scholarly journals Intelligently managing mixed traffic flows at intersections Proposal of a platoon-based round-robin algorithm with priorities

2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicles ◽  
State Of The Art ◽  
Control Methods ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Traffic Conditions ◽  
Advisory System ◽  
Intersection Control ◽  
Integration Effort

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>

scholarly journals Intelligently managing mixed traffic flows at intersections Proposal of a platoon-based round-robin algorithm with priorities

2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicles ◽  
State Of The Art ◽  
Control Methods ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Traffic Conditions ◽  
Advisory System ◽  
Intersection Control ◽  
Integration Effort

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>

scholarly journals Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles

Vehicles ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 523-541
Author(s):  
Abdullah Baz ◽  
Ping Yi ◽  
Ahmad Qurashi
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Autonomous Vehicles ◽  
Control Algorithm ◽  
Autonomous Vehicle ◽  
Signalized Intersection ◽  
Mixed Traffic ◽  
Intersection Safety ◽  
Vehicle To Infrastructure ◽  
Intersection Control

The rapidly improving autonomous vehicle (AV) technology will have a significant impact on traffic safety and efficiency. This study introduces a game-theory-based priority control algorithm for autonomous vehicles to improve intersection safety and efficiency with mixed traffic. By using vehicle-to-infrastructure (V2I) communications, this model allows an AV to exchange information with the roadside units (RSU) to support the decision making of whether an ordinary vehicle (OV) or an AV should pass the intersection first. The safety of vehicles is taken in different stages of decisions to assure collision-free intersection operations. Two different mathematical models have been developed, where model one is for an AV/AV situation and model two is when an AV meets an OV. A simulation model was developed to implement the algorithm and compare the performance of each model with the conventional traffic control at a four-legged signalized intersection and at a roundabout. Three levels of traffic volume and speed combinations were tested in the simulation. The results show significant reductions in delay for both cases; for case (I), AV/AV model, a 65% reduction compared to a roundabout and 84% compared to a four-legged signalized intersection, and for case (II), AV/OV model, the reduction is 30% and 89%, respectively.

scholarly journals Variable Speed Limit and Ramp Metering for Mixed Traffic Flows: A Review and Open Questions

2021 ◽  
Vol 11 (6) ◽  
pp. 2574
Author(s):  
Filip Vrbanić ◽  
Edouard Ivanjko ◽  
Krešimir Kušić ◽  
Dino Čakija
Keyword(s):  
Traffic Control ◽  
Ramp Metering ◽  
Transport Infrastructure ◽  
Control Algorithms ◽  
Speed Limit ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Demand

The trend of increasing traffic demand is causing congestion on existing urban roads, including urban motorways, resulting in a decrease in Level of Service (LoS) and safety, and an increase in fuel consumption. Lack of space and non-compliance with cities’ sustainable urban plans prevent the expansion of new transport infrastructure in some urban areas. To alleviate the aforementioned problems, appropriate solutions come from the domain of Intelligent Transportation Systems by implementing traffic control services. Those services include Variable Speed Limit (VSL) and Ramp Metering (RM) for urban motorways. VSL reduces the speed of incoming vehicles to a bottleneck area, and RM limits the inflow through on-ramps. In addition, with the increasing development of Autonomous Vehicles (AVs) and Connected AVs (CAVs), new opportunities for traffic control are emerging. VSL and RM can reduce traffic congestion on urban motorways, especially so in the case of mixed traffic flows where AVs and CAVs can fully comply with the control system output. Currently, there is no existing overview of control algorithms and applications for VSL and RM in mixed traffic flows. Therefore, we present a comprehensive survey of VSL and RM control algorithms including the most recent reinforcement learning-based approaches. Best practices for mixed traffic flow control are summarized and new viewpoints and future research directions are presented, including an overview of the currently open research questions.

scholarly journals An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach

2013 ◽  
Vol 23 (1) ◽  
pp. 183-200 ◽  
Author(s):  
Fei Yan ◽  
Mahjoub Dridi ◽  
Abdellah El Moudni
Keyword(s):  
Genetic Algorithm ◽  
Traffic Control ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Control Methods ◽  
Traffic Condition ◽  
Sequencing Problem ◽  
Genetic Algorithm Approach ◽  
Short Time ◽  
Intersection Management

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.

Anticipatory Optimization of Traffic Control

2000 ◽  
Vol 1725 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Henk J. van Zuylen ◽  
Henk Taale
Keyword(s):  
Traffic Control ◽  
Optimization Problem ◽  
Bilevel Optimization ◽  
Simulation Studies ◽  
Traffic Flows ◽  
System Optimum ◽  
Time Model ◽  
Traffic Conditions ◽  
Made In ◽  
Small Disturbances

Traffic control and travelers’ behavior are two mutually influential processes with different objectives. Decisions made in traffic control influence travelers’ possibilities in choosing their preferred mode, route, and time of departure; and the choices made by travelers influence the optimization possibilities for traffic control. This research presents the results of simulation studies and a mathematical analysis of this bilevel optimization problem. Under certain conditions, multiple stable situations are possible, but some of these situations are sensitive to small disturbances by which the system moves away from the original equilibrium state. There appears to be a nonlinear relationship between system parameters and the character and location of the equilibrium situations. The details of the travel time model appear to have a large influence. If road authorities want to optimize traffic control, they have to anticipate the reaction of travelers. This makes the optimization process much more complicated. Iterative optimization, where traffic control is adjusted as soon as traffic conditions change, generally does not lead to a system optimum. Methods are therefore necessary that allow for the optimization of traffic control while taking into account that traffic flows will change as a result of traffic control.

Multiple-Factors Aware Car-Following Model for Connected and Autonomous Vehicles

2021 ◽  
pp. 036119812110452
Author(s):  
Huaqing Ma ◽  
Hao Wu ◽  
Yucong Hu ◽  
Zhiwei Chen ◽  
Jialing Luo
Keyword(s):  
Autonomous Vehicles ◽  
Transportation Systems ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Simulation Experiments ◽  
Velocity Difference ◽  
Car Following ◽  
Multiple Factors ◽  
Car Following Model ◽  
The Stability

The emergence of connected and autonomous vehicles (CAV) is of great significance to the development of transportation systems. This paper proposes a multiple-factors aware car-following (MACF) model for CAVs with the consideration of multiple factors including vehicle co-optimization velocity, velocity difference of multiple PVs, and space headway of multiple PVs. The Next Generation Simulation (NGSIM) dataset and the genetic algorithm are used to calibrate the parameters of the model. The stability of the MACF model is first theoretically proved and then empirically verified via numerical simulation experiments. In addition, the VISSIM software is partially redeveloped based on the MACF model to analyze mixed traffic flows consisting of human-driven vehicles and CAVs. Results show that the integration of CAVs based on the MACF model effectively improves the average velocity and throughput of the system.

scholarly journals Traffic Equilibrium for Mixed Traffic Flows of Human-Driven Vehicles and Connected and Autonomous Vehicles in Transportation Networks under Tradable Credit Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Fang Zhang ◽  
Jian Lu ◽  
Xiaojian Hu
Keyword(s):  
Autonomous Vehicles ◽  
Network Performance ◽  
Penetration Rate ◽  
User Equilibrium ◽  
Unit Price ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Stochastic User Equilibrium ◽  
Tradable Credit Scheme ◽  
Tradable Credit

In this paper, the traffic equilibriums for mixed traffic flows of human-driven vehicles (HDV) and connected and autonomous vehicles (CAV) under a tradable credit scheme (TCS) are established and formulated as two variational inequality (VI) problems with exogenous and endogenous CAV penetration rate, respectively. A modified Lagrangian dual (MLD) method embedded with a revised Smith’s route-swapping (RSRS) algorithm is proposed to solve the problems. Based on the numerical analysis, the impacts of CAV penetration and the extra expense of using a CAV on network performance are investigated. A novel driveway management, autonomous vehicle/credit charge (AVCC) link, is put forward to improve the efficiency of TCS. Under the TCS with exogenous CAV penetration rate, a logit-based model is applied to describe the stochastic user equilibrium for mixed traffic flow. It is found that the penetration of CAV gives rise to a better network performance and it can be further improved by the deployment of AVCC link. Under the TCS with endogenous penetration rate, a nested-logit model is applied to describe travelers’ choices of vehicle types and routes. It is found that the deployment of AVCC links can slow down the decline rate of CAV penetration with increasing expense and thus ensure a lower average travel time for CAVs. In both cases, the deployment of AVCC links can stimulate credit trading and drop down its unit price.

Sign in / Sign up

Export Citation Format

Share Document