Adaptive Regenerative Braking in Electric Vehicles

Elektrofahrzeuge fahren lokal emissionsfrei und tragen damit dazu bei, die Emissionen in Städten zu reduzieren. Zusätzlich, zeichnen sich Elektrofahrzeuge durch ein dynamisches Fahrverhalten aus. Nachteilig wirkt sich bei den meisten Elektrofahrzeugen, die geringe Reichweite auf die Akzeptanz bei Neuwagenkäufern aus. Eine der Maßnahmen zur Erhöhung der Reichweite von Elektrofahrzeuge ist das regenerative Bremsen. Hierbei wird die kinetische Energie des Fahrzeugs durch generatorisches Bremsen als elektrische Energie zurückgewonnen. Diese zurückgewonnene Energie erhöht die Reichweite des Autos. In dieser Dissertation, wird ein adaptives regeneratives Bremssystem vorgestellt. Dieses System wählt abhängig vom Fahrertyp und der aktuellen Verkehrssituation ein geeignetes regeneratives Bremsniveau aus. Um ein solches System zu realisieren, wurden Verfahren entwickelt, welche einerseits den Fahrertyp und andererseits die Fahrerintention durch Analyse des Fahrbetriebs ermitteln. Dazu wurde u.a. ein mehrdimensionales verstecktes Markov-Modell (MDHMM) entwickelt. Bei Verwendung des Fahrertyps und der Intention des Fahrers, kann so eine geeignete Bremsstufe ausgewählt werden, die die physikalische Begrenzung der Fahrzeugkomponenten berücksichtigt. Durch den Einsatz des entwickelten Systems, kann gezeigt werden, dass eine Erhöhung der Reichweite erreicht werden kann, ohne den Komfort des Fahrers zu beeinträchtigen

Effectiveness of an Emergency Vehicle Operations Course Component, Visual and Perceptual Skills: Analyzing Student Response to Searching, Identifying, Predicting, Deciding, and Executing Skills

As funding for driver education declines according to the National Highway Safety Administration (NHSA) 2013 Traffic Safety Facts, there were 2,345,719 people injured or killed as a result of vehicle crashes. NHTSA reported that there were a total of 118 people killed in 2013 from accidents involving emergency vehicles. The effectiveness of an Emergency Vehicle Operations Course component of visual and perceptual skills can be measured by administering the Driver Performance Test prior to and after student participation. This study examined the population of the students who participated in the TRS 235: Emergency Vehicle Operations Course at Eastern Kentucky University (EKU) in a traditional classroom and online delivery formats. This study determined the potential for a participant to be involved in a crash prior to and after completing TRS 235, as well as the effect the course had on the participants’ visual and perceptual skills. The results of this study indicated that the online and traditional course delivery formats pre and post-test total scores increased significantly. This study also determined that there was a significant difference between the efficacy of online and traditional delivery with online participants scoring higher than the traditional participants. It is important to note that this study does not examine the actual physical performance of the participants’ driving skills or behavior

Simulation of AEB system testing

Tato diplomová práce popisuje simulační nástroj, který byl vytvořen pro analýzu funkcí ADAS systémů a dynamiky vozidel. Nástroj byl vytvořen v aplikacích CarMaker a Microsoft Excel. Software lze použít jako SIL test pro analýzu výstupních dat senzoru před provedením fyzických zkoušek.This master thesis describes a simulation tool which was created to analyze ADAS functions and vehicle dynamics. The tool was created in CarMaker and Microsoft Excel. The software can be used as SIL testing to analyze sensor output data before proving ground test

Understanding the Automotive Pedal Usage and Foot Movement Characteristics of Older Drivers

The purpose of this study was to understand the pedal usage characteristics of older drivers in various driving tasks using an instrumented vehicle. This study stemmed from the prevalence of the pedal application errors (PAEs) and the older drivers’overrepresentation in crashes caused by PAEs. With the population increasing and becoming older, it is estimated that in 2020 there will be 40 million drivers over the age of 65 in the United States. Compared with their younger counterparts, older drivers are facing declining cognitive and physical abilities, such as impaired vision, slower reaction time and diminishing range of limb motion. Because these abilities are closely associated both with the driving task and the ability to recover from a crash, older drivers are overrepresented in vehicle crash involvement rate, and they are especially vulnerable to injuries caused by the crashes. Pedal misapplication crash is a type of crash preceded by a driver mistakenly pressing the accelerator pedal. Recently, the National Highway Traffic Safety Administration issued a report on PAE. The report reveals that older drivers are overrepresented in pedal misapplication crashes and that several driving tasks are overrepresented, such as emergency stopping, parking lot maneuvers and reaching out of the vehicle to interact with a curb-side device such as a card reader, mailbox, or ATM. Existing research has investigated the PAEs from different perspectives, but questions remain as to why older drivers are more likely to commit PAEs in these driving tasks. The current study investigated the pedal usage characteristics of 26 older drivers in driving tasks, such as startle-braking, forward parking and reaching out from the vehicle, which are scenarios associated with higher risk of PAEs. Ten stopping tasks were also investigated as baseline tasks. The study was conducted on-road using an instrumented vehicle. The data collected by the instrumented vehicle included pedal travel (potentiometer), force applied on the pedals (Tekscan sensor), and video recordings of each driver’s upper body and his or her foot movement. The study findings include the following: a) There are significantly positive correlations between a driver’s stature and the percent of foot pivoting, as well as between the shoe length and the percent of foot pivoting, which means the taller the driver or the longer the driver’s shoe, the more likely the driver will use foot pivoting instead of foot lifting in the baseline stopping tasks; b) In the startle-braking task, the driver is more likely to use foot lifting than that in the baseline tasks; c) The foot movement strategy is not found to affect lateral foot placement in either the baseline stopping tasks or the startle-braking task; d) When reaching out of the driver’s window to swipe a card at a card reader, the lateral foot placement on the brake pedal will bias rightward, compared with the lateral foot placement prior to reaching out; e) Approaching a gated access or parking in a dark, relatively confined parking space does not significantly slow down a driver’ foot transfer from the accelerator pedal to the brake pedal; f) Stature of a driver does not significantly affect the time required to successfully complete a card-swiping task. A driver’s pedal operation characteristics are associated with many factors, among which four factors are identified to be relevant to the driver’s pedal operation: stature, shoe length, startle stimuli and reaching out of the driver’s window. To identify the direct causes of PAEs, future research should investigate the pedal operation characteristics in a more controlled environment. For example, an eye-tracking device can be used to study the relationship between gaze direction and foot movement. Other driving scenarios, such as reversing, should be studied as well. In addition, a study with a larger sample size and novice drivers is necessary to validate the findings of the current study and to understand the PAEs among the population with little driving experience. The current study has both clinical and engineering implications. For occupational therapists and driving rehabilitation specialists, factors such as stature, leg length, footwear, vehicle type and pedal configuration may provide information about driver’s foot behaviors. For example, drivers with flat-soled shoes may tend to use foot lifting and drivers with wedged shoes may tend to use foot pivoting. Drivers with very wide shoes may get the shoe caught under the brake pedal when pivoting from the accelerator pedal to the brake pedal. Drivers with short leg length may be able to use foot pivoting when driving a sports vehicle, but they would have to use foot lifting when driving a large truck. Drivers tend to use foot lifting when the pedals are higher above from the vehicle floor and drivers tend to use foot pivoting when the pedals are lower above the vehicle floor. An in-clinic test of a driver’s lower extremity functions prior to on-road assessment helps to select the appropriate test vehicles. For example, it is recommended that shorter drivers with weaker lower extremity functions use vehicles of which the pedals are lower above the vehicle floor. To reduce the chance of a driver’s foot slipping off the brake pedal, engineers should consider redesigning the pedal pad to increase the friction coefficient of shoe-pedal contact. For example, using tread width of 2mm produces higher friction values. In addition, Automatic Vehicle Identification can be implemented so that the drivers do not have to reach out of the window to swipe card and to enter a gated access. Other driver assistance systems such as Autonomous Emergency Braking and Automated Parking System can either mitigate the damage or eliminate the chance of a human error

Power loss minimization in electric cars by wheel force allocation

The need for lowering the emission levels has never been greater than now. In the vehicle industry, electrification seems to be an irreversible way ahead but user-related challenges such as limited range delay electricity as the primary energy source for personal transportation. Other control-related challenges are also introduced as electric cars are over-actuated, i.e. several actuators can be used for the same purpose. Over-actuation introduces the possibility to choose more freely which actuator to use when. Can this freedom of choice be used to improve energy efficiency of electric cars by e.g. minimizing power losses? In this thesis, two wheel force distribution algorithms have been developed with a method called control allocation. The algorithms minimize power losses in the electric drivetrain, transmission and tires. They were tested in a simulated city cycle in a Volvo V60 configuration with four electric motors, each connected to a wheel through a single speed transmission and coupling respectively. It was found that by using developed algorithms, up to 3.9% energy could be saved. In a next step, the transmission ratio on the front motors and rear motors were optimized in combination with one of the algorithms. By using a larger transmission ratio in the front than in the rear, the energy consumption reduced even further. With these development steps, up to 7.9% energy could be saved compared to the original vehicle

A Review of Near-Collision Driver Behavior Models

Objective: This article provides a review of recent models of driver behavior in on-road collision situations. Background: In efforts to improve traffic safety, computer simulation of accident situations holds promise as a valuable tool, for both academia and industry. However, to ensure the validity of simulations, models are needed that accurately capture near-crash driver behavior, as observed in real traffic or driving experiments.<p> Method: Scientific articles were identified by a systematic approach, including extensive database searches. Criteria for inclusion were defined and applied, including the requirement that models should have been previously applied to simulate on-road collision avoidance behavior. Several selected models were implemented and tested in selected scenarios.<p> Results: The reviewed articles were grouped according to a rough taxonomy based on main emphasis, namely avoidance by braking, avoidance by steering, avoidance by a combination of braking and steering, effects of driver states and characteristics on avoidance, and simulation platforms.<p> Conclusion: A large number of near-collision driver behavior models have been proposed. Validation using human driving data has often been limited, but exceptions exist. The research field appears fragmented, but simulation-based comparison indicates that there may be more similarity between models than what is apparent from the model equations. Further comparison of models is recommended.<p> Application: This review provides traffic safety researchers with an overview of the field of driver models for collision situations. Specifically, researchers aiming to develop simulations of on-road collision accident situations can use this review to find suitable starting points for their work

Modeling drivers’ naturalistic driving behavior on rural two-lane curves

This dissertation examined drivers’ naturalistic driving behavior on rural two-lane curves using the Strategic Highway Research Program 2 Naturalistic Driving Study data. It is a state-of-the-art naturalistic driving study that collected more than 3,000 drivers’ daily driving behavior over two years in the U.S. The major data sources were vehicle network, lane tracking system, front and rear radar, driver demographics, driver surveys, vehicle characteristics, and video cameras. This dissertation has three objectives: 1) examine the contributing factors to crashes and near-crashes on rural two-lane curves; 2) understand drivers’ normal driving behavior on rural two lane curves; 3) evaluate how drivers continuously interact with curve geometries using functional data analysis. The first study analyzed the crashes and near-crashes on rural two-lane curves using logistic regression model. The model was used to predict the binary event outcomes using a number of explanatory variables, including driver behavior variables, curve characteristics, and traffic environments. The odds ratio of getting involved in safety critical events was calculated for each contributing factor. Furthermore, the second study focused on the analysis of drivers’ normal curve negotiation behavior on rural two-lane curves. Significant relationships were found between curve radius, lateral acceleration, and vehicle speeds. A linear mixed model was used to predict mean speeds based on curve geometry and driver factors. The third analysis applied functional data analysis method to analyze the time series speed data on four example curves. Functional data analysis was found to be a useful method to analyze the time series observations and understand driver’s behavior from naturalistic driving study. Overall, this dissertation is one of the first studies to investigate drivers’ curve negotiation behavior using naturalistic driving study data, and greatly enhanced our understanding about the role of driver behavior in curve negotiation process. This dissertation had many important implications for curve geometry design, policy making, and advanced vehicle safety system. This dissertation also discussed the opportunities and challenges of analyzing the Strategic Highway Research Program 2 Naturalistic Driving Study data, and the implications for future research

Quality Of Service Measures At Signalized Intersections

The concept of using qualitative measures to describe the quality of service at signalized intersections provided by different designs and controls has been discussed in numerous conferences. Such measures may include driver\u27s comfort, convenience, anxiety, and preferences. The primary objective of this study was to demonstrate the feasibility of using the University of Central Florida\u27s interactive driving simulator to execute several scenarios involving different unusual design and operation practices to measure the quality of service at a signalized intersection. This thesis describes the scenarios, the experiments conducted, the data collected, and analysis of results. Signalized intersections with 3 types of characteristic features were identified for this study. They included 1. A lane dropping on the downstream side of the intersection 2. Misalignment of traffic lanes between the approach and downstream side 3. Shared left turn and through traffic lane or separate lanes for each approaching the intersection The experimental phase consisted of a brief orientation session to get acclimated to the driving simulator followed by two driving scenarios presented to all subjects. Each scenario consisted of a drive through an urban section of the simulator\u27s visual data base where each subject encountered a Type 1, 2 and 3 intersections. A total of 40 subjects, 25 males and 15 females were recruited for the experiment. Data logging at 60 Hz for each scenario consisted of time-stamped values of x-position and y-position of the simulator vehicle, steering, accelerator and brake inputs by the driver, and vehicle speed. After the experiment a questionnaire soliciting opinions and reactions about each intersection was administered. Simulator experiment results showed that there was a significant difference between the merge lengths for the two cases of Type 1 intersection (lane drop on the downstream side of the intersection). For Type 2 intersection (misalignment of traffic lanes between the approach and downstream side) there was a considerable difference between the average paths followed by subjects for the two cases. For Type 3 intersection (shared left and through traffic lane approaching the intersection) the simulator experiment supported the fact that people get frustrated when trapped behind a left turning vehicle in a joint left and through lane intersection and take evasive actions to cross the intersection as soon as possible

Development of rear-end collision avoidance in automobiles

The goal of this work is to develop a Rear-End Collision Avoidance System for automobiles. In order to develop the Rear-end Collision Avoidance System, it is stated that the most important difference from the old practice is the fact that new design approach attempts to completely avoid collision instead of minimizing the damage by over-designing cars. Rear-end collisions are the third highest cause of multiple vehicle fatalities in the U.S. Their cause seems to be a result of poor driver awareness and communication. For example, car brake lights illuminate exactly the same whether the car is slowing, stopping or the driver is simply resting his foot on the pedal. In the development of Rear-End Collision Avoidance System (RECAS), a thorough review of hardware, software, driver/human factors, and current rear-end collision avoidance systems are included. Key sensor technologies are identified and reviewed in an attempt to ease the design effort. The characteristics and capabilities of alternative and emerging sensor technologies are also described and their performance compared. In designing a RECAS the first component is to monitor the distance and speed of the car ahead. If an unsafe condition is detected a warning is issued and the vehicle is decelerated (if necessary). The second component in the design effort utilizes the illumination of independent segments of brake lights corresponding to the stopping condition of the car. This communicates the stopping intensity to the following driver. The RECAS is designed the using the LabVIEW software. The simulation is designed to meet several criteria: System warnings should result in a minimum load on driver attention, and the system should also perform well in a variety of driving conditions. In order to illustrate and test the proposed RECAS methods, a Java program has been developed. This simulation animates a multi-car, multi-lane highway environment where car speeds are assigned randomly, and the proposed RECAS approaches demonstrate rear-end collision avoidance successfully. The Java simulation is an applet, which is easily accessible through the World Wide Web and also can be tested for different angles of the sensor