Fleet Monitoring With GPS

By using Fleet monitoring with GPS, transportation companies can use the data to implement rewards programs and encourage better driving. Fuel costs are the second largest expense line for transportation companies, and GPS tracking makes it possible to better understand how well vehicles are operated. Fuel efficiency can decrease as a result of poor driving habits, and unauthorized vehicle use can raise costs. GPS tracking alerts management to such unauthorized use, and allows for time-use restrictions and calendar templates.

Vehicle mass data can be used as a feedback parameter for controlling vehicle operations

One challenge in the use of vehicle mass data as a feedback parameter for controlling vehicle operations is the volume of the data. In a typical scenario, vehicle mass data is a function of the distance travelled by vehicles during a specific segment. In addition to the volume of data collected per vehicle, the sampling size of probe data is not always large enough to be representative of a fleet’s entire travel time.

Using the vehicle mass data as a feedback¬†Fleet monitoring with GPS parameter for fleet monitoring with GPS can provide managers with real-time information about the performance of their vehicles and help them resolve problems quickly. For example, fleet vehicles are notorious for being neglected and drivers often change cars every day. GPS tracking can provide managers with a comprehensive picture of their fleet’s operations in real time and inform them of any mechanical issues before they become serious.

Vehicle mass data can be used as an analytical metric to determine how much work a vehicle is performing

Mass data can help identify anomalies that can increase fuel and maintenance costs. The data collected can also show you if certain vehicles are having consistent problems. If a specific vehicle is consistently experiencing problems, you can make changes to improve performance and avoid detours. Mass data can also help you identify maintenance issues, so you can schedule preventative maintenance and avoid costly detours.

In addition to mass data, vehicle mass can be used to make performance assessments and to identify cost efficiencies. NPMRDS data, for example, contains data based on probe readings from across the country. However, these readings contain empty records during five minute reporting intervals. The coverage map allows you to explore the frequency of empty readings and filters by time of day, vehicle type, and more.

Vehicle mass data can be used to determine if a driver has violated a speed limit

The ability to use vehicle mass data to determine if a driver has violater a speed limit is a significant advancement in vehicle safety and security. This technology allows police officers to monitor the speed of drivers in real time. Vehicles emit radio signals that measure their mass. These radio signals are then received by receiver units (RSUs), which encapsulate the messages and transmit them to CSs. The CSs can determine the rated speed limits for the area covered by the RSU. They will have the vehicle’s mass and the allowed speed limits over time, and compare those to the vehicle’s speed and find out if it has violated the speed limit.

Speed limit systems can also track average speed and maximum speed of violators, the number of lanes a vehicle is in at the time of the violation, and the type of vehicle that has violated the limits. They can also know which lane a driver is in and what impact overspeeding has on the vehicles in that lane. In addition to speed limit detection, this technology can be used to adjust speed limits based on the time of day, the type of vehicle and its weight, as well as the driver’s gender and age.

Vehicle mass data can be used to determine if a driver has violated a load histogram

Weight in motion systems, which analyze vehicle mass and velocity, can be used to determine if a vehicle is overloaded. The statistical distribution of total weight depends on the category of vehicles being analyzed. Heavy vehicles are those weighing over 3.5 tons. The results from a statistical analysis of this data show that the weight distribution is non-symmetrical. The gamma or lognormal distribution curves are used to approximate the Rayleigh distribution curve.

This type of data can help a police officer identify drivers who may be driving over the maximum safe load. It can also be used to determine if a driver has violated a load histogram by analyzing the mass of the vehicle. Annotations can be as simple as “taking a break,” or as detailed as a driver chooses.

This entry was posted in Main. Bookmark the permalink.