Abstract

Magnitude of urban population and unplanned development of cities have led to road traffic congestion in major cities and added increasing pressure on overall road transport and road related infrastructure. Nowadays, intelligent transportation systems such as Vehicular Ad Hoc Networks (VANET) are used for distributed road traffic. VANET is a wireless network that gathers complex and randomly generated data related to distributed traffic along with other information such as weather con ditions on real time basis. In this paper, the Author has attempted to implement a system on Event Driven Architecture (EDA) to detect complex but similar levels of traffic congestion which resembles real life traffic situation. The system is designed with the help of a technique called Complex Event Processing (CEP) that treats all messages in the network from corresponding vehicles as an event. The effectiveness of this system can be observed by using different performance metrics. https://journalnx.com/journal-article/20150533 Document type: Conference object

Abstract

Road congestion results in a huge waste of time and productivity for millions of people. A possible way to deal with this problem is to have transportation authorities distribute traffic information to drivers, which, in turn, can decide (or be aided by a navigator) to route around congested areas. Such traffic information can be gathered by relying on static sensors placed at specific road locations (e.g., induction loops and video cameras) or by having single vehicles report their location, speed, and travel time. While the former approach has been widely exploited, the latter has come about only more recently; consequently, its potential is less understood. For this reason, in this paper, we study a realistic test case that allows the evaluation of the effectiveness of such a solution. As part of this process, (a) we designed a system that allows vehicles to crowd-source traffic information in an ad hoc manner, allowing them to dynamically reroute based on individually collected traffic information; (b) we implemented a realistic network-mobility simulator that allowed us to evaluate such a model; and (c) we performed a case study that evaluates whether such a decentralized system can help drivers to minimize trip times, which is the main focus of this paper. This study is based on traffic survey data from Portland, OR, and our results indicate that such navigation systems can indeed greatly improve traffic flow. Finally, to test the feasibility of our approach, we implemented our system and ran some real experiments at UCLA's C-Vet test bed.