State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends

Tomar, Ishu; Indu, S.; Pandey, Neeta

doi:10.3390/electronics11030465

Cited by 30 publications

(12 citation statements)

References 78 publications

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“…Traffic signal control, as an important tool, is widely used in traffic flow management. Research indicates that traffic signal control is currently one of the most effective methods, which can significantly reduce traffic congestion and improve traffic efficiency [1]. The study of signal control at complex traffic intersections remains necessary given the rapid development of sensors and intelligent connected vehicles [2].…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Wu,

Zhou,

Tan

et al. 2023

Preprint

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The paper proposes, for the first time in the field of optimizing regional traffic signals, a model based on a quantum genetic algorithm to solve the problem of traffic congestion at intersections under the existing infrastructure conditions. The model introduces four evaluation criteria: vehicle waiting time, standard deviation, collision percentage, and algorithm execution time. It conducts simulation experiments on three typical intersection types: cross intersections, roundabouts, and diamond intersections. A more optimal regional traffic signal control scheme is proposed. In order to verify the effectiveness of the scheme, a large number of subsequent simulation experiments are conducted. The results demonstrate that, compared to other traditional intelligent algorithms, the algorithm presented in this paper performs better at alleviating traffic congestion at intersections.

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Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Wu,

Zhou,

Tan

et al. 2023

Preprint

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“…Synchronising traffic lights in the surrounding area is a complex process, but it has been investigated by many researchers, such as Tomar et al., who divided the system into levels of synchronisation as in Figure 3 [27].…”

Section: Related Workmentioning

confidence: 99%

“…Intersections mostly have four traffic lights (more or less), each with multiple lanes and two directions (forward and backward) as illustrated in Figure 5. First, we introduce a method to assign F I G U R E 3 Levels of synchronisation [27] F I G U R E 4 The proposed system phases an ID number for each lane on the traffic lights and an ID to distinguish the lane, direction and intersection. The ID can also define the related lanes from all directions that may be affected by the current lane traffic itself.…”

Section: Phase 1: Lane Identificationmentioning

confidence: 99%

Novel system for road traffic optimisation in large cities

et al. 2022

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Traffic congestion and road intersection management have become a significant issue, mainly with the highly increasing number of vehicles in cities. There is a common belief from vehicle drivers that installing traffic lights with some consideration of traffic flows will be dominant in traffic movements. This article proposes a novel system for Urban Traffic Control (UTC) with a continuous dynamic environment adaptation to improve traffic flow on large cities' network roads. The proposed system introduces vehicle counting method, lane evaluation of the current status and controlling method considering the effect on the whole traffic network-not just the intersection itself-to provide an efficient traffic scheduling. The main objective of the authors' system is to reduce traffic jam, by reducing waiting time and trip time for vehicles at intersections. Some indicators and models are introduced in this work to assign traffic flow schedules with minimum traffic congestion and vehicle waiting time. These indicators and models include a traffic jam indicator, vehicle priority and lane weight. A multi-agent urban traffic control system is proposed as the simulation environment using NetLogo simulator. (A total of 150) Vehicles are generated with random behaviour distributed over 25 intersections for 9 h duration to compare the normal fixed cycle traffic light and the authors' smart traffic control. Results show a reduction in the total average waiting time of all vehicles for the simulation period by more than (29.98%). Hence, it is more suitable for the complexity of the current traffic condition with minimum changing infrastructure. K E Y W O R D S road traffic control, road traffic management, smart cities, smart traffic light, urban traffic control, UTC This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…As an example, such inspection could be provided for underwater object surveillance during border control, when it is not easy to give a traditional type of nonintrusive inspection with the fixed control point over large vehicles, such as cruise liners, or at a vast area, such as port or a gulf. In this case, smaller remotely controlled or self-driven vehicles equipped with a set of sensors, transducers, and other technologies for nonintrusive control are in use to provide security inspection activities [ 29 , 30 , 31 , 32 ]. Such vehicles have proven to be effective for underwater inspection, but they still need to be improved with more advanced sensors and signal processing algorithms [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

The Use of Terrestrial and Maritime Autonomous Vehicles in Nonintrusive Object Inspection

Mamchur

Pekša

Kolodinskis

et al. 2022

Sensors

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Traditional nonintrusive object inspection methods are complex or extremely expensive to apply in certain cases, such as inspection of enormous objects, underwater or maritime inspection, an unobtrusive inspection of a crowded place, etc. With the latest advances in robotics, autonomous self-driving vehicles could be applied for this task. The present study is devoted to a review of the existing and novel technologies and methods of using autonomous self-driving vehicles for nonintrusive object inspection. Both terrestrial and maritime self-driving vehicles, their typical construction, sets of sensors, and software algorithms used for implementing self-driving motion were analyzed. The standard types of sensors used for nonintrusive object inspection in security checks at the control points, which could be successfully implemented at self-driving vehicles, along with typical areas of implementation of such vehicles, were reviewed, analyzed, and classified.

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State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends

Cited by 30 publications

References 78 publications

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Novel system for road traffic optimisation in large cities

The Use of Terrestrial and Maritime Autonomous Vehicles in Nonintrusive Object Inspection

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