Generalized gap acceptance models for unsignalized intersections

TL;DR

This paper develops advanced gap acceptance models for unsignalized intersections by incorporating driver impatience, multiple driver and vehicle types, and a novel queueing framework to better analyze and predict intersection performance.

Contribution

It introduces generalized models that include driver impatience, multiple driver classes, and a new queueing approach, significantly enhancing practical applicability.

Findings

Incorporates driver impatience and merging behavior.

Allows multiple driver and vehicle classes.

Uses M^X/SM2/1 queueing model for analysis.

Abstract

This paper contributes to the modeling and analysis of unsignalized intersections. In classical gap acceptance models vehicles on the minor road accept any gap greater than the CRITICAL gap, and reject gaps below this threshold, where the gap is the time between two subsequent vehicles on the major road. The main contribution of this paper is to develop a series of generalizations of existing models, thus increasing the model's practical applicability significantly. First, we incorporate {driver impatience behavior} while allowing for a realistic merging behavior; we do so by distinguishing between the critical gap and the merging time, thus allowing MULTIPLE vehicles to use a sufficiently large gap. Incorporating this feature is particularly challenging in models with driver impatience. Secondly, we allow for multiple classes of gap acceptance behavior, enabling us to distinguish between different driver types and/or different vehicle types. Thirdly, we use the novel M$^X$/SM2/1 queueing model, which has batch arrivals, dependent service times, and a different service-time distribution for vehicles arriving in an empty queue on the minor road (where `service time' refers to the time required to find a sufficiently large gap). This setup facilitates the analysis of the service-time distribution of an arbitrary vehicle on the minor road and of the queue length on the minor road. In particular, we can compute the MEAN service time, thus enabling the evaluation of the capacity for the minor road vehicles.