• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.16-24
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• 2013

Some GM (General Motors) vehicles are using a GMLAN (General Motors Local Area Network) communication protocol for control and diagnostics. The airbag control module uses vehicle speed information from the GMLAN to record the vehicle speed as pre-crash information. In order to use the vehicle speed information for crash reconstruction purposes, it helps to be able to understand the accuracy of the data. The actual vehicle speed is not expected to be the same as the GMLAN indicated speed in some situations like a spin or if there is hard braking. This paper compares the actual vehicle speed and vehicle speed information during specific vehicle maneuvers. Actual vehicle speed is calculated from a GPS sensor, while GMLAN vehicle speed is calculated from transmission output sensor by the Engine control module (ECM). Vehicle maneuvers defined as Mode #1, Mode #2, Mode #3. The Mode #1 maneuver simulates wheel lock-up and skidding f by hard-braking at a specific speed. The Mode #2 maneuver simulates a 90degree turn using a J-turn maneuver at a specific speed. The Mode#3 maneuver simulates a 180 degree turn using a spin type of maneuver at a specific speed. The study then compares the GMLAN speed and GPS speed to see what speed difference exists between them. The results of this paper are applicable to GM vehicles only. This paper catalogs the performance and limitations of two vehicles as useful reference for crash reconstructions where there is a need to understand the speed indicated in the pre-crash section of the SDM data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.187-192
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• 2003

of the road would be a key index judged for a safety at the vehicle driving on the road. In Korea, as seen through a lot of documents, the vehicle driving speed is much faster compared with the design speed. The vehicle driving speed is an important element to get to know the vehicle driving characteristics. However, it is not easy to obtain the vehicle driving speed relating to vehicles' consecutive movements just merely through the presently used methods of vehicle driving speed. In consequence, this study has conducted photographing vehicle movements by use of digital moving images. Based on digital moving Images pictured, we have obtained a certain time interval frame and extracted out vehicles' coordinates and calculated vehicle speed from the firstly rectified image and the secondly rectified image. We could obtain comparatively exact results in the calculation of vehicle driving speed as errors of about 4%, as a result of comparison and verification of vehicle speed calculated from the digital moving images and the speed obtained from DGPS.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.359-365
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• 2005

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, 'When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.' The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness of estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a $6\%$ worst-case error during a hard braking maneuver lasting a few seconds.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.51-58
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• 2002

Vehicle dynamics control systems are. complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed is good results in normal conditions. But the estimation error in severe braking is discontented. In this paper, we estimate the absolute vehicle speed by using the wheel speed data from standard 50-tooth anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used. Ten algorithms are verified experimentally to estimate the absolute vehicle speed and one of those is perfectly shown to estimate the vehicle speed with a 4% error during a braking maneuver.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.82-91
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• 2011

In this paper, a planar model for mechanics of a vehicle/pedestrian collision incorporating road gradient is derived to evaluate the pre-collision speed of vehicle. It takes into account a few physical variables and parameters of popular wrap and forward projection collisions, which include horizontal distance traveled between primary and secondary impacts with the vehicle, launch angle, center-of-gravity height at launch, distance from launch to rest, pedestrian-ground drag factor, the pre-collision vehicle speed and road gradient. The model including road gradient is derived analytically for reconstruction of pedestrian collision accidents, and evaluates the vehicle speed from the pedestrian throw distance. The model coefficients have physical interpretations and are determined through direct calculation. This work shows that the road gradient has a significant effect on the evaluation of the vehicle speed and must be considered in accident cases with inclined road. In additions, foreign/domestic empirical cases and multibody dynamic simulation results are used to construct a least-squares fitted model that has the same structure of the analytical one that provides an estimate of the vehicle speed based on the pedestrian throw distance and the band within which the vehicle speed would be expected to be in 95% of cases.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.856-864
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• 2008

This paper describes a vehicle low speed driving assistant (VLDA) system that is composed of laser scanner. This vehicle is designed for following lead vehicle (LV) without driver's operation. The system is made up several component systems that are based on unmanned ground vehicle (UGV). Each component system is applied to use advanced safety vehicle developed to complete UGV system. VLDA system was divided into vehicle control system and obstacle detecting system. The obstacle detecting system calculate distance and angle of LV and transmit these data to vehicle control system using front, left and right laser scanners. Vehicle control system makes vehicle control values such as steering angle, acceleration and brake position and control vehicle's movement with steering, acceleration and brake actuators. In this research, we designed VLDA system like as low speed cruise control system and test it on real road environments.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.58-65
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• 2003

Vehicle acceleration data from an accelerometer and wheel speed data from standard, 50-tooth antilock braking system wheel speed sensors are used to estimate the absolute longitudinal speed of a vehicle. We develop the four velocity estimation algorithms. And we compare experimental results with the Butterworth filtered speed from the fifth wheel and find that it is possible to estimate absolute longitudinal vehicle speed during a hard braking maneuver lasting three seconds.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.881-887
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• 2015

The hardware-in-the-loop simulation (HILS) of a railway vehicle is crucial for overcoming the limitation of field tests of a railway vehicle. A brake HILS system for a railway vehicle was previously not able to test the performance of a speed-sensing system of a railway vehicle, since wheelset speeds were generated only by computer simulations. In this paper, we present a novel wheelset speed implementation of a brake HILS system for a railway vehicle. Four wheelset speeds of a brake HILS system for a car of a railway vehicle are implemented using four small-sized servomotors, whereas the speed sensors and pole wheels used in the brake HILS system are the actual ones of the railway vehicle. According to the simulated speeds of four wheelsets in the dynamic equations of motion, four servomotors generate wheel speeds in real time, and then the measured wheelset speeds are fed back to the computer simulation model. Moreover, in this paper, we improve the performance of wheelset speed measurement via the T method instead of the M method presently used in the field. The performances of wheelset speed implementation and speed-sensor operation are demonstrated by experimental works using a HILS system.

• Journal of ILASS-Korea
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• v.28 no.4
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• pp.184-190
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• 2023

The European Union has instituted a new emission standard protocol that necessitates real-time measurements from vehicles on actual roads. The adequate development of routes for real driving emissions (RDE) mandates substantial resources, encompassing both vehicles and a portable emission measurement system (PEMS). In this study, a simulation tool was utilized to predict the vehicle speed traversing the routes developed for the RDE measurements. Initially, the vehicle powertrain system was modeled for both a gasoline hybrid vehicle and a gasoline engine-only vehicle. Subsequently, the speed profile for the specified vehicle was constructed based on the RDE route developed for the EURO-6 standard. Finally, the predicted vehicle speed profiles for highway and urban routes were assessed utilizing the actual driving data. The driving model predicted more consistency in the vehicle speed at each driving section. Meanwhile, the human driver tended to accelerate further, and then decelerate in each section, instead of cruising at a predicted section speed.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.179-186
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• 2002

The absolute longitudinal speed of a vehicle is estimated by using vehicle acceleration data from an accelerometer and wheel speed data from standard 50-tooth antiknock braking system wheel speed sensors. An intuitive solution to this problem is, "When wheel slip is low, calculate absolute velocities from the wheel speeds; when wheel slip is high, calculate absolute velocity by integrating the accelerometer." Fuzzy logic is introduced to implement the above idea and a new algorithm of "modified velocities with step integration" is proposed. This algorithm is verified experimentally to estimate speed of a vehicle, and is also shown to estimate absolute longitudinal vehicle speed with a 6% worst-case error during a hard braking maneuver lasting three seconds.