An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent transportation systems

Younes, Maram Bani; Boukerche, Azzedine

doi:10.1007/s11276-017-1482-5

Cited by 80 publications

(43 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, innovative systems, such as the Internet of Vehicles, may collect data, such as vehicle speed and vehicle operations, using Global Positioning System (GPS) and sensors located in the car. This information is transmitted to the urban traffic brain through Internet technology to monitor road traffic conditions and intelligently adjust the cycle of signal lights (to better serve to alleviate traffic congestion) [42][43][44][45][46][47]. However, this information can also be used to assess driver insurance risks, with adverse consequences for privacy rights.…”

Section: Research Hypothesesmentioning

confidence: 99%

Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China

2020

View full text Add to dashboard Cite

More countries and regions are joining the bandwagon of smart city construction, which is an important strategy and innovative urban governance concept to solve the problem of rapid urbanization. This paper examines whether smart city innovation is able to ameliorate the traffic congestion faced by a large number of cities. Using panel data for 187 prefecture-level cities in China from 2008 to 2017, this paper tests the effect of implementation of a smart city on urban traffic congestion with the difference-in-difference method. The results show that, firstly, the construction of smart cities have significantly reduced the degree of urban traffic congestion and improved the quality and capacity of public transport. Secondly, information technology and urban innovation are the main mechanisms for smart city implementation to improve urban traffic problems. Thirdly, the improvement effect of smart city implementation on traffic management shows an increasing marginal effect over time. By overcoming the estimation bias in previous studies, this study accurately analyzes the positive role and dynamic effect of smart city construction on traffic improvement. It augments the literature of program evaluation and assessment of smart city implementation. By examining how to improve traffic congestion, it offers some insights that could inspire governments to build smarter cities with better traffic.

show abstract

Section: Research Hypothesesmentioning

confidence: 99%

Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China

2020

View full text Add to dashboard Cite

show abstract

“…Younes and Boukerche [3] introduced a dynamic traffic light scheduling algorithm. This algorithm schedules the competing flows at any signalized intersection, to allow the more dense traffic flows to cross the intersection first.…”

Section: Related Workmentioning

confidence: 99%

Management of Vehicular Traffic System using Artificial Bee Colony Algorithm

Adebiyi¹,

Abubilal²,

Tekanyi³

et al. 2017

IJIGSP

View full text Add to dashboard Cite

Abstract-In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition in order to minimize the Average Waiting Time (AWT) at the cross intersection. A MATLAB based Graphic User Interface (GUI) traffic control simulator was developed. In order to demonstrate the effectiveness of the developed ADSA this paper was validated with the existing work in the literature. The result obtained for the AWT of the developed ADSA had a performance of 76.67%. While for vehicular queues cleared at the intersection the developed ADSA had a performance of 53.33%. The results clearly expressed that the developed ADSA method has been successful in minimizing the Average Waiting Time and vehicular queues at the intersection.

show abstract

“…Similar strategies are used for rail preemption and transit signal priority [2]. However, it may also produce a negative impact on the general traffic not only at the same intersection where the EV is approaching but also on other neighboring intersections, especially in the case of coordinated signal control [3,4].…”

Section: Introductionmentioning

confidence: 99%

A Strategy for Emergency Vehicle Preemption and Route Selection

2019

View full text Add to dashboard Cite

Emergency vehicle preemption (EVP) aims to give right of way to emergency vehicles (EV) heading toward the incident location through a network of signalized intersections by creating a green wave en-route. The design goals of EVP systems are two folds: first, to avoid any hindrance to the passage of EV along the road and at the intersections and second, to reduce the negative impact of preemption on general traffic. The negative impact of EVP on normal traffic can be minimized by selecting appropriate preemption strategy. The EVP schemes proposed earlier aim to minimize the travel time of the EV with no or little consideration to the negative impact of EVP on the normal traffic. In this study, a joint strategy for optimal path selection and EV preemption is developed. The proposed scheme selects the optimal path for the EV before it departs from its origin and then activates the preemption on each intersection en-route at the right time to clear the intersection before the EV reaches. The proposed EVP scheme also aims to minimize the impact of EVP over normal traffic at both stages (i.e., path selection phase and preemption phase). A major advantage of the proposed method is that once the optimal path is selected, the emergency information can be disseminated to other vehicles using vehicle-to-vehicle and vehicle-to-infrastructure communication in the EV path to clear the entire route or the approaching lane. The strategy was tested using a microscopic simulation environment for a real traffic network. The findings indicated a major reduction in the travel time of the EV while minimizing the impact of preemption on the normal traffic. The proposed strategy and evaluation procedure can be helpful for corresponding agencies and practitioners to assess the impact of implementing preemption on existing or proposed arterials.

show abstract

An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent transportation systems

Cited by 80 publications

References 14 publications

Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China

Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China

Management of Vehicular Traffic System using Artificial Bee Colony Algorithm

A Strategy for Emergency Vehicle Preemption and Route Selection

Contact Info

Product

Resources

About