Mitigating flash crowd effect using connected vehicle technology

Grzybek, Agata; Danoy, Grégoire; Bouvry, Pascal; Seredynski, Marcin

doi:10.1016/j.vehcom.2015.10.002

Cited by 14 publications

(10 citation statements)

References 30 publications

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“…With decentralized coordination between vehicles based on the freedom degrees that each vehicle has available to avoid collision [60]. A design of traffic simulation models for such vehicles for exchanging information to reduce the average delay and minimize traffic congestion for vehicles could be clearly seen in [48,[61][62][63][64][65]]. An experimental model and simulation for pertaining the performance of IEEE 802.11p communication standard is used in [28] and robust decision support tool for cooperative traffic simulation [46].…”

Section: Traffic Management Applicationsmentioning

confidence: 99%

A review on vehicle to vehicle communication system applications

Ameen¹,

Mahamad²,

Saon³

et al. 2020

IJEECS

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<span>The field of automated vehicle technology is developing rapidly developing. While it is likely to be many years before self-driving cars are commercially viable and used in a wide range of conditions by the general public, technological advances are speeding along the automated technology continuum towards this destination. Automated vehicle technologies troth with significant social benefits such as reduced injuries and deaths, increased road efficiency, mobility. Automated vehicles can improve traffic safety, balance traffic flows, maximize road usage by offering driver warnings and/or assuming vehicle control in dangerous situations, as well as provide motorists with the best end-to-end transportation experience and reduce emissions, which are the most important goals of modern smart traffic control infrastructures. Exchanging data and integration of such systems with Vehicle-to-Vehicle (V2V) may be a keystone to successful readying of vehicular ad-hoc networks (VANETs) and will simply be the following step of this evolution, with dynamic period of time data exchange between all the players of the traffic dominant system and fostering cooperative urban quality. One of the applications of this concept is to provide vehicles and roads with the ability to make road time more enjoyable and also to make roads safer. These applications are typical examples of what an Intelligent Transportation System (ITS) is called, whose objective is to improve security by using new information and communication technologies (NTIC). In this paper, we will focus on the study of the main component in ITS systems and present a review of the major V2V benefits related to driver safety by focusing primarily on the recent developments of these systems.</span>

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Section: Traffic Management Applicationsmentioning

confidence: 99%

A review on vehicle to vehicle communication system applications

Ameen¹,

Mahamad²,

Saon³

et al. 2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…In addition, other works focus on cross-layer protocol for traffic management, calculation of the desired vehicles' speed necessary to cross and distribution of datagathering protocol for the collection of delay tolerant to make the congestion control efficient [40]- [43]. The problem of routing guidance in nonrecurring congestion caused by temporary loss of capacity is also addressed in [44]. The authors in [45]- [49] focus on new Geocast approaches, forwarding protocols for mitigating the interest broadcast storm and the disconnected link problems in a car-following control scheme and sampling-based estimation schemes (SESs).…”

Section: ) Developmentmentioning

confidence: 99%

“…Other topics include a wide measuring of incoming traffic [69] and full distribution of traffic information systems that enable traffic selforganisation in smart cities [75], [132]. Research has been performed on designing efficient microscopic traffic simulation model for such vehicles, including a robust protocol for exchanging information to improve and reduce traffic congestion, minimise average delay for vehicles [44], [56], [57], [73], [94], [100], simulations and an experimental model pertaining to the performance of IEEE 802.11p communication standard to reduce traffic congestion [66] and robust decision support tool for cooperative traffic simulation [65].…”

Section: E Motivationsmentioning

confidence: 99%

A Deep Review and Analysis of Data Exchange in Vehicle-to-Vehicle Communications Systems: Coherent Taxonomy, Challenges, Motivations, Recommendations, Substantial Analysis and Future Directions

et al. 2019

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Data exchange in Vehicle-to-vehicle (V2V) communications systems is a field that requires automated solutions, tools and methods and the capability to facilitate early detection and even a prediction. Many studies have focused on V2V system and its classification to improve road safety, reduce traffic congestion and help streamline the vehicle flow on the road. This study aims to review and analyse literature related to data exchange in V2V communications systems. The factors considered to improve the understanding of the field's various contextual aspects were derived from published studies. We systematically searched all articles about the classification and detection of data exchange in vehicles, as well as their evaluation. Three main databases, namely, ScienceDirect, Web of Science and IEEE Xplore from 2008 to 2018, were used. These indices were considered sufficiently extensive to encompass our literature. On the basis of our inclusion and exclusion criteria, 140 articles were selected. Most articles (53/140) are studies conducted in a V2V communication system; a number of papers (51/140) covered the actual attempts to develop V2V communications; and few papers (18/140) comprised framework proposals and architectures. The last portion (18/140) of articles presented review and survey articles. V2V collision avoidance system, which is a field requiring automated solutions, tools and methods, entails the capability to facilitate early detection. Several studies have been performed on the automatic detection of V2V and their subtypes to promote accurate detection. The basic characteristics of this emerging field are identified from the aspects of motivations, open challenges that impede the technology's utility, authors' recommendations and substantial analysis of the previous studies are discussed based on seven aspect (devices, number of scenario, test location, types of sensors, number of vehicle, evaluation techniques used and types of software). A propose research methodology as new direction is provided to solve the gaps identified in the analysis. This methodology consists of four phases; investigation, develop a hardware system, study and analysis, and evaluation phases. However, research areas on V2V communication with the scope of data exchange are varied. This systematic review is expected to open opportunities for researchers and encourage them to work on the identified gaps.

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“…Finally, in-vehicle routing systems can also be used to incentivize cooperation between vehicles (Helbing et al, 2005;Kato et al, 2002). However, more common in literature are decentralized approaches that use instantaneous traffic information (Grzybek et al, 2015). Such systems are commonly designed as multi-agent systems, employing nature-inspired metaheuristic algorithms (Cong et al, 2013) or game theoretic principles (Klein and Ben-Elia, 2016;Garcia et al, 2000) for optimization.…”

Section: Introductionmentioning

confidence: 99%

Design analysis of a decentralized equilibrium-routing strategy for intelligent vehicles

Mahajan

Hegyi

Arem

2019

Transportation Research Part C: Emerging Technologies

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Intelligent vehicle technologies are opening new possibilities for decentralized vehicle routing systems, suitable for regulating large traffic networks, and at the same time, capable of providing customized advice to individual vehicles. In this study, we perform a rigorous simulation-based analysis of an in-vehicle routing strategy that aims to achieve a user-equilibrium distribution in traffic. Novel features of the approach include: a mechanism based on forward propagation of individual vehicle decisions to anticipate future traffic dynamics; time-dependent prediction of route travel times with neural network-based link predictors; and a stochastic routing policy for invehicle decision-making based on predicted travel times. However, for an effective application of the approach, design choices need to be made regarding the accuracy of the link predictors, and some control settings. These choices may depend on the network size and structure. We investigate the impact of two important design aspects: sequentially using link-level predictors for route travel time estimation, and the control parameter values, on the equilibrium performance at the networklevel. The results suggest functional scalability of the approach, in terms of the prediction model accuracy and routing performance. Overall, the work contributes to a qualitative and quantitative understanding of emergent performance from the given routing approach. 1. Introduction Dynamic route guidance in freeway or urban traffic networks with time-varying demand and stochastic travel times is a classic transportation problem (Papageorgiou, 1990). At the same time, recent advances in automated and connected vehicle capabilities (Shladover, 2017), boosted by other emerging technologies, like cloud computing, artificial intelligence, big data, and internet of things, are fundamentally transforming the potential and design of traffic control systems (Diakaki et al., 2015; Papageorgiou et al., 2015). In-vehicle route guidance systems, be they satellite navigation devices or GPS enabled smartphone applications, such as Google Maps, Waze, and Apple Maps, are becoming ubiquitous and connected. These trends are making decentralized routing approaches increasingly more practicable. The benefits of a decentralized control structure range from lower computation and communication loads, higher fault tolerance, to robustness against measurement errors, delays and failures. Moreover, decentralized decision-making makes it possible to provide personalized advice to individual vehicles. We focus on decentralized route guidance systems that can achieve a user-equilibrium (UE) condition, famously known as the Wardrop's first principle of route choice

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Mitigating flash crowd effect using connected vehicle technology

Cited by 14 publications

References 30 publications

A review on vehicle to vehicle communication system applications

A review on vehicle to vehicle communication system applications

A Deep Review and Analysis of Data Exchange in Vehicle-to-Vehicle Communications Systems: Coherent Taxonomy, Challenges, Motivations, Recommendations, Substantial Analysis and Future Directions

Design analysis of a decentralized equilibrium-routing strategy for intelligent vehicles

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