Platoon-based traffic flow model for estimating breakdown probability at single-lane expressway bottlenecks

Abstract

This study investigates the mechanism of traffic breakdown and establishes a traffic flow model that precisely simulates the stochastic and dynamic processes of traffic flow at a bottleneck. The proposed model contains two models of stochastic processes associated with traffic flow dynamics: a model of platoon formation behind a bottleneck and a model of speed transitions within a platoon. After these proposed models are validated, they are applied to a simple one-way, one-lane expressway section containing a bottleneck, and the stochastic nature of traffic breakdown is demonstrated through theoretical exercises.

A Microscopic Platoon Stability Model Using Vehicle-to-Vehicle Communication

“…The followers' vehicles remain behind in the platoon for long In this situation, the ratio of splitting vehicles increases. Similarly, relative speed variance increases lead to a decrease in correlation [30]. If the time headway interval between neighboring vehicles is long enough, cars in the platoon travel freely.…”

Estimation of Traffic Flow Rate With Data From Connected-Automated Vehicles Using Bayesian Inference and Deep Learning

“…This means that we can use the mean or mode of the posterior distribution as a specific estimation, but also estimate the probability that the flow rate exceeds a certain value. This is a nice feature as it can be used to quantify the probability of traffic breakdown (Elefteriadou et al, 1995;Persaud et al, 1998;Evans et al, 2001;Brilon et al, 2005;Shiomi et al, 2011;Chen et al, 2014;Han and Ahn, 2018), which can be used for proactive control to prevent traffic breakdown. Thus, this feature is a notable advantage of the Bayesian inference method.…”

Driver perception uncertainty in perceived relative speed and reaction time in car following – A quantum optical flow perspective

“…Furthermore, lane traffic phenomena characterized by the interactions and reactions of drivers of multiple vehicles surrounding are rooted in psychological reactions of the drivers (Papageorgiou and Maimaris, 2012). For example, congestion upstream of a traffic bottleneck or shockwave can vary in propagation length, depending upon the upstream traffic flow and density perceived by drivers (Shiomi et al, 2011). Therein, shockwaves were also discussed in numerous previous studies (Bose and Ioannou, 2000;Nagai et al, 2006;Tanaka et al, LV driver takes action to change speed (e:g., the brake light of the LV is on) at time t 1 to the time when the FV driver takes action (e:g., puts a foot on the brake pedal) in response to the speed change of the LV at time t 2 .…”