Traffic Improvement in Manhattan Road Networks With the Use of Parallel Hybrid Biobjective Genetic Algorithm

Abstract

There are many reasons for traffic congestions such as the "stop-and-go wave effect", periodic increase in intensity of vehicle and pedestrian traffic ("rush hours"), frequent maneuvering, uncontrolled pedestrians' movement on road crossings and other factors. This paper considers the problem of biobjective optimization and rebalancing of vehicles' and pedestrians' flows with the use of Manhattan road networks (MRNs) with smart traffic lights (STLs) as the case study of intelligent transportation system (ITS). For this purpose, we have studied the possibilities of applying STLs to control of traffic in large-scale road networks providing a speed harmonization and traffic prioritization between vehicles and pedestrians. The considered multiagent system (MAS) includes agent vehicles, agent pedestrians and agent lights that interact with each other according with given rules (e.g., V2V, V2P, V2I). Such STLs use information on the traffic structure and its density to switch signals at each moment in time. In the non-stationary mode with a periodic traffic intensity to provide the analysis of traffic flows done by STLs it has been suggestedto use the fuzzy clustering algorithm aggregated with the density-based spatial clustering algorithm (FCA-DBSCAN). At the uniform motion fixed durations of phases set up for STLs that computed individually with use of the suggested parallel hybrid biobjective real-coded genetic algorithm (BORCGA-BOPSO). The approach allows to improve significantly the time-efficiency of seeking optimal individualised STLs' characteristics while keeping up their quality. Moreover, the ITS based on STLs with parameters optimized with the BORCGA-BOPSO provides significant traffic improvement in MRNs in contrast to the case of uncontrolled pedestrian crossings and using usual (i.e., non-smart) traffic lights.

Exploring the Spatio-Temporally Heterogeneous Impact of Traffic Network Structure on Ride-Hailing Emissions Using Shenzhen, China, as a Case Study

“…Additionally, longer travel distances are generally associated with higher emissions, which is particularly evident in long-distance commuting between cities or suburbs [35,36]. Furthermore, there has been a growing interest among scholars in investigating the impact of traffic signal control efficiency on travel emissions [37,38]. This is because the "stop-and-go" characteristics of vehicles, often experienced before traffic lights, contribute to traffic congestion and subsequently increase emissions.…”

Classification of Computer Attacks Using Multifractal Spectrum of Fractal Dimension

“…Многочисленные исследования статистических характеристик сетевого трафика и сетевых компьютерных атак (КА) показывают наличие у них свойств фрактальности или самоподобия, а также изменчивость показателей, характеризующих фрактальные свойства [1][2][3]. Для оценки степени самоподобия используются понятия фрактальной размерности (ФР) множества (по Хаусдорфу) D и показатель Херста H, характеризующий степень самоподобия процесса, связанные между собой соотношением: D = 2 -H.…”

Evaluation of Sustainable Behavior and Acceptance of Electric Public Transportation: A Perspective from the Philippines

“…Alongside the development of public transportation, one of the goals among developing countries would be to create smart cities. Adopting the suggestions made by Akopov and Beklaryan [142], it could be posited that smart traffic lights addressing heavy traffic flow, optimal stop-and-go signaling, and prioritization between pedestrian and vehicle flows could effectively impact traffic issues. Traffic issues are one of the main problems in the Philippines today, but the country could adopt the application made and developed by this study for a more time-efficient traffic flow.…”