Drivers are essential factors affecting the efficiency and management level of a carrier. In this thesis, the driver assignment problem is investigated and methods for obtaining lower total operational costs are introduced for small and medium-sized truck freight transportation companies. Three interrelated research topics, including the following, have been systematically studied. Firstly, extending the traditional costing and Activity-Based Costing (ABC) method, the new Time-Driven Activity-Based Costing (TDABC) method, TDABC-FTC, has been introduced for truck freight companies. Detailed implementation process flow has been designed to streamline the easy incorporation of overhead cost. Fuel costs hold about one-third of the total operational costs of truck freight transportation, and drivers’ driving behaviors heavily influence the fuel consumption rate. In this work, the On-Board Diagnostics (OBD) Ⅱ, GPS tracker and Controller Area Network (CAN) bus are used to retrieve related truck operation data and transfer these data to a central database for later processing to obtain driving behavior parameters. An artificial neural network (ANN) model, built using MATLAB toolbox, is introduced to capture the relations between driving behavior and fuel consumption rate. The fuel consumption indicators for different drivers are then developed to reflect their relative fuel consumption rate quantitatively. The driver assignment problem is modeled as an optimization problem for minimizing the total operational cost of the truck, and the NP-hard problem is solved as a mixed integer programming problem. Two solution methods, Branch and Bound, and the Hungarian algorithm, are used to solve the formulated driver assignment problem. The Hungarian algorithm has been modified to address two particular situations in the driver assignment problem. Numerical experiments are conducted to validate the effectiveness of the newly introduced TDABC model, the fuel saving oriented optimal driver assignment method associating driver behavior to truck fuel consumption rate for different transportation tasks, and the solution methods for the special optimization problems formulated in this work. The newly introduced methods were tested using real truck fleet data, showing considerable benefit of the optimal scheduling techniques, and forming the foundation for further research in this area. / Graduate

The problem of this thesis is to determine the degree of relationship existing between laboratory test scores and practical test scores in driver education and training. The tests considered in this study are depth perception, visual acuity, reaction time, and field of vision.

Lighting consumes approximately 20-25% of the energy produced worldwide. LED based lighting is rapidly becoming the preferred choice over incandescent and fluorescent based lighting. LEDs have advantages such as high efficacy, long operating lifetime and excellent lumen maintenance. Therefore, to gain benefits from LEDs for lighting purposes, they must be driven with efficient drivers which maintain high LED efficacy and long LED lifetime. A review of existing LED drivers is done, and their advantages and drawbacks are identified. Existing fault-tolerant drivers are also reviewed. Several dimming methods and their effects on the LED efficacy and lifetime are investigated. As a result, a converter with coupled inductors, suitable as an LED driver which has high efficiency and can maintain high LED efficacy, incorporated with a high efficiency dimming method, is chosen. For the proposed LED driver, a comprehensive analysis on the effects of coupling type and coupling coefficient on converter performance is done. This is carried out to establish the best coupled inductor structure and coupling coefficient, for the proposed LED driver. The coupled inductor obtained is used to achieve high LED efficacy and also used to eliminate the need for an output filtering capacitor. This results in a highly compact, high efficiency and low cost LED driver. A lossless method of LED string current sensing is proposed, so that driver efficiency is not negatively impacted. The LED driver and a digital control system are designed, with the fault-tolerant feature incorporated. The LED driver and the control system are simulated and practically implemented. The results obtained show excellent LED driver performance. The fault-tolerant feature can enable the driver to operate under fault conditions, saving repair costs and down time. Additionally, a novel digitally controlled LED driver, which can drive several independent multiple LED loads, is proposed. This novel driver is simulated and practically implemented; with the results showing excellent driver performance. The novel LED driver can simplify and reduce costs of existing LED lighting systems. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / Unrestricted

No description available.

No description available.

Vehicle automation has garnered increasing attention as a means of improving safety and efficiency. Advanced Driver Assistance Systems (ADAS) have gained popularity in the transport industry. However, establishing an appropriate level of trust in these systems is crucial for their successful implementation. This research explores the factors influencing driver trust calibration in different levels of automation within driver assistance systems for commercial mobility trucks to ensure drivers comprehend the limitations of these systems and uphold road safety. A qualitative approach involved eleven interviews and observations with drivers to explore their perceptions, experiences, and expectations regarding these systems. The study’s findings extend the Hoff and Bashir Trust model to include significant social factors in calibrating trust. These findings offer valuable insights into the various trust factors that impact driver trust calibration at different levels of automation in driver assistance systems for commercial mobility trucks. These insights contribute to academia in that they help understand how trust in automation is formed and calibrated in real-world settings. In the automotive industry, they can guide the design and implementation of these systems to enhance future drivers’ safety and overall experience.

Intersection Advance Driver Assist Systems (I-ADAS) may prevent 25 to 93% of intersection crashes. The effectiveness of I-ADAS will be limited by driver's pre-crash behavior and other environmental factors. This study will characterize real-world intersection traversals to evaluate the effectiveness of I-ADAS while accounting for driver behavior in crash and near-crash scenarios. This study characterized real-world intersection traversals using naturalistic driving datasets: the Second Strategic Highway Research Program (SHRP-2) and the Virginia Traffic Cameras for Advanced Safety Technologies (VT-CAST) 2020. A step-by-step approach was taken to create an algorithm that can identify three different intersection traversal trajectories: straight crossing path (SCP); left turn across path opposite direction (LTAP/OD); and left turn across path lateral direction (LTAP/LD). About 140,000 intersection traversals were characterized and used to train a unique driver behavior model. The median average speed for all encounter types was about 7.2 m/s. The driver behavior model was a Markov Model with a multinomial regression that achieved an average 90.5% accuracy across the three crash modes. The model used over 124,000 total intersection encounters including 301 crash and near-crash scenarios. I-ADAS effectiveness was evaluated with realistic driver behavior in simulations of intersection traversal scenarios based on proposed US New Car Assessment Program I-ADAS test protocols. All near-crashes were avoided. The driver with I-ADAS overall helped avoid more crashes. For SCP and LTAP the collisions avoided increased as the field of view of the sensor increased in I-ADAS only simulations. There were 18% crash scenarios that were not avoided with I-ADAS with driver. Among near-crash scenarios, where NHTSA expects no I-ADAS activation, there were fewer I-ADAS activations (58.5%) due to driver input compared to the I-ADAS only simulations (0%). / Master of Science / Intersection Advance Driver Assist Systems (I-ADAS) may prevent 25-93% of intersection crashes. I-ADAS can assist drivers in preventing or mitigating these crashes using a collision warning system or automatically applying the brakes for the driver. One way I-ADAS may assist in crash prevention is with automatic emergency braking (AEB), which will automatically apply braking without driver input if the vehicle detects that a crash is imminent. The United States New Car Assessment Program (US-NCAP) has also proposed adding I-ADAS with AEB tests into its standard test matrix. The US-NCAP has proposed three different scenarios. All the tests have two crash-imminent configurations where the vehicles are set up to collide if no deceleration occurs and a near-miss configuration where the vehicles are set up to barely miss each other. This study will use intersection traversals from naturalistic driving data in the US to build a driver behavior model. The intersection travels will be characterized by their speed, acceleration, deceleration, and estimated time to collision. The driver behavior model was able to predict the longitudinal and lateral movements for the driver. The proposed US-NCAP test protocols were then simulated with varied sensors parameters where one vehicle was equipped with I-ADAS and a driver. The vehicle with I-ADAS with a driver was more successful than a vehicle only equipped with I-ADAS at preventing a crash.

Current return-to-drive recommendations for patients following rotator cuff repair (RCR) surgery are not uniform due to a lack of empirical evidence relating driving safety and time-after-surgery. To address the limitations of previous work, Badger et al. (2022) evaluated, on public roads, the driving fitness of patients prior to RCR and at multiple post-operative timepoints. The goal of the Badger, et al. study was to make evidence-based return-to-drive recommendations in an environment with higher fidelity than that of a simulator and not subject to biases inherent to surveys. Badger et al., however, do not fully investigate the driving practices exhibited by subjects, overlooking the potential presence of compensatory driver behaviors. Further investigation of these behaviors through observation of direct driving techniques and practices over time can specifically answer how drivers may modify their behaviors to address a perceived state of impairment. Additionally, the degree of success in vehicle operation by comparing an ideal turn to the path taken by the driver allows for a level of quantification of the effectiveness of the compensatory techniques. Moreover, driver trajectories inferred from the vehicle Controller Area Network (CAN) metrics and from global positioning system (GPS) coordinates are contrasted with the ideal turn to assess minimum requirements for future sensors that are used to make these trajectory comparisons. This investigation leverages pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed the same prescribed driving maneuvers and drove the same route in a preoperative state and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral data were annotated to extract key characteristics of interest and related them to relevant vehicle sensor readings. To construct vehicle paths, data was obtained from the on-board data acquisition system (DAS). Behavioral metrics considered the use of ipsilateral vehicle controls, performance of non-primary vehicle tasks, and steering techniques utilized to assess the impact of mobility restrictions due to sling use. Sling use was found to be a significant factor in use of the non-ipsilateral hand associated with the operative extremity (i.e., operative hand) on vehicle functions and, in particular, difficulty with the gear shifting control. Additionally, when considering the performance of non-primary vehicle tasks as assessed through a prescribed visor manipulation, sling use was not a significant factor for the task duration or completion of the task in a fluid motion. Sling use was, however, significant with respect to operative hand position prior to the completion of the visor manipulation: the operative hand was often not on the steering wheel prior to the visor maneuver. In addition, the operative hand was never used to manipulate the visor when the sling was worn. One-handed steering was also more frequent with the presence of the sling. Further behavioral analysis assessed the presence of compensatory behavior exhibited by subjects during periods in which impairment was perceived. Perceived impairment was observed as a function of the different experimental timepoints. Findings indicated a significant decrease in the lateral vehicle jerk during post-operative weeks 6 and 12. Significant differences, however, were not observed in body position alteration to avoid contact with the interior vehicle cabin, in over-the-shoulder checks, and in forward leans during yield and merge maneuvers. Regarding trajectory analysis, sling use did not produce a significant difference in the error metrics between the actual and ideal paths. In completion of turning maneuvers, however, operative extremity was significant for left turns, with greater error against the ideal path observed from those in the left operative cohort compared to those in the right operative cohort. For the right turn, however, operative extremity was not found to be a significant factor. In addition, the GPS data accuracy proved insufficient to support comparison against the ideal path. Overall, findings from this study provide metrics beyond those used in Badger, et al. that can be used in answering when it is safe for rotator cuff repair patients to return-to-drive. With the limited differences observed as a function of study timepoint and sling use, it is recommended that patients are able to safely return-to-drive at two weeks post-operation. If anything, results suggest that overcompensation, as inferred from observation of safer driving behaviors than normal, is present during some experimental timepoints, particularly post-operative week 2. / Master of Science / Current recommendations based on when it is safe for rotator cuff repair patients to return-to-drive are not standard because of a lack of suitable evidence. Previous work and recommendations rely on surveys and simulators which do not create fully realistic conditions and are subject to biases. To address the limitations of previous work, Badger et. al (2022) studied actual rotator cuff repair patients on public roads prior and following operation at multiple timepoints. Badger et al., however, did not consider the potential adaptations in driver behavior due to mobility restrictions and the perception of inferiority due to injury. Additionally, the degree of success of the adaptive driving behaviors based on the error between the actual vehicle path taken and a defined ideal path have not been explored in conjunction with the injury. This investigation is based on the pre-existing data collected by the Virginia Tech Transportation Institute (VTTI) and Carilion Clinic as used in the analysis performed by Badger et al. (2022). RCR patients (n=27) executed identical driving maneuvers and drove the same route before operation and at 2-, 4-, 6-, and 12-weeks post operation. Behavioral observations were recorded and related to relevant vehicle sensor readings. To construct vehicle paths, data was taken from the on-board data acquisition system (DAS). Participants adopted different behaviors, such as using the right hand to use the turn signal when the left arm was in a sling and the left hand to operate the gear shifter when the right arm was on a sling, to assist in combating mobility restrictions. One-handed steering was also more prominent during periods of sling-use. Sling-use, however, did not produce a significant difference in error between the actual vehicle path taken and the ideal path available to the driver. For left-operated participants completing left turns, there was also greater error in comparison to the ideal path than for the group of right-operated patients. However, there was not a difference between left- and right-operated arm participant error in completion of a right turn. The GPS data did not provide a suitable approximation of vehicle trajectory. Overall, findings from this study help to answer when it is safe for rotator cuff repair patients to return-to-drive through evaluation of the effectiveness of compensatory behaviors adopted by participants. With no significant difference in turn execution based on sling use, results suggest that patients can safely return-to-drive at two weeks post-operation. In fact, results suggest that overcompensation towards safer behaviors is present during some experimental timepoints, particularly post-operative week 2.

No description available.

This study was undertaken to simulator test and evaluate a complete drowsy driver detection system. The goal of the study was to recommend optimal specifications for a system to be further studied in an actual vehicle. The system used a set of algorithms developed from previously collected data and a set of previously optimized advisory tones, advisory messages, alarm stimuli, and drowsiness countermeasures. Detection occurred if eye closure or lane excursion exceeded predetermined thresholds. Data were obtained from six sleep-deprived subjects who drove a motion base automobile simulator late at night. Each subject was trained in carefully observing lane boundaries, using a device which sounded an alarm if lane boundaries were exceeded. The performance aspect of the system dominated the detection process. None of the algorithms tracked well with the measures they were designed to estimate; correlations were much lower than expected. The algorithms relied heavily on the positioning of the vehicle relative to the lane. / Master of Science