Intelligent traffic management at intersections supported by V2V and V2I communications

Bento, Luis Conde; Parafita, Ricardo; Nunes, Urbano

doi:10.1109/itsc.2012.6338766

Cited by 63 publications

(25 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since vehicles without communication capabilities cannot be excluded, [19], [22] and [23] suggest several algorithms both in roundabouts and classical intersections, based on spatio-temporal reservation technique.…”

Section: State Of the Artmentioning

confidence: 99%

Cooperative Intelligence in Roundabout Intersections Using Hierarchical Fuzzy Behavior Calculation of Vehicle Speed Profile

Bosankic¹,

Mehmedović

2016

MATEC Web Conf.

View full text Add to dashboard Cite

Abstract. In this paper, a new fuzzy-behavior-based algorithm for roundabout intersection management is presented. The algorithm employs cooperative intelligence and includes intelligent vehicles and infrastructure to calculate speed profiles for different vehicles, in order to achieve more comfortable driving profiles, as well to reduce congestion and CO2 emissions. The algorithm uses adaptive spatio-temporal reservation technique and was tested in MATLAB/Simulink environment. The algorithm is designed to function in different scenarios with both cooperative and non-cooperative vehicles, as well as optional intersection infrastructure. Results have show that using the proposed algorithm different vehicle communication types can be successfully combined in order to increase traffic flow through roundabout intersections.

show abstract

Section: State Of the Artmentioning

confidence: 99%

Cooperative Intelligence in Roundabout Intersections Using Hierarchical Fuzzy Behavior Calculation of Vehicle Speed Profile

Bosankic¹,

Mehmedović

2016

MATEC Web Conf.

View full text Add to dashboard Cite

show abstract

“…In most existing intersection traffic management methods including [2][3][4][5][6]9,[14][15][16], vehicles' intersection usages are scheduled on the basis of individual vehicles without grouping them and scheduling the groups as batches. We observe that these approaches often introduce additional delays to avoid collisions between streams of cars coming from different directions.…”

Section: B Motivation For Win-fit: Individual Cars Vs Groupsmentioning

confidence: 99%

“…A number of approaches have been developed to improve the intersection throughput, i.e., the total number of cars that pass an intersection per unit time, for cooperative autonomous vehicles, while avoiding collisions. Vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communications based DSRC [18] and WAVE [19] standards are utilized by autonomous vehicles to interact with each other or an infrastructure node to exchange the driving information and share the intersection state to decide, if each vehicle can drive through the intersection or it has to stop based on certain criteria [2][3][4][5][6]9,14,15]. In most existing approaches, including [2][3][4][5][6]9,14,15], intersection scheduling decisions are made on the basis of individual vehicles in either a centralized or distributed manner.…”

Section: Introductionmentioning

confidence: 99%

Win-fit: Efficient intersection management via dynamic vehicle batching and scheduling

Chen

Kang

2015

2015 International Conference on Connected Vehicles and Expo (ICCVE)

View full text Add to dashboard Cite

Intersection management is one of the most challenging tasks in traffic control. In this paper, to significantly decrease the average delay for autonomous vehicles to cross an intersection without any collision, vehicles are dynamically grouped and a selected winner group is allowed to drive through the intersection as one batch unlike most existing approaches, which only schedule individual autonomous vehicles one by one. Further, certain vehicles in the non-winner groups are allowed to safely cross the intersection during idle time slots (if any) unused by the winner group to further decrease the delay. Our approach has the lower-bound time complexity, and decreases the average trip delay to cross a simulated intersection by 31% -95% compared to several state-of-the-art baselines.

show abstract

“…Besides that, non communicating vehicles should be identified and reported by the road-side infrastructure [9]. In [10], a microscopic traffic simulator was developed to study intelligent traffic management techniques and evaluate their performance at roundabouts and crossroads. In the paper [11], the fuzzybehavior-based algorithm for roundabout intersection management is presented.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Vehicle-to-Vehicle (V2V) Decision Making in Roundabout using Game Theory

Banjanović-Mehmedović¹,

Halilović²,

Bosankic³

et al. 2016

ijacsa

View full text Add to dashboard Cite

Abstract-Roundabout intersections promote a continuous flow of traffic. Roundabouts entry move traffic through an intersection more quickly, and with less congestion on approaching roads. With the introduction of smart vehicles and cooperative decision-making, roundabout management shortens the waiting time and leads to a more efficient traffic without breaking the traffic laws and earning penalties. This paper proposes a novel approach of cooperative behavior strategy in conflict situations between the autonomous vehicles in roundabout using game theory. The game theory presents a strategic decision-making technique between independent agents -players. Each individual player tends to achieve best payoff, by analyzing possible actions of other players and their influence on game outcome. The Prisoner's Dilemma game strategy is selected as approach to autonomous vehicle-to-vehicle (V2V) decision making at roundabout test-bed, because the commonly known traffic laws dictate certain rules of vehicle's behavior at roundabout. It is shown that, by integrating non-zero-sum game theory in autonomous vehicle-to-vehicle (V2V) decision making capabilities, the roundabout entry problem can be solved efficiently with shortened waiting times for individual autonomous vehicles.

show abstract

Intelligent traffic management at intersections supported by V2V and V2I communications

Cited by 63 publications

References 9 publications

Cooperative Intelligence in Roundabout Intersections Using Hierarchical Fuzzy Behavior Calculation of Vehicle Speed Profile

Cooperative Intelligence in Roundabout Intersections Using Hierarchical Fuzzy Behavior Calculation of Vehicle Speed Profile

Win-fit: Efficient intersection management via dynamic vehicle batching and scheduling

Autonomous Vehicle-to-Vehicle (V2V) Decision Making in Roundabout using Game Theory

Contact Info

Product

Resources

About