Allan Mariano de Souza

Decreasing greenhouse emissions through an intelligent traffic information system based on inter-vehicle communication

Traffic congestion is an urban mobility problem, which generates stress to drivers and economic losses. In 2012, greenhouse gas emissions from transportation accounted for about 28% of total U.S. greenhouse gas emissions. Intelligent transportation systems can assist in the identification and reduction of vehicular traffic congestion. In this context, this work proposes an intelligent traffic information system based on inter-vehicle communication to avoid vehicle traffic congestion. The main goal of the proposed solution is to decrease CO2 emissions, the average trip time and fuel consumption by avoiding congested roads. Simulation results show that our proposed solution can reduce the average trip time, and the overall CO2 emission and fuel consumption. In particular, the trip time was decreased approximately 86%, the fuel consumption 40% and the CO2 emission 55%. This shows the potential of the proposed solution.

An intelligent transportation system for detection and control of congested roads in urban centers

Traffic jams frustrate drivers and cost billions per year in time and fuel consumption. In order to avoid such problems, this paper presents an intelligent transportation system that collects real-time traffic information and is able to detect and manage traffic congestion based on this information. Simulation results show that the proposed protocol can reduce the average travel time, CO2 emission and fuel consumption. In particular, the average travel time was reduced in approximately 23%, the average fuel consumption in 9% and average CO2 emission in 10%.

Scorpion: A Solution Using Cooperative Rerouting to Prevent Congestion and Improve Traffic Condition

Most large cities suffer with congestion problem, one of the main causes of congestion is the sudden increase of vehicle traffic during peak hours, mainly in areas with bottlenecks. Current solutions in the literature are based on perceiving road traffic conditions and re-routing vehicles to avoid the congested area. However, they do not consider the impact of thesechanges on near future traffic patterns. Hence, these approachesare unable to provide a long-term solution to the congestion problem, since when suggesting alternative routes, they create new bottlenecks at roads closer to the congested one, thus just transferring the problem from one point to another one. With this issue in mind, we propose an intelligent traffic cooperative routing application called SCORPION, which improves the overall spatial utilization of a road network and also reduces the average vehicletravel costs by avoiding vehicles from getting stuck in traffic. Simulation results show that our proposal is able to forecasting congestion and re-route vehicles properly, performing a load balance of vehicular traffic.

Real-time path planning to prevent traffic jam through an intelligent transportation system

Congestion is a major problem in large cities. One of the main causes of congestion is the sudden increase of vehicle traffic during peak hours. Current solutions are based on perceiving road traffic conditions and re-routing vehicles to avoid the congested area. However, they do not consider the impact of these changes on near future traffic patterns. Hence, these approaches are unable to provide a long-term solution to the congestion problem, since when suggesting alternative routes they create new bottlenecks at roads closer to the congested one, thus just transferring the problem from one point to another. With this issue in mind, we propose an intelligent traffic system called CHIMERA, which improves the overall spatial utilization of a road network and also reduces the average vehicle travel costs by avoiding vehicles from getting stuck in traffic. Simulation results show that our proposal is more efficient in forecasting congestion and is able to re-route vehicles appropriately, performing a proper load balance of vehicular traffic.

Traffic management systems: A classification, review, challenges, and future perspectives

In cities, where the number of vehicles continuously increases faster than the available traffic infrastructure to support them, congestion is a difficult issue to deal with and it becomes even worse in case of car accidents. This problem affects many aspects of the modern society, including economic development, traffic accidents, increase in greenhouse emissions, time spent, and health damages. In this context, modern societies can rely on traffic management system to minimize traffic congestion and its negative effects. Traffic management systems are composed of a set of application and management tools to improve the overall traffic efficiency and safety of the transportation systems. Furthermore, to overcome such issue, traffic management system gathers information from heterogeneous sources, exploits such information to identify hazards that may potentially degrade the traffic efficiency, and then provides services to control them. With this question in mind, this article presents a classification, review, challenges, and future perspectives to implement a traffic management system.

A Fully-distributed Traffic Management System to Improve the Overall Traffic Efficiency

In recent years, the number of vehicles has increased faster than the available infrastructure. Consequently, traffic congestion has become a daily problem affecting several aspects of modern society, including regional economic development. In this way, Traffic Management System (TMS) have been proposed to improve the traffic efficient and minimize traffic congestion problems. These systems rely on gather traffic-related data in a central entity to identify congestion and suggest alternative routes. However such approach adds load in communication channel depending on the traffic density. In this way, this paper introduces FASTER, a fully-distributed TMS to improve the overall vehicle traffic efficiency that does not overloads the communication channel, providing a suitable distributed solution. Simulation results indicate that our FASTER outperforms the assessed solutions in different scenarios and in different key requirements of TMS.

GARUDA: A New Geographical Accident Aware Solution to Reduce Urban Congestion

In cities where the number of vehicles continuously increases faster than the available infrastructure, traffic congestion is a difficult issue to deal with. This problem becomes even worse in case of accidents that affects many aspects of the modern society, including economic development and CO2 emission. Several solutions for Intelligent Transportation Systems have been proposed to identify congestions and re-route the vehicles afterwards. This work introduces GARUDA, a fully distributed and pro-active intelligent traffic information system, which avoid congestions, calculates new routes, and notifies drivers to follow new paths proactively. Simulation results show the effectiveness of GARUDA. When compared to original vehicular mobility trace, GARUDA reduces the average trip time in approximately 53%, the overall CO 2 emission in 26% and the fuel consumption in 28%.

ADD: A Data Dissemination Solution for Highly Dynamic Highway Environments

Vehicular Ad-Hoc Networks (VANETs) are a specific type of moving networks in which the nodes are vehicles with processing, storage and wireless communication capacity. VANETs face a number of challenges in terms of data dissemination due to the volatile density of vehicles and frequent changes in the network topology induced by the high mobility of the vehicles and of short-range communications. The envisaged applications, as well as some inherent characteristics of the VANETs render the data dissemination an essential service and a challenging task in these networks. Many data dissemination protocols have been proposed in the literature, nevertheless, most of such protocols do not deal simultaneously with the problems of broadcast storm and synchronization problem. To face such problems, we propose a new data dissemination protocol in vehicular networks named ADD, which operates in highly dynamic highway environments. The ADD consists two mechanisms, broadcast suppression and delay desynchronization. ADD uses a preference zone to eliminate the broadcast storm problem and the delay desynchronization to eliminate the synchronization problem caused by 802.11p protocol. When compared with three known solutions SRD, Flooding and AID we show that our proposal for data dissemination executes it with higher efficiency than other protocols, exceeding them in different scenarios in all the undertaken evaluations.

ICARUS: Improvement of traffic Condition through an Alerting and Re-routing System

Abstract In cities, where the number of vehicles continuously increase faster than the available infrastructure to contain them, traffic congestion is a difficult issue to deal with. This problem becomes even worse in case of accidents and affects many aspects of the modern society, including economic development, accidents, CO (Carbon monoxide) emission, trip time, and health. Several solutions for Traffic Management System (TMS) have been proposed to identify congestions and re-route the vehicles afterward. To this end, they exchange messages periodically between vehicles and central server, what can cause an overhead in the communication channel. In this scenario, it is important to identify the source of the problem and inform the drivers of new routes before the congestion takes place with, considering the limitations of vehicular communication. This work introduces ICARUS, a distributed and pro-active Traffic Management System, which receives notifications about a traffic events then it can calculates new routes, and, then, notifies drivers to follow new paths pro-actively by using inter-vehicle communications. Simulation results show the effectiveness of ICARUS in calculating new routes and disseminating them to vehicles approaching a congested area. Hence, ICARUS reduces the travel time, fuel consumption, and CO emissions of vehicles in urban environments when compared to existing approaches. In addition, ICARUS reduces the broadcast storm problem and maximizes the data dissemination capabilities with short delays and low overhead.

A new Solution based on Inter-Vehicle Communication to Reduce Traffic jam in Highway Environment

Traffic congestion is an urban mobility problem, which generates stress to drivers and economic losses. In 2012, greenhouse gas emissions from transportation accounted for about 28% of total U.S. greenhouse gas emissions. Intelligent transportation systems can assist in the identification and reduction of vehicular traffic congestion. In this context, this work proposes an intelligent traffic information system based on inter-vehicle communication to avoid vehicle traffic congestion. The main goal of the proposed solution is to decrease CO2 emissions, the average trip time and fuel consumption by avoiding congested roads. Simulation results show that our proposed solution can reduce the average trip time, and the overall CO2 emission and fuel consumption. In particular, the trip time was decreased approximately 86%, the fuel consumption 40% and the CO2 emission 55%. This shows the potential of the proposed solution.