Roberto Sadao Yokoyama

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.

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%.

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.

Minimizing traffic jams in urban Centers using vehicular ad hoc networks

Traffic jam in urban centers is a mobility problem responsible for significant economic losses and the degradation of the environment. However, a wide range of technologies, in particular, intelligent transportation systems, may be used to predict, identify and reduce vehicular traffic congestion. In this context, this work presents an Intelligent Traffic Information System (ITIS) which relies on inter-vehicle communication in order to avoid traffic jams in urban centers. The main goal of the proposed system is to reduce the average trip time, the fuel consumption and CO2 emissions, thus increasing vehicular traffic efficiency, reducing economic losses and making cities more environmental friendly. Simulation results for a synthetic scenario have shown that our proposed system is able to accomplish this goal. In particular, the average trip time was decreased ≈47%, the fuel consumption ≈22% and the CO2 emission ≈24%.

Secure Connection Re-establishment for Session-Based IP Mobility

The Session-based IP Mobility Support [1] is a general purpose socket-based API designed to create mobility-aware applications that do not break with transmission disruptions or delays. In this paper, we present and discuss the security support provided in order to deal with threats in the phases of closed session opening and suspended session reopening. The performance of these phases were assessed through experiments in a real wireless network and compared with handshake approaches of the most common upper layer protocols, such as TCP, SSL, and SSH. The operation latency results show a good cost-effectiveness of the secure session support, which is an important requirement for handling IP mobility in Vehicular Communication Networks (VCN). Using the developed protocol, the detection of link disruption and the trusted re-establishment of an ongoing connection can be achieved with little overhead.

Performance evaluation of unmanned aerial vehicles in automatic power meter readings

Typically, the electric power companies employ a group of power meter readers to collect data on the customers energy consumption. This task is usually carried out manually, which can lead to high cost and errors, causing financial losses. Some approaches have tried to minimize these problems, using strategies such as discovering the minimal route or relying on vehicles to perform the readings. However, errors in the manual readings can occur and vehicles suffer from congestion and high fuel and maintenance costs. In this work, we go further and propose an architecture to the Automatic Meter Reading (AMR) system using Unmanned Aerial Vehicles (UAV). The main challenge of the solution is to design a robust and lightweight protocol that is capable of dealing with wireless communication collisions. Therefore, the main contribution of this work is the design of a new protocol to ensure wireless communication from UAV to the power meters. We validated and evaluated the architecture in an urban scenario, with results showing a decrease of time and distance when compared to other approaches. We also evaluated the system proposed with Linear Flight Plan, the Ant Colony Optimization and Guided Local Search metaheuristic. Our mechanism attains an improvement of 98% in reducing the message collisions and reducing the energy consumption of the power meters.

Towards the Use of Unmanned Aerial Vehicles for Automatic Power Meter Readings

Most electric power companies employs power meter reader to collect data on the customers energy consumption. Usually, this task is carried out manually, which can lead to high cost and errors, causing financial losses. Some approaches trying to minimize these problems, such as: discover the minimal route or use a car to perform the readings. However, errors associated the manual readings can still occurs and cars suffer with congestions and a high costs of the fuel consumption and to maintaining. In this work, we go further and propose an architecture to Automatic Meter Reading (AMR) system using Unmanned Aerial Vehicles (UAV). The main challenge of the solution is design a robust and lightweight protocol that is able to deal with the wireless communication collisions. Therefore, the main contribution of this work is the design a new protocol to ensure wireless communication from UAV to the power meters. We validated and evaluated the architecture in an urban scenario and the results show a decrease of time and distance respectively when compared to car approach. Our collision mechanism reaches an improved of 98% in reducing the messages collisions.