Intelligent Transportation Systems

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Intelligent Transportation Systems (ITS) use a broad range of wireless communication systems integrated into on-board computers in vehicles to monitor and control them. This technology is used to eliminate the unpredictability of humans. This system would allow for all the cars on the road to be in continuous communication and to have real-time data on their current locations. Different methods have been created and tested that will someday make ITS common around the world.


Partial Planning

The Partial Planning approach combines techniques that require both computers and the driver to stay alert and take control of the vehicle. Partial Planning uses algorithms integrated into the Co-Pilot electronic framework of the vehicle’s computer system. Using single or multiple processors, the components run on separate processes with shared memory[1]. Sensors in the car and laser scanners in the bumper let the vehicle gather information from the surrounding environment such as lanes and obstacles. Information is used to create a model of the vehicle state and the obstacles in the path. The Co-Pilot module is intended to highly support the driver with recommendations of maneuvers to take.

Magnetic Signal

Magnetic detection is a reliable method of gathering data not usually affected by weather conditions and detectable through foliage and debris. Unlike detection methods based on video imaging and sensors, magnetic signals do not require a direct “line of sight.” Vehicles can be classified by measuring and processing signals based on a single micro-electro-mechanical system (MEMS). The magnetic field disturbance is concentrated mostly at the locations near the engines and wheels, but the spread of ferrous materials throughout the vehicle also works. The different shapes and sizes of the cars will disturb the Earth’s magnetic field in different ways, giving each vehicle model an identifiable magnetic signature. The polarity of the magnetic signal can identify if the vehicle is moving forward or backwards[2]. The computers can take this information to determine the gap necessary between vehicles[3].

Adaptive Cruise Control

Adaptive Cruise Control (ACC) is installed in vehicles to monitor speed and distances when driving in different scenarios, like when a car is traveling alone or when there is another car detected[4]. When a car is detected, the ACC will adjust the speed to follow while remaining at a safe distance. ACC can cause some discomfort to passengers due to the acceleration and jerk.

Global Positioning System

Global Positioning System (GPS) is a navigation system made up of a network of 24 satellites in orbit above Earth placed by the United States Department of Defense (US DoD). Originally intended for military use, it is now available for use by civilians. GPS works in any weather conditions, anywhere in the world, 24 hours a day[5]. By integrating a computer into the car (CarPC) with a GPS and wireless communication, an intelligent route-guide system can be created. The GPS will find the car’s location and relay this information to the CarPC. The computer will use wireless communications to notify other cars of its location in real time. Directions, speeds, and location can all be shared between groups of cars[6].


On American highways, more than 40,000 people are killed each year, while roadway infrastructure is deteriorating faster than it can be maintained[7]. To make ITS safer, cars can be traveling in platoons, a series of vehicles moving in one group in the same direction with one car leading and the rest following. To ensure safety, the distance between each car in the platoon must be monitored and maintained. This inter-distance is proportional to the speed of the vehicle, and so CarPC must be able to compute the necessary calculations. Different platoons must remain 30 to 60 meters apart, while the inter-distance changes from one to three meters. The CarPC also must know what to do in the case of vehicle malfunction. To do this, causes of vehicle failures are categorized by severity with the appropriate maneuver for each.

Environmental Benefits

President Barack Obama expressed concern and interest in the reduction of greenhouse gases in the United States. By 2020, the national goal was to reduce greenhouse gas production to below the levels of the 1990s. By 2050, the country needs to reduce production to 80% below the 1990 levels. 45% of the world's vehicular CO2 production is from the United States, and this also accounts for one-third of the U.S. total CO2 emission . To dramatically improve America's energy security, a system to automate control of the vehicles while on highways, reducing congestion, improving safety, and freeing the driver's time must be created[7].
This is where the on-board computer for the smart highways is beneficial. The computer is able to tell what the optimal driving speed is for the vehicle and maintain the speed for extended periods of time, like a mandatory cruise control. To reduce the total driving mileage, the computer would have the ability to eliminate traffic all-together. To maximize the energy savings, a healthy balance between these two ideas would have to be maintained. In traffic, an increase in speed by only half a mph could save fuel consumption by almost 3%. By eliminating the inner city traffic with intelligent driving, the speed increase would decrease fuel consumption even more. On highways, the computer has the ability to control the lane changes and gaps between cars, which would eliminate the rush hour traffic[3].


  1. Resende, P.; Nashashibi, F.; , "Real-time dynamic trajectory planning for highly automated driving in highways," Intelligent Transportation Systems (ITSC), 2010 13th International IEEE Conference on , vol., no., pp.653-658, 19-22 Sept. 2010
  2. Lan, JH; Xiang, Y.; Wang, LP,; Shi, YQ.;, “Vehicle detection and classification by measuring and processing magnetic signal,” Measurement, vol. 44, no. 1, pp.174-180, Jan. 2011
  3. 3.0 3.1 Tsugawa, S.; Kato, S.; , "Energy ITS: another application of vehicular communications," Communications Magazine, IEEE , vol.48, no.11, pp.120-126, November 2010
  4. Luo, L.; Liu, H.; Li, P.; Wang, H.;, "Model predictive control for adaptive cruise control with multi-objectives: comfort, fuel-economy, safety and car-following," Journal of the Zhejiang University, vol. 11, no. 3, pp. 191-201, December 2009
  5. (n.d.). What is GPS [online]. Available:
  6. Pin-Yung Chen; Ya-Wen Shih; Shih-Hung Chang; Yi-Hsuan Hung; , "An intelligent on-line route guide system in a fleet," Intelligent Transportation Systems (ITSC), 2010 13th International IEEE Conference on , vol., no., pp.291-294, 19-22 Sept. 2010
  7. 7.0 7.1 Heaslip, K.; Muhs, J.; Womack, K.;, "Automated Electric Transportation: A Way to Meet America's Critical Issues," Leadership and Management in Engineering, vol. 11, no., pp.23-28, December 2010