When You Pay Road Tax

• Road tax shall be payable in advance in respect of every motor vehicle on or before the fifteenth of April each year. The owner of a motor vehicle shall have the option of paying the tax in four quarterly installments payable on or before the fifteenth of April, July, October and January.

• a person fails to pay an installment of tax within fifteenth of April, July, October and January each year, he shall be liable to pay in addition to arrears of taxes, penalty as prescribed.

• In case of default of payment of road taxes, the arrears of taxes will be recoverable as arrears to Land revenue.

Data Extraction

If the selection of crashes for upload to SAFETYNET is done by computer extraction, it is critical that all the necessary elements are present to accurately make the extraction. For crashes involving non-fatal injuries, or vehicle damage, additional data are very important. The selection criteria related to crash severity requires identification that a person was BOTH injured and transported for treatment or that a vehicle was BOTH towed and received disabling damage

Potential Crash Report Problems

Limited space on a form can result in the use of space saving measures such as a “merging” of data elements into a single field. This can result in fields that don’t appropriately record the intended data. One example would be the use of the same field for the officer to record the registered vehicle owner and the responsible carrier. The owner of the vehicle is NOT always the motor carrier. If the officer records the name of the owner and the USDOT of the proper motor carrier, this will produce a mis-match when the case is uploaded in SAFETYNET. Conversely, recording the motor carrier can cause the registered vehicle owner to be lost. Another example would be a lack of sufficient space for the officer to write the entire motor carrier name or address. This promotes abbreviations and partial names to be recorded, making it difficult to resolve any errors.

Carrier Identification

The information on interstate or intrastate carriers is provided to the Federal Motor Carrier Safety Administration which uses the data to target unsafe carriers for more in-depth investigations. A poor safety record can lead to a carrier losing its operating authority. Missing or inaccurate carrier information when reporting on a qualifying crash can allow “unsafe” carriers to escape regulation or cause “safe” carriers to inappropriately have their safety records affected. Consequently, when reporting crashes it is critical to report the correct carrier name, number and address.

NOTE: The companies and carriers shown in the photographs on this site are included for illustrative purposes only. These images in NO WAY indicate or imply unsafe or improper operating practices by those pictured.

Onboard Monitoring to Improve Commercial Motor Vehicle Safety

The overall objective of this program is to determine whether onboard monitoring and feedback can improve C commercial motor vehicle driver performance and safety. This project will (1) define which driver performance aspects should be measured, (2) determine the best means of communicating information to the driver (e.g., real-time or delayed feedback), (3) design and development of a prototype suite, and (4) develop a research methodology for the follow-on FOT.

Enhanced Rear Signaling for Commercial Motor Vehicles

In September, 2005 FMCSA initiated development of a prototype enhanced rear signaling system for use on commercial motor vehicles (CMVs). The system incorporates countermeasures that were developed in Phase I of this project. The system was evaluated by installing it on a test truck and by observing the behavior of drivers in real-world conditions. Based on the analysis of following driver behavior, the system showed that there are possible benefits to this system, or elements of this system, when used on CMVs. FMCSA is now considering conducting a field operational test (FOT) to further explore this system.

The countermeasures identified in Phase I include: (1) LED brake lamps with an ambient light sensor to make the lamps brighter in direct sunlight and more conspicuous in bright ambient light, (2) brake lamps that are activated by engine braking to address the increasing use of jake brakes in CMVs, (3) additional conspicuity markings that create a more accurate perception of the truck position for following drivers, (4) a sensor system that detects and tracks a following vehicle and sounds a focused audio signal and illuminates a traffic clearing lamp when the vehicle is following too closely or approaching at too high a rate of speed.

Phase III of the Enhanced Rear Signaling project will entail lab, simulator, track, and jury tests to ascertain the best configuration and combination of countermeasures to be used in a large scale FOT. In addition, a large scale, 18-month FOT will be designed. The research will entail exploration of most effective photometric characteristics of the enhanced brake lamps, comparison of existing required retro-reflective markings with the octagonal retro-reflective markings developed in Phase I, and lab/simulator and/or track tests of changes in closure rates with the prototype and without.

Phase IV of the Enhanced Rear Signaling project will execute a large-scale field operational test to analyze the benefits of the prototype system developed in Phase II. Its goal will be to determine the effectiveness of the specific components of the system and develop support for any potential rulemaking action that NHTSA may choose to undertake.

Advanced Driver Fatigue Research – GWU earmark

This report summarizes the findings of the Advanced Driver Fatigue Research project conducted by the Center for Intelligent Systems Research (CISR) of the George Washington University, and funded by FMCSA. This goal of this project was to develop an unobtrusive drowsy driver detection system for commercial motor carriers. CISR previously developed an effective drowsiness detection system for automobiles that relied solely on the driver’s steering patterns for input. This project’s evaluation of this system confirms that this approach is equally valid for truck drivers, despite the differences between truck and automobile driving. The drowsy driver detection system exhibited acceptable false positive and false negative readings and an ideal warning rate before crashes.