Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach

Dan Zhou,Sheng Jin,Dianhai Wang,Dongfang Ma

doi:10.1155/2015/420581

Abstract

Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA) model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS) CA model and the multivalue CA (M-CA) model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs) and electric bicycles (EBs). In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.

Highlights

Traffic flow theories are generally divided into two branches: macroscopic and microscopic theories [1]
The default values of the random slowing down probability of regular bicycles (RBs), the random slowing down probability of electric bicycles (EBs), and the proportion of EBs are 0.4, 0.4, and 0.5, respectively, for the MCA model
In the M-cellular automata (CA) model, the slowing down probability is the probability that the number of bicycles (cjr(t + 1)) decreases, which means that one bicycle decreases its speed

Summary

Introduction

Traffic flow theories are generally divided into two branches: macroscopic and microscopic theories [1]. The macroscopic traffic flow models are based on fluid dynamics and are mostly used to elucidate the relationships between density, volume, and speed ( called the fundamental diagram) in various traffic conditions. The microscopic traffic models, on the other hand, describe the interaction between individual vehicles. The microscopic traffic models generally include car-following models and cellular automata (CA) models. CA models have emerged as an efficient tool for simulating highway traffic flow because of their easy concept, simple rule, and speed in conducting numerical investigations. Nagel and Schreckenberg [9] presented the well-known NS CA model, which is an extension of the rule-184 model allowing the maximal speed of vehicles to be more than one cell/s. The NS model and the many improved versions of it reproduce some basic and complicated phenomena such as stop and go, metastable states, capacity drop phenomena (which means the capacity of road experiences a large drop under critical density conditions), and synchronized flow in real traffic conditions

Results

Discussion

Conclusion