With city budgets under pressure, municipal expenses are coming under close scrutiny. In many municipalities, fleet operation makes up much of a city’s budget. Take, for example, a large city the size of Winston-Salem, NC: A quarter-million residents require services like police, fire, waste collection, public works, and parks and recreation, all with vehicles that can easily range from 1,500 to 2,000 in their fleets. Public transit buses can add 500 on top of that. All of this equipment creates expense in terms of capital outlay, people power, maintenance, and of course, fuel. (Did you know that the average garbage truck gets about 3mpg?) Minimizing operation waste and eliminating duplicated efforts could produce welcome savings in fuel, maintenance, capital expenditures and staffing budgets.
Enter V2I (Vehicle-to-Infrastructure) communication and data collection systems. While the goal of V2V (Vehicle-to-Vehicle) systems is to improve traffic safety via a mesh network where vehicles exchange information with each other, V2I enables vehicles to communicate with stationary infrastructure components. Information relating to the timing of traffic lights and road signs, or potential hazards ahead, is available to the vehicle. V2I can also provide large amounts of data to be used for future vehicle route optimization. Onboard GPS units containing Antenova or other precision GPS Modules provide position information that can be combined with the many variables of a municipal fleet operation. High-speed communication, relying on state-of-the-art components like Analog Devices’ ADAR7251 16-Bit Simultaneous Sampling ADCs, enable the transmission of large amounts of data between fleet units and a centralized operations center. Municipalities can crunch gathered data through specialized applications that focus on roadway safety, smart route planning, and fuel usage in terms of cost savings and greener transportation.
Figure 2: Vehicle to Infrastructure (V2I) communication.
Though most of the key technology already exists for V2I systems, working examples are limited. The car manufacturer Audi has set up a pilot system in Las Vegas, Nevada that allows cars to communicate with a municipal traffic system to make intelligent predictions about traffic conditions. In Porto, Portugal, Veniam has set up a trial project focused on data management and transmission that includes hardware, software, and cloud components for delivering data and services over a mesh network of connected vehicles. The U.S. Department of Transportation has set up pilot sites in Wyoming, New York City, and Tampa, Florida focused on providing information such as traffic advisories that inform the driver of safety, mobility, or environment-related conditions.
Though the sweet spot for V2I systems may currently be large cities in the 250,000 to 750,000 population range, V2I should be scalable to other municipal applications. It is downward scalable to small cities but dependent on system cost and payback through realized fleet savings. Larger cities need to incorporate management costs involved with larger, more complex systems in their decisions. Scaling to statewide V2I introduces costs associated with the hardware required to cover large amounts of physical land area.
Municipalities account for an appreciable number of vehicles on the road today. Proper management of these fleets can mean lower fuel costs, maintenance, and capital expenditures. Reduced road time and time-of-day optimization increases road safety and decreases highway congestion. Solutions are under study to make municipal fleet transport smarter, safer, and more efficient. To improve fleet management systems, both local and statewide institutions are looking for real-time, dynamic solutions to improve municipal fleet performance, variable costs, and future capital expenditures. Information and communication technologies that enable exchange between vehicles, sensors, and data centers to gather and process information and dynamically manage the fleet are available. Ideally, V2I system development can be accelerated using real-time traffic data already available from GPS logs gathered by private trucking firms and public transit.
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