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NSERC DIVA - Developing Next Generation Intelligent Vehicular Networks and Applications

The DIVA network is hosted at the University of Ottawa. It focusses on intelligent vehicular networks and their applications. DIVA targets the design and development of network protocols and applications for vehicular ad hoc and sensor networks (VANets) that allow high-speed communication among vehicles and ground-based infrastructure, and increase driving comfort.

DIVA will provide the foundation and architecture design for deploying large-scale intelligent vehicular network services and applications; and it will provide interested agencies with efficient tools to understand congestion by developing a standardized communication infrastructure and integrated intelligent transportation system to measure congestion and its multiple effects. Furthermore, by understanding congestion, novel intelligent transportation systems will be developed to improve the Canadian transportation system and, as a result, the quality of life for drivers and passengers.

Challenge

In a 2006 study conducted by Transport Canada, the congestion in urban areas was estimated to cost Canadians between $2.3 billion and $3.7 billion per year. Ninety percent of the cost is associated with time lost in traffic; seven percent occurs because of fuel consumed; and three percent is from increased greenhouse gas emissions. This statistical estimation does not include costs related to congestion caused by bad weather, accidents, stalled vehicles and other incidents.

The vision shared by the network participants across Canada is to see developed and deployed distributed, robust, secure and fault-tolerant communication solutions. These will enable the proliferation of intelligent vehicular network systems to reduce roadway fatalities, fossil-fuel consumption, greenhouse gas emissions and traffic congestions, while providing drivers and passengers with driving comfort applications (such as location-aware services, multimedia streaming, local news, tourist information and alert messages on highways and city streets).

Network Structure

DIVA consists of five interdisciplinary research themes that integrate a team of 20 researchers from across Canada, along with a large number of graduate students on the various project teams. DIVA brings together Canadian experts from the fields of vehicular networks, mobile ad hoc networks, distributed and mobile systems, wireless sensor networks, data mining, spatio-temporal data management, network security and privacy, service oriented architectures, and heterogeneous wireless networks.

DIVA is organized into five main themes:

  1. Integration of Heterogeneous Vehicular Networks;
  2. Intelligent Vehicular Ad Hoc and Sensor Networks;
  3. Multimedia delivery over VANets;
  4. Security and Privacy in Vehicular Networks; and
  5. Infrastructures and Applications for Vehicular Communications.

Research Objectives

The main objectives of the DIVA network are to 1) integrate heterogeneous vehicular networks within a mobile vehicular environment; and 2) develop practical implementations of distributed intelligent transportation systems and associated applications. In order to achieve these objectives, the activities performed in this network are undertaken by experts in several fields and carried out in conjunction with industrial partners, each of which constitute a potential opportunity for technology and knowledge transfer and offering potential employment to graduating students in the program.

The intelligent transportation systems (ITS) plan for Canada, as set out by Transport Canada in An Intelligent Transportation Systems Plan for Canada: en Route to Intelligent Mobility (1999), has clearly identified several applications (e.g., public safety, congestion control) designed to foster the further development of Canada's transportation systems. In the DIVA network, infrastructure-to-vehicle and vehicle-to-vehicle and related services will be investigated. Infrastructure-to-vehicle applications include arterial management (e.g., adaptive signal control, accident avoidance warnings, audio warnings, parking lot controls, speed limits, lane management, and flexible traffic signal control). Vehicle-to-vehicle-based applications to be investigated by DIVA researchers, and its public and industrial partners, include collision avoidance, collision notification and driver assistance (e.g., intelligent navigation, adaptive cruise control and speed limit, and precision parking).

Outcomes

The expected outcomes of this network research are:

  • a solid understanding of next generation intelligent vehicular network service and application requirements in a heterogeneous wireless environment;
  • the design of an integrated framework for heterogeneous vehicular ad hoc and sensor networks;
  • a robust and secure infrastructure; and
  • a suite of efficient vehicular communication protocols and testbeds to foster Canadian research in large-scale vehicular networks for ITS-based applications.

The proposed technologies for intelligent vehicular networks will enable the development and testing of innovative products and services in order to reduce congestion, improve mobility over current practices, and enhance safety for drivers and passengers.

Contacts

Azzedine Boukerche
Network Scientific Director and Principal Investigator
Tel.: 613-562-5800, Ext. 6712
E-mail: boukerch@site.uottawa.ca

Richard W. Pazzi
Network Manager
Tel.: 613-562-5800, Ext. 2650
E-mail: rwerner@site.uottawa.ca


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