under the principles of Vision Zero, fatalities and serious injuries due to roadway traffic collisions - including intersection conflicts - can be prevented.

However, dynamic data-driven strategies are needed to make more substantial and sustainable gains for dilemma zone safety. 

Figure 2. Diagram of the Type II dilemma zone or decision zone where a driver is able to stop before the intersection


 

Dilemma zone: solvable physics problem

The Type I dilemma zone problem can be addressed with appropriate yellow clearance, which is determined based on kinematics equations with an assumed speed and deceleration rate for a typical vehicle approaching the intersection.

The Type II dilemma zone problem is harder to address because it involves a decision component on the part of the driver. When Chang, Messer and Santiago defined the boundaries of the Type II dilemma zone (also known as “decision zone”) in terms of travel time to the stop bar, they observed that 85% of drivers stopped if their vehicles were three or more seconds away from the stop bar when the signal light turned yellow, but almost all drivers continued through the intersection if they were two or fewer seconds away from the stop bar. (5) 

The length of the decision zone itself is determined as the area between the point until which ‘Most Stop’ and the point beyond which ‘Nearly All Continue’ when faced with a yellow signal indication. (Figure 3: Driver behaviour and decision zone diagram)

The Signal Timing Manual  2nd Edition, which provides trend-based guidance from previous studies, indicates that the decision zone usually exists between 5.5 and 2.5 seconds of travel time from the stop bar. (6)

Figure 3. Strategies to protect the intersection must include driver behaviour

The Signal Timing Manual quantifies these values in stop bar distance, dictated by various common approach speeds. This travel time-based definition is the simplest quantification and effectively applies physics to the decision zone, which can then be used in signal timing. But it should be used with caution as the decision zone problem involves individual human factors - including driving style, level of attention, and perception and reaction time - which often render “static” solutions to the problem ineffective. (Figure 4: The Signal Timing Manual 2nd Edition chart)

 

Role of signal timing 

The appropriate length of yellow signal change and red signal clearance timing, paired with accurate detection technology for green or red signal extension activation, represents a standard way to help mitigate conflict at an intersection with other vehicles, as well as pedestrians and bicyclists.

The first objective when identifying a solution for a dilemma zone is to determine the green signal extension indication. Traditionally, the green signal timing interval is extended for drivers passing through advanced detection zone(s) positioned at various key locations along the roadway, ahead of the intersection based on the posted speed limit for the roadway. Each detector has its own green extension timer with preset timing pertinent to the travel time from that dilemma zone location to the stop bar at the designed approach speed. 

However, after a certain point, it becomes unfeasible to continue extending the green signal interval. In this situation, the mitigation strategy relies on an appropriately-timed yellow signal change and red signal clearance interval and extending the red clearance interval until all conflicting - and potentially conflicting - drivers have safely passed through the intersection. These strategies provide the second layer of mitigation when green signal extension is no longer feasible.

 Figure 4. The Signal Timing Manual 2nd Edition guidance for decision zones based on vehicle speeds

 

Velocity and other factors 

Green signal time, yellow signal change, and red signal clearance intervals work together in providing dilemma zone protection. Chang et al presented an equation in terms of the driver’s position approaching the intersection in relation to the distance that the driver can travel at a constant approach speed given the yellow signal change and red signal clearance time: 

x + w + l <= v(Y+AR)

In this equation, x is the distance of the driver from the stop bar, w is the width of the intersection, l is the length of the vehicle, v is velocity of the vehicle approach, Y is the yellow signal change duration, and AR is the red signal clearance duration. This equation stipulates that the distance a driver must travel to reach the far side of the intersection must be less than or equal to the distance the driver will travel at a constant speed for the duration of the yellow signal change and red signal clearance.

In addition to the distance travelled, Chang et al also noted that stopping distance is just as important to determining appropriate signal timing to enhance dilemma zone safety: 

xs = v * t + v^2/(2*d)

This stopping distance formula includes t as the driver’s perception-reaction time and d represents the deceleration rate. If the stopping distance xs is greater than x, or the distance the driver will travel for the duration of the yellow signal change and red signal clearance in the prior equation, then the driver will not be able to stop before the intersection, and the yellow signal change plus red signal clearance time will not be sufficient to provide safe passage through the intersection.

The Signal Timing Manual 2nd Edition provides a formula from the Institute of Transportation Engineers (ITE) to calculate the yellow signal change interval:

Y = t +       1.47v
   2(a + 32.2 g)

In this formula, Y is the yellow change interval in seconds, t is the perception-reaction time to the onset of a yellow indication in seconds, v is the approach speed in miles per hour, a is the deceleration rate in response to the onset of a yellow signal indication in feet per second per second, and g is the grade with uphill positive and downhill negative (percent grade / 100) (feet / feet).

The National Cooperative Highway Research Program (NCHRP) 731 report recommends a deceleration rate of 10 feet per second per second and a perception-reaction time of 1.0 second for signal timing determinations. (7)

However, Chang et al recommend a longer perception-reaction time of 1.2 seconds, with some agencies applying an even longer reaction time factor of 1.5 seconds.

 

New technologies: new dilemma zone strategies

While the signal timing design strategies and recommendations described above based on traffic studies and research are somewhat effective for dilemma zone protection, the challenge is that they do not take into consideration the dynamics of vehicle type (e.g. trucks and other large vehicles require longer stopping distances), trajectory or specific driver behaviour. But the reality is that vehicles and drivers are unique and different, and different road conditions affect the dilemma zone problem in different ways.

Fortunately, new dilemma zone protection strategies can now be developed and implemented based on new capabilities powered by leading-edge sensor and software technologies that can instantaneously sense geopositional vehicle information, vehicle type/classification, and vehicle tracking information (including vehicle velocity). 

This additional vehicle data provides more accurate and dynamic information on vehicle type, trajectory and user behaviour, which can be used to develop more effective dilemma zone protection strategies. High-resolution, real-time sensor data combined with innovative traffic controller software can apply real-time signal timing changes to effectively address real-time roadway conditions and vehicle and driver behaviour to help reduce intersection conflicts. (Figure 5: Video detection)

Figure 5. New video sensors can provide advance speed-conditional detection zones

Leading-edge radar and video sensors now offer alternative solutions to fixed-point detection for dilemma zone configuration and protection strategies. Advance detection zones can be created as ‘motion’ zones to accommodate highly variable traffic condition elements to control the zone’s output. 

Motion zones can be conditioned on attributes like vehicle approach speed, direction, class and ETA to enable different dilemma zone protection strategies for different kinds of vehicles and scenarios. It can also help address vehicles travelling below or above the posted speed limit, which may require significantly different decision zone lengths. (Figure 6: Radar detection)

Figure 6. Similar to video sensors, speed-conditional motion zones can also be established with radar sensors

In addition, modern technologies and advanced software mean that monitoring, reporting and analysing real-time signal states can be leveraged to continuously study and develop new mitigation strategies. Time-stamped events and signal performance measures (SPM) data fed to traffic simulation software can also be used to create simulations of vehicle trajectories and various actuations to understand problems related to the dilemma zone and assess different mitigation strategies before actual implementation. 
 

Summary

The benefits of real-time data-driven applications for dilemma zone protection strategies are profound. With sensor and software technologies now providing situational awareness with high-resolution real-time vehicle data that includes speed, location, trajectory, classification and ETA of all approaching vehicles, more intelligent strategies, including artificial intelligence applications with predictive capabilities, can now be employed. This opens the door for far-reaching mobility and other comprehensive safety enhancement strategies, helping us accelerate towards a Vision Zero future.

 

References


1.    Denos Gazis, Robert Herman, Alexei Maradudin, (1960) The Problem of the Amber Signal Light in Traffic Flow. Operations Research 8(1):112-132
2.    Charles V. Zegeer, Robert C. Deen, (1978) Green-Extension Systems at High-Speed Intersections. Kentucky Transportation Center Research Report 835.
3.    World Health Organization (WHO), Safety and Mobility (SAM), Social Determinants of Health (SDH), (2023) Global Status Report on Road Safety 2023. ISBN: 978-92-4-008651-7
4.    Insurance Institute for Highway Safety (IIWS), (2023), Red Light Running, https://www.iihs.org/topics/red-light-running
5.    Myung-Soon Chang, Carroll J. Messer, Alberto J. Santiago, (1985) Timing Traffic Signal Change Intervals Based on Driver Behavior. Transportation Research Record: Journal of the Transportation Research Board (TRB), No. 1027, TRB of the National Academies, Washington DC
6.    Tom Urbanik, Alison M. Tanaka, Bailey Lozner, Eric Lindstrom, Kevin Lee, Shaun Quayle, Scott Beaird, Shing Tsoi, Paul Ryus, Doug Gettman, Srinivasa Sunkari, Kevin Balke, Darcy M. Bullock, (2015), Signal Timing Manual 2nd Edition, Report: National Cooperative Highway Research Program (NCHRP) 812, Transportation Research Board (TRB) of the National Academies, Washington DC
7.    Transportation Research Board, National Cooperative Highway Research Program (NCHRP) Report 731: Guidelines for Timing Yellow and All-Red Intervals at Signalized Intersections offers guidance for yellow change and all-red clearance intervals at signalized intersections (2016). DOI: 10.17226/22700, Project Number: 03-95

 

ABOUT THE AUTHORS
Sunny Chakravarty (top) is vice president of engineering and Vincent Mayeda is marketing communications specialist for Econolite
 

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