Cellular automaton model with dynamical 2D speed-gap relation reproduces empirical and experimental features of traffic flow

TL;DR

This paper introduces an improved cellular automaton traffic flow model that captures complex traffic phenomena by allowing dynamic two-dimensional speed-gap relationships, aligning well with empirical data and experimental observations.

Contribution

The novel aspect is modeling traffic states as dynamically spanning a 2D speed-gap region, enhancing the realism of traffic flow simulations compared to traditional models.

Findings

Successfully reproduces free flow, synchronized flow, and jams.

Captures evolution of disturbances and spatiotemporal patterns.

Aligns with empirical traffic speed data from NGSIM.

Abstract

This paper proposes an improved cellular automaton traffic flow model based on the brake light model, which takes into account that the desired time gap of vehicles is remarkably larger than one second. Although the hypothetical steady state of vehicles in the deterministic limit corresponds to a unique relationship between speeds and gaps in the proposed model, the traffic states of vehicles dynamically span a two-dimensional region in the plane of speed versus gap, due to the various randomizations. It is shown that the model is able to well reproduce (i) the free flow, synchronized flow, jam as well as the transitions among the three phases; (ii) the evolution features of disturbances and the spatiotemporal patterns in a car-following platoon; (iii) the empirical time series of traffic speed obtained from NGSIM data. Therefore, we argue that a model can potentially reproduce the empirical and experimental features of traffic flow, provided that the traffic states are able to dynamically span a 2D speed-gap region.