scholarly journals Cellular Automata Model for Mixed Traffic Flow with Lane Changing Behavior

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Devaraj Hanumappa ◽  
Parthasarathy Ramachandran
Keyword(s):  
Cellular Automata ◽  
Cell System ◽  
Flow Density ◽  
Lane Change ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Change Behavior ◽  
Traffic Stream ◽  
Lane Width ◽  
Indian Cities

Indian cities are seen with predominantly mixed traffic plying on the streets. Modeling the mixed traffic involving vehicles characterised of different speed, length, and width is a challenging issue. Based on the finer cell system of cellular automata (CA) models, this paper proposes to evaluate the mixed traffic behavior with cars and motorcycles for intermediate lane width, which is more common in Indian cities. The maximum car flow is observed (even with the presence of motorcycles) in the results which is higher than the Na-Sch model for cars. This increase is mainly due to the changing behavior. The car flow decreases as the density of the motorcycle increases. Furthermore, the paper proposes to evaluate the effect of lane change behavior on the speed and flow of the traffic stream using the fundamental diagrams of speed flow density curves. The simulation result suggests that lane change probability has little effect on the speed and flow of the traffic stream.

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 Expansion of the Fundamental Diagram from a Microscopic Multilane Modeling Framework of Mixed Traffic

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Mudasser Seraj ◽  
Jiangchen Li ◽  
Tony Z. Qiu
Keyword(s):  
Accurate Estimation ◽  
Flow Density ◽  
Mixed Traffic ◽  
Gap Acceptance ◽  
Fundamental Diagram ◽  
Lane Changing ◽  
Car Following ◽  
Proposed Model ◽  
Density Relationship ◽  
Motion Dynamics

Microscopic modeling of mixed traffic (i.e., automaton-driven vehicles and human-driven vehicles) dynamics, particularly car-following, lane-changing, and gap-acceptance, provides the opportunity to gain a more accurate estimation of flow-density relationships for both traditional traffic with human-driven vehicles and different mixed traffic scenarios. Our paper proposes a microscopic framework to model multilane traffic for both vehicle types on shared roadways which sets the stage to explore the capability of macroscopic car-following models in general to explain the fundamental flow-density relationship. Since prior models inadequately represent the fundamental diagram realistically, we propose a rectified macroscopic flow model that can account for the impact of both lane-changing and gap-acceptance. Differentiability, boundary conditions, and flexibility of the proposed model are tested to validate its applicability. Finally, the capability to interpret the flow-density relationship by the proposed model is verified for different mixed traffic scenarios. Although few model parameter values were obtained directly from the simulation input, the rest of the parameters have been calibrated by flow and density outputs from the simulations. The analysis results show a distinct correlation between the proposed model parameters with automation-driven vehicle shares and lane-changing rates of traffic. The findings from this study emphasize the importance of taking complete motion dynamics into account, rather than partial motion dynamics (i.e., car-following) as has been the case in the previous studies, to explain macroscopic traffic flow characteristics, irrespective of the vehicle type.

Categorizing Merging and Diverging Strategies of Truck Drivers at Motorway Ramps and Weaving Sections using a Trajectory Dataset

2020 ◽  
Vol 2674 (9) ◽  
pp. 855-866
Author(s):  
Salil Sharma ◽  
Maaike Snelder ◽  
Lóránt Tavasszy ◽  
Hans van Lint
Keyword(s):  
Finite Mixture Models ◽  
Research Area ◽  
Truck Drivers ◽  
Lane Change ◽  
Trajectory Data ◽  
Microscopic Simulation ◽  
Data Set ◽  
Lane Changing ◽  
Change Behavior ◽  
Essential Components

Lane-changing models are essential components for microscopic simulation. Although the literature recognizes that different classes of vehicles have different ways of performing lane-change maneuvers, lane change behavior of truck drivers is an overlooked research area. We propose that truck drivers are heterogeneous in their lane change behavior too and that inter-driver differences within truck drivers exist. We explore lane changing behavior of truck drivers using a trajectory data set collected around motorway bottlenecks in the Netherlands which include on-ramp, off-ramp, and weaving sections. Finite mixture models are used to categorize truck drivers with respect to their merging and diverging maneuvers. Indicator variables include spatial, temporal, kinematic, and gap acceptance characteristics of lane-changing maneuvers. The results suggest that truck drivers can be categorized into two and three categories with respect to their merging and diverging behaviors, respectively. The majority of truck drivers show a tendency to merge or diverge at the earliest possible opportunity; this type of behavior leads to most of the lane change activity at the beginning of motorway bottlenecks, thus contributing to the raised level of turbulence. By incorporating heterogeneity within the lane-changing component, the accuracy and realism of existing microscopic simulation packages can be improved for traffic and safety-related assessments.

Parametric study of microscopic two-dimensional traffic flow models: A literature review

2018 ◽  
Vol 45 (11) ◽  
pp. 909-921 ◽  
Author(s):  
Geetimukta Mahapatra ◽  
Akhilesh Kumar Maurya ◽  
Partha Chakroborty
Keyword(s):  
Simulation Models ◽  
Lateral Position ◽  
Two Dimensional ◽  
Mixed Traffic ◽  
Lane Changing ◽  
The Real ◽  
Flow Models ◽  
Traffic Stream ◽  
Traffic Flow Models ◽  
Lane Based

Indian traffic is highly heterogeneous consisting of all-inclusive vehicle characteristics, occupying any lateral position over the entire road width which results in vehicles continuous interaction with the neighbouring vehicles (in both longitudinal and lateral directions), indicating two-dimensional (2D) traffic manoeuvre, opposite to the traditional one-dimensional (1D) interaction of vehicles in lane based traffic. Certain modifications were made in the existing 1D models to describe the overtaking and lane changing manoeuvre of the mixed traffic stream. However, the continuous lateral manoeuvre of the no-lane based mixed traffic cannot be described by these parameters. This paper initially provides a brief review of different 2D behavioural models, which describe the longitudinal and lateral movements simultaneously. Also, the various existing commercially available traffic micro-simulation frameworks developed for representing the real traffic are reviewed. Different microscopic traffic parameters used in the existing simulation models to mimic the real-world traffic are identified, which can be used to understand the 2D traffic stream.

scholarly journals Analysis of the Relationship between the Density and Lane-Changing Behavior of Circular Multilane Urban Expressway in Mixed Traffic

2022 ◽  
Vol 2022 ◽  
pp. 1-40
Author(s):  
Han Xie ◽  
Juanxiu Zhu ◽  
Huawei Duan
Keyword(s):  
Linear Relationship ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Heavy Traffic ◽  
Traffic Density ◽  
Flow Density ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Urban Expressway ◽  
The Relationship

The behavior of changing lanes has a great impact on road traffic with heavy traffic. Traffic flow density is one of the important parameters that characterize the characteristics of traffic flow, and it will also be affected by the behavior of changing lanes, especially in the case of each lane. The penetration of autonomous vehicles can effectively reduce lane-changing behavior. Studying the relationship between traffic flow density and lane-changing behavior under different autonomous vehicle penetration rates is of great significance for describing the operation mechanism of mixed traffic flow and the control of mixed traffic. In this article, we use empirical, simulation, and data-driven methods to analyze the urban expressway of autonomous vehicles with penetration rates of 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation experiment was carried out on the road, and data related to density, the rate of changing into the lanes, and the rate of changing out lanes were collected. The analysis of the experimental results found the following: (1) The increase in penetration of autonomous vehicles leads to a certain degree of downward trend in density, the rate of changing into the lanes, and the rate of changing out lanes. (2) Different lanes have different effects on the penetration of autonomous vehicles. In a 4-lane road, the two lanes farther from the entrance and exit are closer in appearance, while the two lanes closer to the entrance and exit are similar. (3) The relationship between density and the rate of changing into the lanes and the rate of changing out lanes shows a linear relationship with the penetration of autonomous vehicles. Although the performance of each lane is slightly different, in general, it can be carried out by a multiple regression model. The given parameter value range is relatively close under different permeability. In summary, autonomous vehicles effectively reduce the traffic density and lane-changing behavior of each lane. There is a linear relationship between traffic flow density and lane-changing behavior with the penetration of autonomous vehicles. The density-lane-changing behavior model proposed in this paper can better describe the relationship between the density of the circular multilane urban expressway and the lane-changing behavior in the case of a large traffic flow in mixed traffic.

A Cellular Automata Asymmetric Lane-Changing Model with Mixed Traffic

2014 ◽  
Vol 1030-1032 ◽  
pp. 1937-1940
Author(s):  
Jian Hui Zhu
Keyword(s):  
Computer Simulation ◽  
Cellular Automata ◽  
Traffic Flow ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Mixed Traffic Flow ◽  
Road Characteristics

Considered the influence of buses on cars’ change lanes and lane-changing of buses, this paper built an asymmetric cellular automata lane changing model under mixed traffic flow based on symmetric two-lane cellular automata lane-changing model and studied driveway occupancy and road characteristics with related parameters. Computer simulation showed that bus ratio has significant impact on lane-changing probability of vehicles.

Hidden Markov Model of Lane-Changing-Based Car-Following Behavior on Freeways using Naturalistic Driving Data

2021 ◽  
pp. 036119812199938
Author(s):  
Li Zhao ◽  
Laurence Rilett ◽  
Mm Shakiul Haque
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Gaussian Mixture ◽  
Vehicle Body ◽  
Lane Change ◽  
Lane Changing ◽  
Car Following ◽  
Pilot Model ◽  
Naturalistic Driving

This paper develops a methodology for simultaneously modeling lane-changing and car-following behavior of automated vehicles on freeways. Naturalistic driving data from the Safety Pilot Model Deployment (SPMD) program are used. First, a framework to process the SPMD data is proposed using various data analytics techniques including data fusion, data mining, and machine learning. Second, pairs of automated host vehicle and their corresponding front vehicle are identified along with their lane-change and car-following relationship data. Using these data, a lane-changing-based car-following (LCCF) model, which explicitly considers lane-change and car-following behavior simultaneously, is developed. The LCCF model is based on Gaussian-mixture-based hidden Markov model theory and is disaggregated into two processes: LCCF association and LCCF dissociation. These categories are based on the result of the lane change. The overall goal is to predict a driver’s lane-change intention using the LCCF model. Results show that the model can predict the lane-change event in the order of 0.6 to 1.3 s before the moment of the vehicle body across the lane boundary. In addition, the execution times of lane-change maneuvers average between 0.55 and 0.86 s. The LCCF model allows the intention time and execution time of driver’s lane-change behavior to be forecast, which will help to develop better advanced driver assistance systems for vehicle controls with respect to lane-change and car-following warning functions.

scholarly journals Automatic Lane-Changing Decision Based on Single-Step Dynamic Game with Incomplete Information and Collision-Free Path Planning

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 173
Author(s):  
Hongbo Wang ◽  
Shihan Xu ◽  
Longze Deng
Keyword(s):  
Path Planning ◽  
Dynamic Game ◽  
Single Step ◽  
Bézier Curve ◽  
Vehicle Safety ◽  
Bezier Curve ◽  
Lane Change ◽  
Hardware In The Loop ◽  
Power Performance ◽  
Lane Changing

Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic game with incomplete information and path planning based on Bézier curve are proposed in this paper to coordinate vehicle lane-changing performance from safety payoff, velocity payoff, and comfort payoff. First, the lane-changing safety distance which is improved by collecting lane-changing data through simulated driving, and lane-changing time obtained by Bézier curve path planning are introduced into the game payoff, so that the selection of the lane-changing start time considers the vehicle safety, power performance and passenger comfort of the lane-changing process. Second, the lane-changing path without collision to the forward vehicle is obtained through the constrained Bézier curve, and the Bézier curve is further constrained to obtain a smoother lane-changing path. The path tracking sliding mode controller of front wheel angle compensation by radical basis function neural network is designed. Finally, the model in the loop simulation and the hardware in the loop experiment are carried out to verify the advantages of the proposed method. The results of three lane-changing conditions designed in the hardware in the loop experiment show that the vehicle safety, power performance, and passenger comfort of the vehicle controlled by the proposed method are better than that of human drivers in discretionary lane change and mandatory lane change scenarios.

Sign in / Sign up

Export Citation Format

Share Document