ABSTRACT
Transportation problems have always been a global concern. The challenges in traffic congestion were easily observed during pre-pandemic times. However, traffic congestion still persists even during the COVID-19 pandemic (2020 and present) where there has been less number of vehicles because of travel restrictions. The emergence of wireless communication technologies and intelligent transportation systems (ITS) pave the way for solving some of the problems found in the transportation industry. Subsequently, traffic control systems are used at various intersections to manage the flow of traffic and reduce car collisions. However, some intersections are better off without these traffic control systems. The proposed study will analyze a T-junction road in five different setups using different types of traffic controllers. The simulation tool used is SUMO. The study found that an adaptive or vehicle-actuated traffic controller is the ideal method for regulating traffic flow in a T-junction with a one-way or two-way main road. It was observed in the simulation that it reduced the potential car collisions in the non-TL junction. However, the average speed and completion time of the road network was affected by the method. © 2022 IEEE.
ABSTRACT
One of the greatest challenges for a traffic control system is to synchronize the flow of vehicles to prevent traffic jams. This issue gets worse when there are priority vehicles, such as ambulances, trying to move through the traffic. Given the current situation, with the COVID-19 pandemic, and the trends of smart cities, in this work, we propose and simulate a traffic control system that prioritizes ambulances within large urban centers, using Fuzzy logic and IoT devices. The simulation of our proposed model was performed on the software Dojot, which is an open platform for IoT modeling. It addressed a real situation, in a path that is usually used by ambulances to get to a reference hospital in the city of Campinas, Brazil. The proposed traffic control system can also be used after the COVID-19 pandemic is over in order to improve traffic flow for other priority vehicles (e.g., firefighters and police) and increase people’s life quality within smart cities. © 2022, Springer Nature Switzerland AG.
ABSTRACT
With the outbreak of the novel coronavirus pneumonia (COVID-19), urban traffic control is an important measure to block the spread and control the development of the epidemic. In this study, to elucidate the blocking effects of different traffic control measures on the transmission of COVID-19 within city territories, the four administrative cities of Jingzhou, Xiaogan, Jingmen, and Shijiazhuang were selected as the study areas. The situation of the epidemic before and after the implementation of three typical traffic control measures-road closure, passenger traffic stoppage, and community population flow control-was analyzed. Based on the classical dynamics theory of infectious diseases, an optimized epidemic transmission susceptible, infectious, removed, exposed (SEIR) model was established, considering the infectivity of the exposed, population migration, and population flow in urban communities. Thereafter, the model was used to study the blocking effects based on whether traffic control measures were implemented in each city and the various traffic control measures on the development of the epidemic. The results indicate that the daily incidence rate of each city is related to the immigration index of approximately 14 days ago;the traffic control measures adopted by each city are also highly effective in blocking the spread of the epidemic. Compared with no traffic control measures, the peak numbers of infected persons in Jingzhou, Xiaogan, Jingmen, and Shijiazhuang decreased by 61.29%, 53.71%, 66.16%, and 66.33%, respectively. The blocking effects of the three control measures exhibit a few differences. The blocking effect of road closure measures is the most prominent;the numbers of latent and infected persons can be reduced by 40.54%-70.88% and 49.11%-64.34%, respectively, using different implementation nodes. Furthermore, a timely and comprehensive implementation of the three traffic control measures can effectively block the spread of the epidemic and control the development of the epidemic in cities. This improved SEIR model, which considers the characteristics of the incubation period, can accurately predict the development trends of the epidemic, thus serving as a technical reference for the formulation of urban traffic control plans over the duration of the epidemic. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.
ABSTRACT
As India is in its developing stage and the traffic on the other side in India is very heterogeneous or mixed in its nature and the average growth rate of vehicles in India is about 8%. With the increase rate of urbanization in India it will lead to the considerable traffic and travel growth on the roads which will result in vehicular delays, long queues and traffic congestion. So, in this paper with the help of traffic simulation software, i.e. VISSIM, three simulation of an unsignalized intersection {Dadour and Una-Jahu, Nerchowk Rd. (NH-21),H.P} will be analyzed and will compare them on the basis of vehicular delays and long queues. These three simulation will be analyzed on the basis of real world traffic data which is less from the expectations due to the pandemic covid-19, theoretical traffic data (increase in real data by 30%) and theoretical traffic data {with traffic signals as theoretical data follows warrant 1 (Min. Vehicular Volume) shown in IRC:93:1985}. Result showed that with increase in vehicular data there was not so much variation in vehicular delays, whereas there was an increase in long queues or queue stops and whilst third simulation (with traffic lights) is done it shows that it overcomes the queue stops of the intersection. © 2022, Springer Nature Singapore Pte Ltd.