Optimizing Right-Turn Signals to Benefit Pedestrian–Vehicle Interactions

Abstract

In most right-driving urban signalized intersections, right-turn vehicle signals do not usually control turns. To address the problem of signal control in a pedestrian–vehicle interaction, this paper establishes a right-turn signal optimization (RTSO) model that considers both efficiency and safety. First, the main factors influencing the behavior of vehicle and pedestrian during pedestrian–vehicle interaction are analyzed, and a pedestrian–vehicle interaction model (PVI model) at an urban road crosswalk is established. This model is used to determine the probabilities of four pedestrian–vehicle interaction situations. Then, based on the traffic conflict theory, the next step was to construct an objective function that minimizes the total delay of traffic participants considering pedestrian–vehicle interactions, and another objective function that minimizes the potential conflicts considering pedestrian–vehicle interactions. Then, an RTSO model is obtained by introducing a safety-efficiency coefficient to combine the previously described two constructed functions. Finally, the PVI model and delay model are verified through video observation data and the establishment of a cellular automata simulation platform of pedestrian–vehicle interaction. Using these models, a field signal plan, the delay minimization scheme, the conflict minimization scheme, and the proposed scheme are numerically analyzed under different yielding rates. This proposed scheme is further numerically analyzed under different safety-efficiency coefficients. The results show that this paper’s RTSO model has certain advantages in increasing safety and reducing delay. In addition, using these results, this paper gives a recommended value for the safety-efficiency coefficients in different application scenarios.

Saturation flow rate analysis for special width approach lanes: An empirical study in Karlsruhe, Germany

“…The common influencing factors, such as area type, lane width, heavy vehicles, grade, turnings, pedestrians and bicycles, have been considered in the manuals, such as the highway capacity manual (HCM) [15]. Other concerned adjustment factors for saturation flow rate include the weak-lane-disciplined mixed traffic stream [16][17][18][19], short lanes [20], left-turn waiting area [21], adverse weather conditions [22], lighting conditions [23], access traffic [24], guide line markings [25], signal countdown devices [26], and autonomous driving environment [27]. Recently, with the wider use of the unconventional intersection design, the saturation flow rate of the lanes under the unconventional design were also explored based on empirical data.…”