Modeling Vehicle–Pedestrian Interactions using a Nonprobabilistic Regression Approach

Abstract

Understanding how vehicle drivers and pedestrians interact is key to identifying countermeasures that improve the safety of the interactions. As a result, techniques that can be used to evaluate the effectiveness of safety countermeasures and traffic control devices without the need to wait for the availability of crash data are needed. Using video, the interactions between right-turning vehicles and conflicting pedestrians were documented and quantified using vehicle and pedestrian position timestamps. Interactions documented were purposely narrow in scope to obtain a controlled dataset. Logged timestamps enabled the calculation of values such as time to complete a right turn and time for a pedestrian to reach a critical conflict point when a vehicle initiated a right turn. A nonprobabilistic regression model explaining the relationship between the calculated values was created. The model described the expected behavior of right-turning drivers: when drivers perceive the possibility of a pedestrian reaching a critical conflict point at the same time as them, they will modify their behavior, even if not coming to a complete stop. This behavior is not a surprise and has been previously documented in the literature. The primary contribution of this research is demonstrating that by analyzing a narrow set of interactions, clear and simple models that mostly explain the interactions between right-turning vehicles and pedestrians can be developed using nonprobabilistic linear regression techniques. An argument is made that the model parameters can be used to evaluate the effectiveness of traffic control devices.

Estimation Method of Left Turn Lane Capacity Under the Influence of Pedestrians and Crosswalk Layout at Signalized Crosswalks

“…In the above sections we tried to summarize how we can express the influence of crossing pedestrians and geometric layout, accordingly their influence on the left turn lane capacity can be generalized using Eqn. (7).…”

“…Their results indicated that there is a primarily linear relationship between pedestrian volume and right turning vehicles flow. Nassereddine et.al [7] investigated the pedestrianvehicle interaction and tried to establish a simple nonprobabilistic regression model that explains the attitude of right-turning drivers (right-hand traffic system) at a specific intersection towards the presence of conflicting pedestrians. Their result confirmed that, when drivers perceive the possibility of pedestrian reaching a critical conflict point at the same time as them, they will modify their behavior even if not coming to a stop.…”

“…As it is discussed in the above sections, the characteristics of waiting pedestrian flow and the interaction of arriving pedestrians on left turning vehicles can be empirically observed and modeled to capture the influence of crossing pedestrians on left turning vehicle movements. After we understand the crossing pedestrian's characteristics and the discharge flow rate, by considering the pedestrians behavior and geometric layout of the crosswalk, the left turn lane capacity can be estimated using Equation (7).…”

Evaluating Right-Turn Flashing Yellow Arrow for Vehicle–Pedestrian Interactions Using a Non-Probabilistic Regression Approach

“…Using a frame-by-frame analysis, right-turning maneuvers when no conflicting pedestrians were present and the interactions between right-turning vehicles and conflicting pedestrians were documented using a previously developed procedure (11). Figure 2 shows the timestamps associated with the two key positions of right-turning vehicles and the two key positions of conflicting pedestrians: timestamp when the front axle of a vehicle crossed the most upstream pavement marking bar of the crosswalk in the entering approach-referred to as P 0 , timestamp when the front axle of a vehicle crossed the most downstream pavement marking bar of the crosswalk in the exiting approach-referred to as P 1 , timestamp when a conflicting pedestrian crossed the first boundary of the inside lane, determined by the direction of travel-referred to as P 2 , and timestamp when a conflicting pedestrian crossed the second boundary of the inside lane, determined by the direction of travel-referred to as P 3 .…”

“…As detailed data from vehicle–pedestrian interactions become easier to obtain thanks to advances in technology, an argument can be made for the use of new (or improved) SSM-style metrics for evaluating the potential safety benefits of a countermeasure. The feasibility of conducting such an evaluation by focusing on a field-derived metric that describes the behavior of a driver is presented in this paper as an evolution of previous work conducted by the authors ( 11 ). Previously introduced metrics to quantify vehicle–pedestrian interactions are used to evaluate the potential safety benefits of RT FYA indications for vehicle–pedestrian interactions.…”