This thesis presents Mantis, a system designed to evaluate possible driving routes and recommend the optimal route based on current and predicted travel conditions. The system uses the Bing Maps REST service to obtain a set of routes. Traffic data from the California Department of Transportation’s Performance Measurement System (PeMS) is then used to estimate travel times for these routes. In addition to simple travel time estimation based on instantaneous traffic conditions, Mantis can use historic data to predict traffic speeds at future times. This allows Mantis to more effectively account for regularly repeating traffic patterns such as rush hour, increasing the accuracy of its travel time estimates. Mantis is also capable of monitoring traffic incidents reported by the California Highway Patrol and identifying incidents that will be encountered along a route’s path.

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Does the use of a cell phone while driving influence the driver's ability to execute a proper turn? Is there difference between genders pertaining to motor skill while driving in a simulated driving environment? To accomplish this task, three groups of ten participants (5 women and 5 men) each were tested using a scripted test scenario focusing on left and right turns. The participants were made to drive through a test scenario to get used to the driving simulator. The scenario for the experimental group was an inner-city training scenario with the presence of vehicular traffic and the main focus area was on six critical turns (3 left and 3 rights). The apparatus used for this study was the "Patrol Simulator" built by GE Driver Development. A 2 (Gender) x 3 (Cell phone condition) between subjects design was used to assess the differences in mean driving performance between gender (male and female) at 3 cell phone conditions (No Phone, Phone No Conversation, Phone with Conversation). The study verified that cellular phones would adversely affects a driver's ability to perform turns, and showed that gender plays a role in this effect. However, it did confirm that gender does not play any role in a person's overall ability to drive. The results indicated a significant main effect for Cell phone Condition for overall turns , F (2, 24) = 38.83, p > .0005, n[eta]² = .76. Results also indicated a significant interaction between Gender and Cell Phone Conditions, F (2, 24) = 3.97, p=.032, n[eta]² = 0.25.

Geo-specific road database development is important to a driving simulation system and a very labor intensive process. Road databases for driving simulation need high resolution and accuracy. Even though commercial software is available on the market, a lot of manual work still has to be done when the road crosssectional profile is not uniform. This research deals with geo-specific road databases development, especially for roads with non-uniform cross sections. In this research, the United States Geographical Survey (USGS) road information is used with aerial photos to accurately extract road boundaries, using image segmentation and data compression techniques. Image segmentation plays an important role in extracting road boundary information. There are numerous methods developed for image segmentation. Six methods have been tried for the purpose of road image segmentation. The major problems with road segmentation are due to the large variety of road appearances and the many linear features in roads. A method that does not require a database of sample images is desired. Furthermore, this method should be able to handle the complexity of road appearances. The proposed method for road segmentation is based on the mean-shift clustering algorithm and it yields a high accuracy. In the phase of building road databases and visual databases based on road segmentation results, the Linde-Buzo-Gray (LBG) vector quantization algorithm is used to identify repeatable cross section profiles. In the phase of texture mapping, five major uniform textures are considered - pavement, white marker, yellow marker, concrete and grass. They are automatically mapped to polygons. In the chapter of results, snapshots of road/visual database are presented.

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's comfort, convenience, anxiety, and preferences. The primary objective of this study was to demonstrate the feasibility of using the University of Central Florida's 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's 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.

This dissertation presents two studies examining the interaction between workload history and driver mental workload. The first experiment focuses on testing for the presence of a hysteresis effect in the driving task. The second experiment examines the proposition that cueing impending periods of higher task demand can reduce the impact of any such potential hysteresis effects. Thirty-two licensed drivers served as participants and all served in both studies. Using the directions provided by a Heads-Up-Display navigation system, participants followed a pre-set route in the simulated environment. At specified points within the drive, the navigation system would purposefully fail which required drivers to relay a ten digit alphanumeric error code to a remote operator in order to reset the system. Results indicated that this increase in task demand from the navigation system's failure leads to a significant increase in perceived mental workload as compared to pre-failure periods. This increase in driver mental workload was not significantly reduced by the time the drive ended, indicating the presence of a hysteresis effect. In the second experiment, the navigation system provided a completely reliable visual warning before failure. Results indicate that cueing had neither an effect on perceived mental workload, nor any ameliorating effect on the hysteretic type effect seen in mental workload recovery. The conclusion of these findings being that the overall safety and efficiency of the surface transportation system would likely improve by designs which accommodate the periods immediately following a reduction in stress. Whether from leaving high demand areas such as work zones or in the period immediately after using a in-car information device such as a GPS or a cell phone, these post-high workload periods are associated with increased variability in driver inputs and levels of mental workload.

Communities for Older Adults: Rising to Integrate a Driver’s Education Resource Program (COA-RIDER) serves as a guide for leaders of local health and community welfare groups, including health-related personnel, that are interested in organizing and expanding a driving resource program in their local communities. This program is a response to the issue of limited community driving resource programs for older adults, many of whom will remain driving as they age. The COA-RIDER program aims to have more community organizations host and collect data for research to sustain future driving resource programs for older adults. Working in collaboration with various individuals, groups, and organizations can build cohesion among members of the community. This program is an opportunity for community members to gain a better understanding of professional roles and duties across different disciplines and fields. Collectively, all can help in the developmental process of providing a beneficial health and wellness resource program for aging drivers. Most importantly, this program not only educates on the importance of addressing mental, physical, and social health; it advocates for older adults to stay connected in their communities through driving, community mobility options, and local resources so that they can remain independent for as long as possible.

<p> We address a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems in this thesis. The driving-forces account for the perturbation inputs or the irregular variations in the internal variables of a dynamic system. These inputs are hidden from the observer most of the time if not always. Reconstruction of such inputs when there is too little or no prior knowledge to build a mathematical model to describe the system's behavior is an important problem in many cases in physics and engineering. To this end, we propose a method for the recursive estimation of driving-forces without the availability of an analytic model of the unknown physical phenomenon. </p> <p> The underlying idea of the proposed estimator is to predict the observables onestep ahead of the current time instant, and then retrieve the driving-force from the prediction error. This idea is embodied by predicting the observables using a bank of echo state networks (ESN) in an online fashion, extracting the raw estimates from the prediction error, and then finally smoothing these estimates in separate adaptive filtering stages. The approach described herein distinguishes itself from the similar methods in the literature in its adaptivity and its greater immunity against varying environmental uncertainties. The adaptive nature of the estimator enables us to retrieve both slowly and rapidly varying driving-forces accurately in presence of model or sensor noises, which are illustrated by experiments in the subsequent chapters of this thesis. In particular, some chaotic/stochastic nonlinear models are studied in controlled experiments. The estimation quality of the proposed approach is judged with a reference to the Posterior Cramer-Rao Lower Bound as a theoretical lower limit on the estimation error. </p> <p> The Bayesian and Maximum-Likelihood (ML) methods are also studied for the estimation of driving-forces when partial or full information is available on the mathematical description of the unknown system. These methods serve as practical merits of assessment for the proposed driving-force estimator. Moreover, a direct performance comparison between the proposed estimator and a favorable estimation scheme of a similar kind is provided, which confirms the advantages of the proposed approach. The proposed method is tested on a real-world application on the extraction of sun's magnetic flux from the sunspot time series. It is illustrated that the results obtained by the proposed estimator are in close agreement with the results of two other analytical studies. </p> <p> Finally, a solution to a real problem in practice is proposed using the method. Specifically, extracting the signature of a small random target embedded in the sea surface is addressed using the live recorded data collected with the McMaster IPIX radar. This is the first specific realization of a radar scene analyzer for the cognitive radar reception in the literature to the author's best knowledge. </p> <p> The material in this thesis is presented in a sandwich thesis format, combining two peer reviewed, published journal articles, and another journal article that is prepared for submission. An additional chapter that provides the background material is included for the completeness of the presentation. </p> / Thesis / Doctor of Philosophy (PhD)

For people who are blind or have low vision (BLV), physical barriers and negative experiences related to using current transportation options can have negative impacts on quality of life. The emergence of levels 4 – 5 automated driving system-dedicated vehicles (L4+ ADS), which will not require human operators to provide any input into the dynamic driving task, could empower the BLV community by providing an independent means of transportation. Yet, the BLV community has concerns that their needs are not being adequately considered by those currently developing L4+ ADSs, which will result in this technology being inaccessible to populations that it would otherwise greatly benefit. The current study sought to address this gap in the literature by explicitly evaluating the information and interactions that BLV riders will require from L4+ ADS. Specifically, we collected focus group and empirical data across three studies on BLV riders' information and interaction requirements for L4+ ADSs across expected and unexpected driving scenarios as well as pick-up and drop-off tasks (PUDO). Through focus groups with sighted (n = 11) and BLV participants (n = 11; Study 1), we identified similarities and differences between sighted and BLV participants in terms of their user needs for L4+ ADSs across five challenging driving scenarios. Next, we examined BLV participants' (n = 13; Study 2) information requests in real-world settings to better understand BLV riders' needs during a simulated L4+ ADS experience. Our findings show that BLV riders want information that helps with (a) orienting to important objects in the environment during PUDO, (b) determining their location while riding in the ADS, and (c) understanding the ADSs' actions. Finally, we developed an HMI prototype using BLV riders' feedback in Studies 1 and 2 and had BLV participants engage with it during a simulated L4+ ADS trip (n = 12; Study 3). Our results suggest that BLV riders value information about nearby landmarks in familiar and unfamiliar areas, as well as explanations for ADS's actions during ordinary and unexpected scenarios. Additionally, BLV riders need information about required walking distances and presence of tripping hazards in order to select a drop-off location. Taken together, our studies show that BLV riders have specific requirements that L4+ ADS must meet in order for this to be an accessible means of transportation. In light of these findings, we generated 28 guidelines and 44 recommendations that could be used by designers to improve the accessibility of L4+ ADSs for BLV riders. / Doctor of Philosophy / When using current transportation options, individuals who are blind or have low vision (BLV) often encounter physical barriers and negative experiences, which can limit their ability to travel independently and have negative impacts on their overall quality of life. However, future vehicles equipped with levels 4 – 5 automated driving systems (L4+ ADSs) will offer transportation that requires no input from human operators, and thus, could be used as an independent means of transportation for the BLV community. Unfortunately, the BLV community has concerns that their needs are not being adequately considered by those currently developing L4+ ADSs, which will result in this technology being inaccessible to populations that it would otherwise greatly benefit. The current work sought to address this gap in the literature by evaluating the information and interactions that BLV riders will require from L4+ ADS. We conducted three studies to collected data on BLV riders' information and interaction requirements for L4+ ADSs across a variety of driving scenarios as well as tasks relating to being picked up and dropped-off by an L4+ ADS. First, through focus groups with sighted and BLV participants, we identified similarities and differences between sighted and BLV participants' user needs for L4+ ADSs across five challenging driving scenarios. Next, to better understand BLV riders' needs, we had BLV participants indicate when they would desire information during a simulated L4+ ADS ride-hailing experience in real-world settings. Our findings show that BLV riders want information that helps with (a) orienting to important objects in the environment during PUDO, (b) determining their location during their trip, and (c) understanding the reason for the ADS's actions. Finally, using BLV riders' feedback, we developed an HMI prototype and had BLV participants engage with it during a simulated L4+ ADS trip. Our results suggest that BLV riders value information about nearby landmarks in both familiar and unfamiliar areas, as well as explanations for ADS's actions during common (e.g., stopping at a stop sign) and unexpected driving scenarios (e.g., sudden swerve). Additionally, when being dropped off, BLV riders need information about required walking distances and presence of tripping hazards in order to select a desirable drop-off location. Taken together, our studies show that BLV riders have specific requirements that L4+ ADS must meet in order for this to be an accessible means of transportation. In light of these findings, we generated a set of guidelines and recommendations that designers can use to improve the accessibility of L4+ ADSs for BLV riders.

A study was undertaken to test and evaluate the human factors design aspects of an automobile moving-map navigation system. The primary objective of the study was to assess the driver attentional demand required by the navigation system during vehicle operation. A secondary objective of the study was to assess design specifics and determine whether or not the design was optimal in terms of efficiency of use in an automotive environment. Thirty-two driver-subjects drove a specially instrumented 1985 Cadillac Sedan de Ville on public roadways for this research. A cross-section of driver-subjects (both genders, ages 18 to 73, and driving experience from 2,000 to 40,000 miles per year) participated, and a cross·section of roadway types (residential, two-lane state route, and limited·access four-lane) and traffic conditions (light and moderate) were used as part of this research. The driver-subjects were asked to perform a variety of tasks while operating the research vehicle. These tasks included navigation tasks normally performed while using the navigation system, as well as a wide variety of conventional automotive tasks (e.g., tuning the radio or reading the speedometer) normally performed during vehicle operation. The purpose of asking the driver-subjects to perform a variety of conventional automotive tasks was so that direct comparisons in attentional demand could be made between tasks performed daily in an automotive environment and the navigation tasks. Twenty-one performance and behavioral measures were collected and analyzed for this research. These measures included eye—scanning and dwell-time measures, task-completion-time measures, and a variety of measures indicating driver performance and behavior. The data analyses for these measures focused on two major goals. First, the analyses determined which tasks (both navigator and conventional) required the highest attentional demand. Second, the analyses were used to determine groups of tasks which, for all practical purposes, required equivalent attentional demand. The results of the analyses indicated that the navigation system is a relatively effective device, useful for its intended purpose. The results also indicated that a number of design improvements are required, however, to optimize the safety and efficiency of the device. An iterative process of design improvement and further research into the effects of improved design on required attentional demand is therefore recommended. / Ph. D.