Static and Dynamic Evaluation of the Driver Speed Perception and Selection Process

Speed impacts the extent to which mobility and safety are experienced across the surface transportation network. By expanding current understanding of speed perception and selection processes our ability to understand and comprehensively address speed-related issues will improve. Driving simulator technology has advanced the field of transportation research. However, it has been limited in its application to speed-related issues. Furthermore, static computer-based evaluations have been used as a means of establishing a preliminary understanding for driver interpretation of stimuli encountered in the roadway, but have been limited in their application to speed. These technologies allow for large sample populations to be evaluated quickly and safely. Phase I of this initiative examined driver ability to perceive travel speeds in a similar real world, simulated world, and static environment. The experimental course traversed roadway where land-use and posted speed limits varied. Drivers’ actual and perceived speeds were recorded at 20 identical “checkpoint” locations in each environment, and the results were analyzed across drivers and environments. Phase II examined three roadway attributes that impact the speed-selection process. A focus group was employed to build improved scenarios of interest for a full-scale static evaluation. In the static environment, 75 drivers were asked how fast they would travel while individual characteristics of the scenario displayed were modified. This multifaceted research initiative expands the potential application of advanced technology in speed-related research, and improves the understanding of factors that influence speed perception and selection processes

Driver and Bicyclist Comprehension of Blue Light Detection Confirmation Systems

This study analyzed motorist and bicyclist understanding and preference of positive confirmation of detection of a bicycle by the traffic signal infrastructure using a blue light detection confirmation (BLDC). The research analyzed results of an online survey of 1,123 respondents and intercept survey of 337 respondents. The study initially found that participants of the survey did not understand the meaning of the blue light itself, but comprehension of the system rose from 40% to 50% when supplemental signs were used. Respondents overwhelmingly indicated that they preferred the sign option that included symbols, text, and a representation of the blue light, in comparison with the sign options that only included symbol and text, or text and blue dot. Additionally, respondents indicated that they “strongly agree” that the supplemental signage helped with understanding the purpose of the detection confirmation devices, that they would support the system at intersections, and that it made them feel better about waiting at an intersection with light. Including supplemental signage with the symbol, text, and blue dot could potentially improve the riding experience for users, as it was strongly preferred among the alternative sign options that were tested; however, further evaluation of sign configurations may be warranted

Fuzzy Logic for Improved Dilemma Zone Identification: A Driving Simulator Study

Type-II dilemma zones are the segment of roadway approaching an intersection where drivers have difficulty deciding to stop or proceed at the onset of the circular yellow (CY) indication. Signalized intersection safety is improved when dilemma zones are correctly identified and steps are taken to reduce the likelihood that vehicles are caught in such zones. This research purports that using driving simulators as a means to collect driver response data at the onset of the CY indication is a valid methodology to augment our analysis of decisions and reactions made within the dilemma zone. The data obtained was compared against that from previous experiments documented in the literature and the evidence suggests that driving simulation is valid for describing driver behavior under the given conditions. After validating the data, fuzzy logic was proposed as a tool to model driver behavior in the dilemma zone, and three models were developed to describe driver behavior as it relates to the speed and position of the vehicle. These models were shown to be consistent with previous research on this subject and were able to predict driver behavior with up to 90% accuracy

Driver Response to Phase Termination at Signalized Intersections at Signalized Intersections: Are Driving Simulator Results Valid?

Type-II dilemma zones are the segment of roadway approaching an intersection where drivers have difficulty deciding to stop or proceed at the onset of the circular yellow indication. Signalized intersection safety is improved when dilemma zones are correctly identified and steps are taken to reduce the likelihood that vehicles are caught in such zones. This research purports that using driving simulator as a means to collect driver response data at the onset of the circular yellow indication is a valid methodology to augment our analysis of decisions and reactions made within the dilemma zone. The data obtained was compared against that from previous experiments documented in the literature and the evidence suggests that driving simulation is a valid mechanism for describing driver behavior under the given conditions

Backing collisions: a study of drivers\u27 eye and backing behaviour using combined rear-view camera and sensor systems

Context—Backing crash injures can be severe; approximately 200 of the 2,500 reported injuries of this type per year to children under the age of 15 years result in death. Technology for assisting drivers when backing has limited success in preventing backing crashes. Objectives—Two questions are addressed: Why is the reduction in backing crashes moderate when rear-view cameras are deployed? Could rear-view cameras augment sensor systems? Design—46 drivers (36 experimental, 10 control) completed 16 parking trials over 2 days (eight trials per day). Experimental participants were provided with a sensor camera system, controls were not. Three crash scenarios were introduced. Setting—Parking facility at UMass Amherst, USA. Subjects—46 drivers (33 men, 13 women) average age 29 years, who were Massachusetts residents licensed within the USA for an average of 9.3 years. Interventions—Vehicles equipped with a rear-view camera and sensor system-based parking aid. Main Outcome Measures—Subject’s eye fixations while driving and researcher’s observation of collision with objects during backing. Results—Only 20% of drivers looked at the rear-view camera before backing, and 88% of those did not crash. Of those who did not look at the rear-view camera before backing, 46% looked after the sensor warned the driver. Conclusions—This study indicates that drivers not only attend to an audible warning, but will look at a rear-view camera if available. Evidence suggests that when used appropriately, rear-view cameras can mitigate the occurrence of backing crashes, particularly when paired with an appropriate sensor system

Three- or Four-Section Displays for Permissive Left Turns? Some Evidence from a Simulator-Based Analysis of Driver Performance

This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the National Academy of Sciences and can be found at: https://doi.org/10.3141/2463-01Many jurisdictions are using the flashing yellow arrow (FYA) to control protected/permissive left turns (PPLTs). For cost and other reasons, some jurisdictions have or are considering implementing FYA with a three-section vertical head, displaying the flashing yellow indication in the same signal face as the protected green arrow. The current Manual on Uniform Traffic Control Devices (MUTCD) permits three-section operation only in height-restricted locations for permissive turns. This paper summarizes the comparison of driver performance with respect to three- and four-section FYA signal configurations gathered in a high-fidelity, motion-based driving simulator with mobile eye-tracking equipment. The experiment controlled for the effects of the opposing traffic, the presence and walking direction of pedestrians, and the signal head arrangement. A 24-intersection simulated environment was created and 27 subjects completed the course, producing 620 permissive left-turn maneuvers for further analysis. Driver performance was measured by 1) average total eye-glance durations at specific areas of interest and 2) the position of the pedestrian in the crosswalk when the driver initiated the left turn. No statistical differences were identified between the average fixation duration when the FYA was presented with a three- or four-section signal head. The pedestrian’s position in the crosswalk when the driver began the left turn was not statistically different for three of the four pedestrian walking directions presented. Overall, it would seem that measureable driver performance is not sensitive to the vertical positioning of the FYA display in the permissive interval

Traffic Signal System Misconceptions Across Three Cohorts: Novice Students, Expert Students, and Practicing Engineers

Theories of situated knowledge and research evidence suggest that students are not prepared for the engineering workforce upon graduation from engineering programs. Concept inventory results from diverse fields suggest that students do not understand fundamental engineering, mathematics, and science concepts. These two concerns may result from different knowledge deficiencies; one from lack of conceptual understanding and the other from lack of applied knowledge. The research goals of this paper are to identify misconceptions, knowledge about phenomena that are persistent and incorrect, related to traffic signal operations and design in novice and expert engineering students and practicing engineering and to attempt to explain the patterns in misconceptions across these three cohorts. Results indicate three patterns (decreasing, increasing, and no change) of misconceptions across the three cohorts considered in this study (novice students, expert students, and practicing engineers). The pattern of decreasing misconception can be explained by a traditional model of learning that suggests improved understanding with additional instruction and student time on task. The pattern of increasing misconception appeared for concepts that were particularly complex and confounded, where practicing engineers produced much more complex answers that were mostly correct, but made leaps and speculations not yet proven in the literature. Misconception frequencies that stayed the same tended to include topics that do not have required national standards or that are buried in automated processes. The process of identifying and documenting misconceptions that exist across these cohorts is a necessary step in the development of data driven curriculum. An example of a conceptual exercise developed from four misconceptions identified in this study is also demonstrated

Innovation in the classroom : A transportation geotechnics application of desktop learning modules to promote inductive learning

In many undergraduate engineering programs, students do not synthesize content learned from multiple courses until a capstone senior design course. As an example, in undergraduate civil engineering programs, transportation engineering concepts (e.g., geometric alignment, asphalt design procedures) and geotechnical engineering concepts (e.g., shear strength of soils, soil compaction) are not often synthesized until senior design, if then. As a result, concepts learned in multiple upper-division engineering courses, as well as other required courses, often seem disparate to students. In reality, engineers are required to synthesize concepts learned in a broad number of their courses to develop creative solutions to unique problems. This will particularly be true for the engineer of the future, who will need to develop unique solutions to problems caused by climate change and increasing global population, among others

Fuzzy Sets to Describe Driver Behavior in the Dilemma Zone of High-Speed Signalized Intersections

The Type II dilemma zone describes a segment of road on the approach to a signalized intersection where, if occupied by a motorist presented with the circular yellow indication, is likely to result in a motorist having difficulty deciding to stop at the stop line or proceed through the intersection. This phenomenon results in increased frequency of three failure conditions: rear-end collision at the stop line (excessive deceleration rates), the more severe right-angle crashes in the intersections, and left-turn head-on collisions (both resulting from incorrect estimates of clearance time). A more effective boundary definition for Type II dilemma zones could contribute to the safe design of signalized intersections. The prevailing approaches to dilemma zone delineation include the consideration of the vehicle’s travel time to the stop line or the driver’s likelihood of stopping at a particular distance from the stop line. The imprecision of the driver’s perception of speed and distance suggest that fuzzy logic may contribute to the identification of the Type II dilemma zone boundaries. A fuzzy logic (FL) model was constructed and validated from driver’s empirically observed behavior at high-speed signalized intersections. The research resulted in an increased understanding of the phenomenon which, when applied to the timing of signals and the placement of vehicle detection, can improve the overall safety of signalized intersections.This is the authors' peer-reviewed accepted manuscript, which is copyrighted by Elsevier. The final version of record can be found here: http://www.journals.elsevier.com/transportation-research-part-f-traffic-psychology-and-behaviour/Keywords: Dilemma zone, Safety, Driver behavior, Signalized intersection

Influence of Collaborative Curriculum Design on Educational Beliefs, Communities of Practitioners, and Classroom Practice in Transportation Engineering Education

The development and widespread implementation of best practices in transportation engineering classrooms is important in attracting and retaining the next generation of transportation engineers. Engineering education professionals have uncovered many best practices in the field; however, the process of effectively disseminating and ultimately achieving the widespread adoption of these best practices by others is not yet well understood. Sixty participants, comprising faculty members, Ph.D. students, and public sector employees, attended a Transportation Engineering Education Workshop convened in Seattle, WA to promote the collaborative development and adoption of active learning and conceptual exercises in the introduction to transportation engineering class. Participant assessments were conducted in the form of pre-, post-, and follow-up surveys. Results showed immediately positive shifts in participant beliefs about the importance of active learning and conceptual exercises with declines during the follow-up period, an increased density and connectivity of curriculum development networks, and extensive reports of valuable experiences and influences from the workshop.KEYWORDS: National Transportation Curriculum Project, (NTCP), Adoption of Innovation, Workshops, Conceptual Change, Active Learning, Introduction to Transportation Engineerin