This paper introduces a novel concept of dilemma zone (DZ) estimation for yielding drivers based on jaywalking pedestrian crossing behavior interference at semiurban uncontrolled intersection approaches on high-speed arterial roads. Field data from uncontrolled intersections in India’s Hanamkonda and Warangal districts, observing 1,090 drivers yielding to pedestrians near intersection conflict areas, were retrieved. Bayesian combined neural networks (BCNNs), permutation-invariant support vector machines (piSVM), and distributional autoreplicative random forest (ditARF) were utilized to define pedestrian composition-based yielding driver DZ location and lengths. According to the ditARF model, pedestrian crossing speed, pedestrian gap size, pedestrian delay, pedestrian group size, conflicting vehicle speed, and conflicting vehicle type influence drivers’ yielding behavior. The study revealed that BCNN and piSVM can be utilized for developing DZ passive warning systems, while ditARF can be beneficial for active driver assistance systems. A novel potential risk proportion (PRP) or risk index was introduced for quantifying risk of yielding vehicle decisions near high-pedestrian-volume uncontrolled intersections on high-speed arterials. Male young-aged pedestrians and large-sized vehicles such as heavy and light commercial vehicles with low PRP had a long DZ nearer to the intersection influence area. The composition-based dilemma zone boundaries (as estimated using the ditARF models) can be used as constraints while optimizing trajectories of nonyielding vehicles at intersections in order to reduce number of vehicles trapped within the type-II dilemma zone for yielding drivers.
The study helps identify parameters such as the longitudinal distance between crossing pedestrians and nonyielding vehicles at an unmarked crossing region (LD), pedestrian walking speed (), approach vehicle speed (), and critical gaps between pedestrians as indicators for assessing yielding driver dilemma zones to jaywalking pedestrian response at uncontrolled intersections. The permutation-invariant support vector machines model based on its static dilemma zone boundaries based on approach speed limits can be utilized for the proposal of passive warning signs that may alert drivers to take cautious maneuvers and thus take evasive actions. The dynamic distributional autoreplicative random forest (ditARF) and Bayesian combined neural network-based dilemma zone boundaries can be utilized for developing real-time driver and pedestrian assistance systems with further advancement to pedestrian-to-vehicle technology. The younger male pedestrian dilemma zone was found to be more dynamic and thus requires situational and social awareness to enhance safety. Yielding driver dilemma zone boundaries can be integrated with Internet of things infrastructure enabling motion sensors to detect real-time pedestrian movements at unmarked crosswalks of intersections. The yielding driver dilemma zone concept along with the potential risk proportion (PRP) performance indicator can help to classify risky intersection approaches (based on traffic flow, road network, and socio-economic-TSN evaluation metric) for importance classification of uncontrolled intersections in a high-speed semiurban corridor. The PRP performance indicator corresponding to dynamic ditARF modeled dilemma zone lengths can be integrated into VISSIM’s COM user interface for better understanding of pedestrian–vehicle interactions by aiding traffic engineering consultants. The probability of yielding (), yielding angle (), jaywalking angle (), longitudinal distance, hard yielding rates, and soft yielding rates can be utilized for calibration of cameras and sensors built-in within Society of Automotive Engineers level-3 autonomous vehicles (AV) according to adjusting pedestrian walking speed variations by Indian AV developers.
Analyzing Yielding Drivers’ Dilemma Behavior toward Pedestrians at Semiurban Uncontrolled Intersections on Arterial Roads
2025-10-01
Article (Journal)
Electronic Resource
English
Behavior of drivers at uncontrolled intersections
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