Jacqueline M. Jenkins

Classifying Passing Maneuvers: A Behavioral Approach

Passing an impeding vehicle on a two-way two-lane roadway is a complex maneuver because of the variety of passing conditions and driver behavior. In this study, the supposition that passing maneuvers can be classified on the basis of a quantitative description of passing behavior was examined by analyzing data collected during a passing experiment conducted in a driving simulator. Evidence was found to support the following hypotheses: (a) the speed increase of the passing vehicle during the passing maneuver is smaller when the speed difference between the passing and impeding vehicles at the moment of initial acceleration is greater and (b) the speed reduction of the passing vehicle during the latter portion of the passing maneuver is greater when the time to collision with the oncoming vehicle at the moment when the passing vehicle returns to the right lane is greater. Therefore, it was concluded that the start of a pass can be classified by acceleration behavior, and the end of the pass can be classified by deceleration behavior. This behavioral approach is an improvement to classifying passing maneuvers on the basis of a qualitative assessment of the passing conditions, as in establishing the AASHTO passing sight distance design criteria and the minimum passing sight distances in the Manual on Uniform Traffic Control Devices for Streets and Highways. A particular passing behavior, described by a specific acceleration and deceleration behavior, could be used to modify or update these criteria, thereby improving the guidance given to passing drivers and potentially the safety of passing areas.

Methodology to Analyze Adaptation in Driving Simulators

Adaptation to a driving simulator is one of the necessary conditions for the validity of almost all driving simulator studies. Learning how to control a simulated vehicle requires practice, which will put some mental load on drivers and can distract them from their main task (i.e., driving). Such distraction during the learning phase affects drivers’ reactions to different situations compared with what they would have done in the real world; therefore, having a tool to confirm that adaptation occurred is necessary to have accurate data. This methodology needs to be sensitive to the diversity of driving styles and applicable to a variety of driving tasks and performance measures. A comprehensive review of the literature indicated a general deficiency in the methodologies being used. Common approaches include having participants drive for a predefined time or driving distance or drive until the participants report that they feel comfortable. Such approaches do not ensure that adaptation has indeed occurred. This paper proposes a methodology to evaluate adaptation by analyzing driver performance measures. The methodology is based on the concept of experience curve effect and is intended to complete and further develop the idea of the learning curve effect that was used in the authors’ earlier research. The methodology was tested for adaptation to acceleration and braking tasks using UBCDrive driving simulator. The results indicated that experience and learning curve effects can be used to identify adapted, adapting, and nonadapting participants.

Review of Handbook of Driving Simulation for Engineering, Medicine, and Psychology by Donald L. Fisher, Matthew Rizzo, Jeffrey Caird, and John D. Lee

Driving simulation has a history spanning several decades and has evolved with the continued advances in computing and imagegeneration technology. The result has been worldwide growth in the number of driving simulators and their expanded use for driver training, for research, and, more recently, as a driving assessment and rehabilitation tool. This publication is a meaningful compilation of driving simulation work. While it is not intended as a complete digest of driving simulation or as a replacement for volumes of technical research, the authors have managed to cover a wide breadth of topics. Each topic is discussed in enough depth to provide guidance and provoke thought; therefore, each topic will prove to be a valuable resource for those of all experience levels. This publication will serve as a great textbook for undergraduate and graduate students and as an important resource for researchers and practitioners. Each chapter in the handbook is self-contained, with its own abstract, table of contents, and list of references; therefore, each chapter will serve as a quick reference. Many chapters cite material in sibling chapters or parent sections of the handbook, directing readers to further explore other aspects of a particular topic and build on their breadth of knowledge. These linkages between chapters are appropriate as they also illustrate the interrelationships of topics that exist within the field of driving simulation. In the overview section, the authors provide guidance to the various types of readers, highlighting which chapters are most likely to be of interest. I am most interested in the section “Applications in Engineering,” specifically, the nine chapters dealing with the use of driving simulation for safety advances in transportation engineering and in-vehicle technologies. Driving simulation has been applied to study driver reactions to various elements of the driving environment, such as the roadway geometry, roadway markings, signs, signals, and other means of guidance. In the handbook, both the advantages and disadvantages of using driving simulation for such experiments are adequately identified and discussed within the various chapters. The advantages include the experimenter having control over the driving environment and simulation scenario, as well as the ability to record detailed information about driver behavior. Such control makes a driving simulator a valuable tool for examining driver reactions to various existing, unique, or nonexistent roadway elements and countermeasures that may be too dangerous or expensive to test on real roads. The level of control is governed by the limitations of the particular system software. The disadvantages include issues with fidelity, simulator sickness, and validation, as well as the cost of developing scenarios. The issue of fidelity, described in terms of a simulator’s capability to reproduce the sensory experience, is a common thread throughout the handbook. For transportation engineering studies evaluating the effectiveness of traffic control devices, appropriate images are required to permit drivers to detect, read, and comprehend traffic control devices so that drivers can choose whether to comply or make decisions regarding their travel route. Display systems vary in field of view, resolution, color accuracy, and luminance range, and the authors include a variety of tricks that have been used and may be useful for future experiments. Simulator sickness is another issue that is mentioned repeatedly throughout the handbook and certainly pertains to applications in transportation engineering. The fidelity of the driving simulator, as well as the tasks required to navigate a particular driving scenario, can contribute to the occurrence of simulator sickness. This poses a definite challenge when the road geometry or the particular type of traffic control devices being evaluated is thought to increase simulator sickness. The authors refer to a very well-known questionnaire used to measure the occurrence and severity of the symptoms and discuss various preventive measures, as well as various indicators to identify the onset of significant symptoms of simulator sickness. Given the issues of fidelity and the occurrence of simulator sickness, which can influence the behavior and performance of drivers, the results of driving simulator experiments are open to scrutiny. The authors discuss both absolute validity, in which results from comparable experiments in a simulated environment and the real world are identical, and relative validity, in which results from comparable experiments in a simulated environment and the real world compare in magnitude and direction. The authors admit to being “ : : : unaware of any driving simulation study in which absolute validity has been claimed.” Relative validity is further defined as being specific for an area of research or specific to a particular study. If study-specific validation is the objective, every simulation study will need to be accompanied by a comparable field study. Given the inherent limitations of conducting field studies, study-specific validation cannot always be assessed. Regardless, driving simulation is a tool that offers the experimenter the ability to explore transportation engineering alternatives. As with all tools, the researchers must be cognizant of the limitations of the tool and interpret the results accordingly. While providing support for the use of driving simulation in engineering, medicine, and psychology, the authors also admit the potential shortcomings and suggest approaches to address such shortcomings. In some areas, this advice is rather lean, but understandably so, given current knowledge and practices. This handbook also includes opinions of the authors, aimed at both initiating new and building on past conversations and debates, which will perhaps help shape the future of driving simulation.