Cellular Automata Model for Mixed Traffic Flow with Lane Changing Behavior

Hanumappa, Devaraj; Ramachandran, Parthasarathy

doi:10.1155/2021/9142790

Cited by 4 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The relevant observation is that no trailing car is slowing below speed 1. Notice that the constant speed pattern seems hard to restore and we observe a regular pattern of the form of (5).…”

Section: Analysis Of the Owmentioning

confidence: 85%

See 1 more Smart Citation

Maximum Traffic Flow Patterns in Interacting Autonomous Vehicles

Cohen

Chopard

Leone

2022

Lecture Notes in Computer Science

View full text Add to dashboard Cite

We consider the auto-organization of a set of autonomous vehicles following each other on either an innite or circular road. The behavior of each car is specied by its "speed regulator", a device that decides to increase or decrease the speed of the car as a function of the head-tail distance to its predecessor and the speed of both cars. A collective behavior emerges that corresponds to previously proposed cellular automata trac models. We further analyze the trac patterns of the system in the long term, as governed by the speed regulator and we study under which conditions trac patterns of maximum ow can or cannot be reach. We show the existence of suboptimal ow conditions that require external coordination mechanisms (that we don not consider in this paper) in order to reach the optimal ow achievable with the given density.

show abstract

Section: Analysis Of the Owmentioning

confidence: 85%

“…Classical analysis of trac models amount to classify the dierent dynamics and identify the conditions for transition, for instance the existence of on/oramp [7,6,4], trac lights [2], lane changing [15], mixed-trac [13], and combinations [5].…”

Section: Introductionmentioning

confidence: 99%

Maximum Traffic Flow Patterns in Interacting Autonomous Vehicles

Cohen

Chopard

Leone

2022

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…LITERATURE REVIEW Proposed 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 (Hanumappa and Ramachandran 2021). Numerous researchers comprehensively reviewed recent developments in modeling lane-changing behavior.…”

Section: IImentioning

confidence: 99%

User Opinion on Factors Affecting Drivers Frequent Lane-Changing Behavior: A National Sample of Drivers in Pakistan

Jilani

2023

IJRASET

View full text Add to dashboard Cite

In recent years massive traffic volume increase has demanded the implementation of traffic improvement plans in Pakistan. The urban Highway transportation networks are becoming congested in developed as well as in most of the developing countries. The main causes of unmanageable heterogeneous traffic congestion on the highway are an increase in population, change in lifestyle, and economic development of a country. To recognize the characteristics of a driver who frequently changes lanes and analyze the techniques of frequent lane-changing behavior. The researchers collected data via a questionnaire survey and analyzed the influence of traffic environment and driver characteristics violation on frequent lane-changing behavior on travel speed in detail by manually Excel statistics. Results showed that the impact of a heterogeneous traffic environment of two lanes and three lanes cars, and traffic flow density was sharply associated with frequent lane-changing behavior. The drivers were the main factors affecting frequent lane-changing behavior in heterogeneous traffic conditions, which was most popular during aggressive driving. Only 8.33% of drivers were never involved in this behavior. Most liable to frequent lane-changing behavior were males as compared to females, 31–40-year-old drivers, and those with low academic qualifications and private vehicle personalities. Among various traffic factors, changes in required speed had the most significant impact on how often lane changes occurred. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency. This research recommends strict enforcement of lane discipline to counter traffic congestion and the remedial measures that are to be taken for the improvement of better and sustainable road infrastructure conditions. Overall the research study will have practical implications for improving traffic management and safety on highways, and it provides a foundation for further research in the field of traffic-related technologies.

show abstract

Optimal safe driving dynamics for autonomous interacting vehicles

Cohen,

Chopard,

Leone

2023

Nat Comput

View full text Add to dashboard Cite

We consider the car following problem for a set of autonomous vehicles following each other on either an infinite or circular road. The behavior of each car is specified by its "speed regulator", a device that decides to increase or decrease the speed of the car as a function of the head-tail distance to its predecessor and the speed of both cars. A collective behavior emerges that corresponds to previously proposed cellular automata traffic models. We further analyze the traffic patterns of the system in the long term, as governed by the speed regulator and we study under which conditions traffic patterns of maximum flow can or cannot be reach. We show the existence of suboptimal flow conditions that require external coordination mechanisms (that we do not consider in this paper) in order to reach the optimal flow achievable with the given density. In contrast with other approaches, we do not try to reproduce observed or measured traffic patterns. We analyze a deterministic speed regulator in order to decipher the emergent dynamics, and to ponder what maneuvers can be safely performed. Here, we restrict our attention to the car following problem. By comparing our speed regulator with classical models, auch as the Nagel–Schreckenberg and KKW models, we observe that although our regulator is formulated in simple terms, its dynamics share similarities with these models. In particular, the KKW model is designed to reproduce the observed behavior that a trailing car in the synchronization range of the leading car tends to regulate its speed to maintain a constant distance. this same behavior is adopted by our speed regulator, showing that this is a safe way of driving.

show abstract

Cellular Automata Model for Mixed Traffic Flow with Lane Changing Behavior

Cited by 4 publications

References 31 publications

Maximum Traffic Flow Patterns in Interacting Autonomous Vehicles

Maximum Traffic Flow Patterns in Interacting Autonomous Vehicles

User Opinion on Factors Affecting Drivers Frequent Lane-Changing Behavior: A National Sample of Drivers in Pakistan

Optimal safe driving dynamics for autonomous interacting vehicles

Contact Info

Product

Resources

About