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

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Dan Zhou ◽  
Sheng Jin ◽  
Dongfang Ma ◽  
Dianhai Wang
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Simulation Models ◽  
Transportation Systems ◽  
Simulation Approach ◽  
Lane Changing ◽  
Slowing Down ◽  
Ca Model ◽  
Stable Performance ◽  
Motorized Vehicles

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.

Multiregime Approach for Microscopic Traffic Simulation

1998 ◽  
Vol 1644 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Yunlong Zhang ◽  
Larry E. Owen ◽  
James E. Clark
Keyword(s):  
Traffic Flow ◽  
Real World ◽  
Traffic Simulation ◽  
Simulation Models ◽  
Traffic Modeling ◽  
Simulation Approach ◽  
Microscopic Simulation ◽  
Lane Changing ◽  
Microscopic Traffic Simulation ◽  
Simulation Results

The purpose of this paper is to explore various traffic modeling aspects and theories that may overcome some of the limitations in existing microscopic simulation models. A multiregime microscopic traffic simulation approach has been formulated featuring realistic and comprehensive carfollowing and lane-changing logic. A prototype implementation of the multiregime approach was developed in C++ and extensively tested. The multiregime simulation results demonstrate the efficiency and validity of the proposed models for a broad range of traffic scenarios. The test and validation results indicate that the model and program outperformed traditional methods and other existing traffic simulation programs. The validity and efficiency of the model is attributed to the fact that the regimes were added to the model incrementally to reflect increasing agreement with real-world traffic flow. The techniques and corresponding models will be used to improve existing microscopic traffic simulation models and programs.

A Cellular Automaton Model for Highway: Considering Multi-Lane Traffic Rules

2014 ◽  
Vol 587-589 ◽  
pp. 2213-2219 ◽  
Author(s):  
Hong Jia Zhu ◽  
Dan Wang ◽  
Ji Biao Zhou
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Maximum Speed ◽  
Lane Changing ◽  
Traffic Characteristics ◽  
Microscopic Models ◽  
Daunting Task ◽  
Micro Simulation ◽  
Ca Model ◽  
The Impact

Vehicular flow in highway is inherently complex and development of microscopic models of vehicular flow has been a daunting task for researchers. This paper presents the use of Cellular automata (CA) micro simulation for modeling multi-lane traffic characteristics in highway, as well as considering the average speed difference (ASD) and lane-changing rules (LCR) in the CA model. Firstly, on the base of the Symmetric Two-Lane Cellular Automata (STCA) model, we analyzed the impact on traffic characteristics, through adjusting the maximum speed and lane-changing rules. Secondly, by the micro simulation, the relationships between speed and density in traffic flow were given considering the ASD and the LCR. The simulation results showed that, (a) the more obvious of speed dispersion, the more serious about speed declining, (b) the speed of overall traffic flow slowed down by 163% under extreme conditions, (c) the more reckless of lane-changing rule drivers used, the higher speed of traffic flow can reach.

Optimization driven cellular automata for traffic flow prediction at signalized intersections

2021 ◽  
Vol 40 (1) ◽  
pp. 1547-1566
Author(s):  
Shuang You ◽  
Yaping Zhou
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Fitness Function ◽  
Traffic Density ◽  
Traffic Flows ◽  
Average Speed ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Ca Model ◽  
Signalised Intersection

The traffic flow prediction using cellular automata (CA) is a trendy research domain that identified the potential of CA in modelling the traffic flow. CA is a technique, which utilizes the basic units for describing the overall behaviour of complicated systems. The CA model poses a benefit for defining the characteristics of traffic flow. This paper proposes a modified CA model to reveal the prediction of traffic flows at the signalised intersection. Based on the CA model, the traffic density and the average speed are computed for studying the characteristics and spatial evolution of traffic flow in signalised intersection. Moreover, a CA model with a self-organizing traffic signal system is devised by proposing a new optimization model for controlling the traffic rules. The Sunflower Cat Optimization (SCO) algorithm is employed for efficiently predicting traffic. The SCO is designed by integrating the Sunflower optimization algorithm (SFO) and Cat swarm optimization (CSO) algorithm. Also, the fitness function is devised, which helps to guide the control rules evaluated by traffic simulation using the CA model. Thus, the cellular automaton is optimized using the SCO algorithm for predicting the traffic flows. The proposed Sunflower Cat Optimization-based cellular automata (SCO-CA) outperformed other methods with minimal travel time, distance, average traffic density, and maximal average speed.

Microscopic simulation of lane changing behaviour at freeway weaving sections

1999 ◽  
Vol 26 (6) ◽  
pp. 840-851 ◽  
Author(s):  
A F Al-Kaisy ◽  
J A Stewart ◽  
M Van Aerde
Keyword(s):  
Simulation Model ◽  
Empirical Data ◽  
Intelligent Transportation Systems ◽  
Traffic Simulation ◽  
Essential Element ◽  
Simulation Models ◽  
Transportation Systems ◽  
Microscopic Simulation ◽  
Lane Changing ◽  
Microscopic Traffic Simulation

Microscopic traffic simulation models are being increasingly used to evaluate Intelligent Transportation Systems (ITS) strategies and to complement empirical data in developing new analytical procedures and methodologies. Lane changing rules are an essential element of any microscopic traffic simulation model. While most of these rules are based on theories and hypotheses, to date no attempt has been made to investigate the consistency of lane changing behaviour from microscopic simulation with empirical observations. The research presented in this paper examined this consistency at freeway weaving areas using empirical data. These data were collected in the late 1980s at several major freeway weaving sections in the State of California. The microscopic traffic simulation model INTEGRATION was used to perform simulation experiments in this research. Vehicle distributions, both total and by type of movement, were used as measures to investigate the lane changing activity that took place at these freeway areas. This examination revealed significant agreement between patterns of lane changing behaviour as observed in the field and as reproduced by microscopic simulation. Most quantitative discrepancies were shown to be a function of user-specified input data or due to some inherent limitations in the empirical data.Key words: simulation, lane changing, weaving, freeways.

scholarly journals Simulation Study of Autonomous Vehicles’ Effect on Traffic Flow Characteristics including Autonomous Buses

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Tanveer Muhammad ◽  
Faizan Ahmad Kashmiri ◽  
Hassan Naeem ◽  
Xin Qi ◽  
Hsu Chia-Chun ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Flow Characteristics ◽  
Transportation Industry ◽  
Lane Changing ◽  
Autonomous Cars ◽  
Ca Model ◽  
Multiple Scenarios

Autonomous vehicles are expected to revolutionize the transportation industry. The goal of this research is to study the heterogeneity in traffic flow dynamics by comparing different penetration rates of four different types of vehicles: autonomous cars (AC), autonomous buses (AB), manual cars (MC), and manual buses (MB). For the purpose of this research, a modified cellular automata (CA) model is developed in order to analyze the effect of heterogeneous vehicles (manual and autonomous). Previously, studies have focused on manual and autonomous cars, but we believe a gap in perception and analysis of mixed traffic still exists, as inclusion of other modes of autonomous vehicle research is very limited. Therefore, we have explicitly examined the effect of the AB on overall traffic flow. Moreover, two types of lane changing behavior (aggressive lane changing and polite lane changing) were also integrated into the model. Multiple scenarios through different compositions of vehicles were simulated. As per the results, if AB is employed concurrently with AC, there will be a significant improvement in traffic flow and road capacity, as equally more passengers can be accommodated in AB as AC is also anticipated to be used in carpooling. Secondly, when the vehicles change the lanes aggressively, there is a substantial growth in the flow rate and capacity of the network. Polite lane change does not significantly affect the flow rate.

scholarly journals A Cellular Automata Traffic Flow Model considering Bus Lane Changing Behavior with Scheduling Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zun-dong Zhang ◽  
Yan-fang Yang ◽  
Wenjiao Qi ◽  
Abderrahim Chariete ◽  
Xing-xiang Lin
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Flow Density ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Traffic Flow Model ◽  
Mixed Traffic Flow ◽  
Bus Lane ◽  
Bus Stops

According to different driving behavioral characteristics of bus drivers, a cellular automata traffic model considering the bus lane changing behavior with scheduling parameters is proposed in this paper. Traffic bottleneck problems caused by bus stops are simulated in multiple lanes roads with no-bay bus stations. With the mixed traffic flow composed of different bus arrival rate, flow-density graph, density distribution graph, and temporal-spatial graph are presented. Furthermore, the mixed traffic flow characteristics are analyzed. Numerical experiment results show that the proposed model can generate a variety of complicated realistic phenomena in the traffic system with bus stops and provide theoretical basis for better using of traffic flow model.

scholarly journals Feature Analysis on Mixed Traffic Flow of Manually Driven and Autonomous Vehicles Based on Cellular Automata

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xinghua Hu ◽  
Mengyu Huang ◽  
Jianpu Guo
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Theoretical Basis ◽  
Flow Model ◽  
Maximum Flow ◽  
Feature Analysis ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
Ca Model

This paper attempts to disclose the features of the mixed traffic flow of manually driven vehicles (MVs) and autonomous vehicles (AVs). Considering dynamic headway, the mixed traffic flow was modelled based on the improved single-land cellular automata (CA) traffic flow model (DHD) proposed by Zhang Ningxi. The established CA model was adopted to obtain the maximum flow of the mixed traffic flow and was analyzed under different proportions of AVs. On this basis, the features of the mixed traffic flow were summarized. The main results are as follows: the proportion of AVs has a significant impact on the mixed traffic flow; when the proportion reached 0.6, the flow of the whole lane was twice that of the MV traffic flow. At a low density, the AV proportion has an obvious influence on mixed traffic flow. At a high density, the mixed traffic flow changed very little, as the AV proportion increased from 0 to 5. The reason is that the flow of the whole lane is constrained by the fact that MVs cannot move faster. However, when the AV proportion reached 0.8, the flow of the whole lane became three times that at the proportion of 0.6. At the speed of 126 km/h, the flow rate was 2.5 times the speed limit of 54 km/h. The findings lay a theoretical basis for the modelling of multilane mixed traffic flow.

Time-Space Research of the Two Safety Deceleration Models

2014 ◽  
Vol 496-500 ◽  
pp. 2950-2954
Author(s):  
Wei Jun Pan ◽  
Na Lu
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Original Model ◽  
Space Research ◽  
Traffic Model ◽  
Time Space ◽  
Proposed Model ◽  
Ca Model ◽  
Combined Action ◽  
Real Traffic

The SDNS cellular automata (CA) traffic model is chosen as the method to point out the fault in the original model by analyzing the condition of safety deceleration. An improved CA model is proposed in this paper through adjustment of the evolution steps and the redefinition of safe deceleration conditions. Thousands of simulations have been carried out. Comparing with SDNS model and original safety deceleration model with the proposed model in this paper, when emerging congestion, the combined action of urging and safe deceleration enabled system self-adjustment so that efficiently mitigated congestion. This proves that the stop status of the whole traffic flow has been improved, which have been observed in real traffic.

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