Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

Driving anger, called "road rage", has gradually become universal phenomenon nowadays, which has been a concern to traffic management authorities. It is necessary to figure out impacting degree of the influencing factors on driving anger for taking the corresponding intervening measures. Forty drivers were enrolled to conduct naturalistic experiments on a busy route in Wuhan, China, where drivers\u27 anger can be induced by various incentive situations including jaywalking, weaving/cutting in line, traffic congestion and red light with extra paid if completing the experiment ahead of reference time. According to behavioral theory and disaggregation theory, the influencing factors including the incentive situations and personal attributes (i.e. gender, age, temperament) were determined for proposing driving anger prediction model based on MNL (multinomial logit). Then, the sensitivity of each influencing factor on driving anger was analyzed by elasticity theory on the basis of the proposed model. The result indicates that age, temperament and illegal behaviors from surrounding people are decisive influencing factors to driving anger sates with different intensity because their average elasticity values for none anger (neutral), low anger, medium anger, high anger are 1.254, 2.713, 2.914, respectively, which are all bigger than 1. Moreover, the accuracy of the proposed model is 78.30%. The results can provide theoretical support for developing key monitoring or targeted intervention to deal with the decisive influencing factors for traffic management authorities

Driver lane change intention inference for intelligent vehicles: framework, survey, and challenges

Intelligent vehicles and advanced driver assistance systems (ADAS) need to have proper awareness of the traffic context as well as the driver status since ADAS share the vehicle control authorities with the human driver. This study provides an overview of the ego-vehicle driver intention inference (DII), which mainly focus on the lane change intention on highways. First, a human intention mechanism is discussed in the beginning to gain an overall understanding of the driver intention. Next, the ego-vehicle driver intention is classified into different categories based on various criteria. A complete DII system can be separated into different modules, which consists of traffic context awareness, driver states monitoring, and the vehicle dynamic measurement module. The relationship between these modules and the corresponding impacts on the DII are analyzed. Then, the lane change intention inference (LCII) system is reviewed from the perspective of input signals, algorithms, and evaluation. Finally, future concerns and emerging trends in this area are highlighted

Age, Health, and Driving Ability: Perceptions of Older Adults

This paper presents the results of a focus group study exploring older individuals\u27 perceptions of older drivers. The study extends the stereotype research of Joanisse, Gagnon, and Voloaca (2012b), further investigating the terms used to describe older drivers. Also explored were the ways older adults perceive age versus health in their considerations of driving. Three focus groups (N=24) were conducted with former and current drivers, 64 years and older, living in Asheville, North Carolina. Participants showed positivity in their descriptions of older drivers as slow and cautious and believed they adapted their driving behavior as aging demanded. Participants showed heterogeneity in their acceptance of the health issues that threatened their continued driving ability. The importance of context in understanding stereotypes of older adults is illustrated. Results are discussed in terms of ingroup/outgroup theory in line with the proposed model

Exploration of Older Adults’ Travel Behavior and Their Transportation Barriers

Both the number of older adults and their proportion of the population are increasing rapidly in the United States. By 2040, about 20.7% of the U.S. population will be 65 and older (Harrison & Ragland, 2003a). These dramatic changes in the composition of the population will bring new challenges to the provision of transportation services. This is because the travel patterns and needs of older adults are likely to become more complicated. A growing number of people will find it increasingly difficult to meet their transportation needs. As the life expectancy of older adults is likely to continue to increase, a greater number of older people will face mobility issues alone (Alsnih & Hensher, 2003). Researchers widely agree that the aging population in the U.S. relies heavily on cars (as drivers or passengers) because they are convenient, flexible, and allow them to live independently and participate in normal daily activities (Haustein, 2012; Rosenbloom, 2005). However, dispersed land use patterns in the United States, the growing number of older adults living in suburban areas, and the current transportation infrastructure in the country make the use of a car a necessity rather than an option for a large proportion of older adults. However, as they age, their physical and mental health deteriorates, making driving dangerous for them. Therefore, it is of great importance to understand the transportation problems of older adults and provide them with reliable and acceptable alternative modes of transportation to help them meet their transportation needs. The study presented here aims to examine the transportation problems of older adults living in urban and suburban areas, make policy recommendations, and identify effective strategies to help them meet their mobility needs. To this end, the study used a mixed-method approach to identify the factors that influence older adults\u27 travel behavior and the issues they face when walking, biking, and using transit. In-depth, one-on-one surveys were conducted in three counties in southeastern Wisconsin with 178 English-speaking older adults aged 65 and older living independently in institutionalized senior housing (i.e., subsidized housing and retirement communities) and in noninstitutionalized buildings. The first main chapter of the thesis (Chapter 4) examines the factors that influence older adults\u27 mode choice for grocery shopping and aims to predict older adults\u27 travel behavior for going to the grocery store. A quantitative analysis involving statistical and machine learning techniques was conducted with older adults who traveled to the grocery store by car, carpool, walking, or public transit (N=153). The results of the study show that household car ownership and having a valid driver\u27s license are the most important factors influencing travel mode choice by older adults. However, age group (65-74 or 75+) and physical disability were not significant factors influencing older adults\u27 choice of transportation mode for grocery shopping. The second main chapter of this study (Chapter 5) examines the reasons why older adults who hold a valid driver\u27s license intend to renew their license when it expires (yes), or whether they do not intend to do so or are hesitant (no/not sure). Using a mixed-method approach including binomial logit regression and qualitative analysis, 116 older adults were surveyed. Results suggest that being 75 years of age and older, having a physical disability, and having a lower level of education (high school and below) negatively influence older adults\u27 decision to renew their driver\u27s license. Older adults who drive frequently and indicate that they would like to be able to drive to destinations easily are more likely to renew their driver\u27s license after it expires. The third main chapter of this thesis (Chapter 6) aims to examine the barriers and challenges older adults face when using modes of transportation other than the personal automobile, such as walking, bicycling, public transit, and ride-hailing. A qualitative content analysis of the 103 open-ended responses was used to fit the results into an ecological model. The study recommends four main actions to help policymakers and city governments overcome these barriers: (1) implement transportation education and outreach programs, (2) improve accessibility to services and facilities through land use policies, (3) improve transportation infrastructure and services, and (4) help for-profit and nonprofit organizations organize informal groups to walk, bike, or carpool together. This thesis has important implications for policy makers and urban practitioners to meet the transportation needs of older adults. Improving transportation infrastructure and providing older adults with reliable and high-standard non-automobile transportation alternatives, managing future land use dynamics and investing in sustainable land use patterns, and coordinating with organizations to support social networks (such as informal clubs and local groups) that help older adults meet their travel needs are among some of these important implications

'탑승자'의 관점의 시간, 위치 기반 차량 클러스터 UI 디자인 프레임 제안 연구

학위논문(석사)--서울대학교 대학원 :미술대학 디자인학부 디자인전공,2019. 8. 정의철.One important design issue is the examination of how the user interface (UI) supports the new user role in future mobility. However, there are few design studies on the passengers cognitive needs and behavior in Autonomous Vehicles (AVs) based on empirical data. There is no doubt that autonomous mobility technologies are growing. The technology is already aiding the driving experience, and it will change the mobility culture and the transition of driver into passenger. This study is based on the premise that future AV is capable of performing all driving tasks. It proposes a set of passenger-centered automotive cluster UI designs for future mobility employing two factors: time and path. A set of empirical data is provided to understand the passengers perspective. In this study, a solid set of empirical data on the cognitive needs of passengers is collected. Human cognitive characteristics and driving tasks are investigated from various viewpoints to understand the passengers iii perspective. The cognitive relationship in the driving environment is analyzed through a literature review on situation awareness (SA) and structuring of the data flow framework. The framework is further explored by connecting the technological role transformation to the passenger. To construct the empirical database on the passenger, three sets of user tests and in-depth interviews were undertaken. The user tests were designed employing the Wizard of Oz method, and the results were summarized using descriptive and exploratory analysis. Based on these insights, a set of UI designs from the perspective of the passenger was proposed, and usability tests were conducted to verify its effectiveness and usability. The results of the tests demonstrate that a major percentage of the information request was related to time (current time and duration) and path (vehicle location and surroundings). Based on the data, a UI framework was built. Two usage scenarios were designed, time-full and time-less, for better in-situation comprehension. Time- and path-based UI were proposed to flow with the scenarios. A usability test was conducted, and a passengers cognitive framework was defined. There are two aspects to this study: the data flow frameworks of the driver/passenger, and the UI design proposal. Situational precision from the perspective of the driver was analyzed to understand the relationship between the user, the vehicle and the road conditions. Further, the cognitive framework of the passenger was proposed based on the data. This study provides a solid understanding of drivers emerging needs when they are relieved of the cognitive burden of driving tasks. The UI features for AV are introduced based on the empirical data and research related to the provision of better situation awareness, focusing on time and location. This study contributes to the extant literature by observing the iv perspective of passengers in Autonomous vehicles based on a qualitative study. The proposed UI design will be further explored as a communication method between the system and the passive user in future mobility.사용자 인터페이스가 (UI) 미래 이동성에서 새로운 사용자 역할을 지지하는 디자인 도출은 미래 이동성 분야에서 중요한 디자인 이슈이다. 그러나 사용자 실험에 근거하여 자율주행차량 (AV) 의 탑승자인지 욕구와 행동에 대한 디자인 연구는 미미하다. 자율주행이 기술의 발전과 그 영역은 점차 넓어지고 있다. 해당 기술은 이미 운전 환경에 적용되고 있으며, 이로 인해 미래 이동문화에서 사용자의 역할은 '운전자'에서 '탑승자'로 변화한다. 본 연구는 미래 자율주행차량이 모든 운전 상황에 대처할 수 있다는 것을 전제로 한다. 사용자 실험을 통해 탑승자의 관점에 대한 분석을 진행하였고, 이를 기반으로 미래 모빌리티 환경에 적용될 사용자 인터페이스를 제안한다. 제안된 디자인은 운전자 중심의 상황인지에서 벗어나 탑승자 중심 인지 정보 요소를 분석하였고, 시간과 경로 두 가지 요소를 강조한 UI 를 제안한다. 본 연구에서 탑승자의 인지 정보 요구에 대한 실험적 데이터를 수집하였다. 탑승자의 관점을 이해하기 위해 다양한 관점에서 인간의 인지적 특성 및 운전 태스크를 관찰하였고, 상황인지 (SA) 에 관한 문헌 연구와 데이터 프레임워크 구조화를 통해 운전 환경에서 발생하는 인지적 요소 관계를 분석하였다. 제안된 프레임워크는 기술 변화에 따라 운전자가 탑승자로 변화되었을 때 운전 환경에서의 데이터 관계 변화를 시각적으로 구조화하여 심층적으로 탐구되었다. 탑승자의 인지 니즈 대한 실험적 데이터베이스를 수집하기 위해 총 3 세트의 유저 테스트와 심층 인터뷰가 수반되었다. 유저 테스트는 Wizard of Oz 방법을 사용하여 설계되었으며 실험 결과는 질적 연구방법론의 분석 방법을 통해 분석되었다. 실험을 통해 얻은 인사이트를 바탕으로 탑승자 관점에서 UI 디자인을 제안하고 사용성 테스트를 통해 효율성과 유용성을 5 점 리 커트 스케일로써 검증하였다. 실험 결과에 따르면 탑승자가 요청한 인지 정보는 시간 (현재 시각 및 기간)과 경로 (차량 위치 및 주변 환경)에 집중된 것을 관찰할 수 있었다. 이와 같은 데이터를 기반으로 UI 프레임워크를 구성하였다. 상황 속의 사용례를 제시하기 위하여도 가지 time-full 과 time-less 의 사용 시나리오를 구축하고, 제안된 시나리오에 따라 시간과 위치에 기반한 UI 를 제안하였다. 제안된 UI 에 대한 사용성 테스트를 진행하였고, 탑승자 관점에서의 운전상황 인지 워크 프레임을 완성하였다. 본 연구의 가치는 두 가지로 정리될 수 있다. 하나는 운전자 / 탑승자의 데이터 플로우 프레임워크를 제안하였다는 것과 두 번째는 탑승자의 관점을 지지하는 UI 디자인 제안에 있다. 운전자의 관점에서의 운전 상황을 분석하여 사용자, 차량, 그리고 도로 상태 간의 관계를 시각화하였고, 이는 탑승자인지 플로우 프레임워크를 제안하는데 기조적인 틀로써 사용되었다. 본 연구는 운전 태스크를 수행하는 데에 필요했던 인지 부담에서 벗어났을 때의 운전자가 필요로 하는 복합적인 니즈에 대해 관찰하고 미래 모빌리티 환경에 적합한 UI 의 디자인 요소에 대한 연구논문이다. 미래 자율주행차량 안의 사용자 인터페이스가 갖추어야 하는 요소를 실험적 데이터에 근거하여 제시하며, 시간과 루트를 강조하여 향상된 상황 인지를 제공하는 방법에 대한 심도있는 관찰을 기록한다. 본 연구는 질적 연구에 기초한 자율 차량의 탑승자 관점을 관찰함으로써 기존 자율주행이 디자인 연구에 기여할 것이다. 제안된 UI 디자인 미래 이동 성안에서 시스템과 탑승자 간의 커뮤니케이션 방법에 대한 연구로써 그 의의가 있다.ABSTRACT ...................................................................................................................... II CHAPTER 1. INTRODUCTION......................................................................................... １ 1.1. BACKGROUND ..............................................................................................................１ 1.2. PURPOSE .....................................................................................................................７ 1.3. RESEARCH QUESTION.....................................................................................................８ CHAPTER 2. LITERATURE REVIEW ..............................................................................１１ 2.1. SITATION AWARENESS (SA) ........................................................................................１１ 2.2. HUMAN INFORMATION PROCESSING MODEL..................................................................１５ 2.3. DRIVING SITUATION AWARENESS AND PERSPECTIVE.........................................................２０ 2.4. DRIVING TASK AND SENSORY INTERACTION ....................................................................２２ CHAPTER 3. COGNITIVE NEEDS IN AUTONOMOUS.....................................................２７ 3.1. DRIVING BEHAVIOR TRANSFORMATION AND CLUSTER UI..................................................２７ 3.2. COGNITIVE FRAMEWORK TRANSFORMATION ..................................................................３３ CHAPTER 4. USER TESTS ............................................................................................３６ 4.1. WIZARD OF OZ PROTOTYPING .....................................................................................３８ 4.2. PILOT TEST 1............................................................................................................４０ 4.2.1. Experiment Design & Laboratory Setting.................................................４０ 4.2.2. Persona Scenario & Task Design ..............................................................４２ 4.2.3. Preparation of Driving situation...............................................................４５ 4.2.4. Procedure.................................................................................................４７ 4.2.5. Data Analysis & Insight............................................................................４８ 4.3. PILOT TEST 2............................................................................................................５１ 4.3.1. Amendment: Experiment Design & Laboratory Setting ...........................５２ 4.3.2. Amendment: Task Scenario & Command Cue..........................................５４ 4.3.3. Amendment: Perform Role and preparation of driving situation ............５７ 4.3.4. Amendment: Procedure ...........................................................................５９ 4.3.5. Data Analysis & Insight............................................................................６２ 4.4. MAIN TEST ..............................................................................................................６５ 4.4.1. Experiment Design & Laboratory setting .................................................６６ 4.4.2. Task Design ..............................................................................................６９ 4.4.3. Procedure.................................................................................................７１ 4.4.4. Result Analysis & Insight..........................................................................７４ CHAPTER 5. UI CONCEPT DEVELOPMENT...................................................................８１ 5.1. UI DESIGN METHOD..................................................................................................８１ 5.2. DESIGN PROPOSAL ....................................................................................................８４ 5.3. USER SCENARIOS ......................................................................................................８６ 5.3.1 Scenario 1. Time-less: Late for a morning meeting..................................８６ 5.3.2 Scenario 2.Time-full: Leisure driving on weekends ..................................９３ CHAPTER 6. USABILITY TEST ......................................................................................９８ 6.1. USABILITY TEST GUIDE ...............................................................................................９８ 6.2. ASSESSMENT USABILITY TEST ..................................................................................１００ 6.2.1 Test planning........................................................................................１００ 6.2.2 Laboratory setting................................................................................１０２ 6.2.3 Test conduct and debriefing.................................................................１０６ 6.3. RESULT ANALYSIS ..................................................................................................１０６ CHAPTER 7. CONCLUSION......................................................................................１０７ APPENDIX 1...........................................................................................................１１０ APPENDIX 2...........................................................................................................１１１ APPENDIX 3...........................................................................................................１１３ APPENDIX 4...........................................................................................................１２１ APPENDIX 5...........................................................................................................１２４ APPENDIX 6...........................................................................................................１２８ APPENDIX 7...........................................................................................................１３３ BIBLIOGRAPHY ......................................................................................................１３６ 국문 초록 ............................................................................................................１４３Maste

Mobility and Aging: Older Drivers’ Visual Searching, Lane Keeping and Coordination

This thesis examined older drivers’ mobility and behaviour through comprehensive measurements of driver-vehicle-environment interaction and investigated the associations between driving behaviour and cognitive functions. Data were collected and analysed for 50 older drivers using eye tracking, GNSS tracking, and GIS. Results showed that poor selective attention, spatial ability and executive function in older drivers adversely affect lane keeping, visual search and coordination. Visual-motor coordination measure is sensitive and effective for driving assessment in older drivers

Microscopic Modeling of Driver Behavior Based on Modifying Field Theory for Work Zone Application

Because many freeways in the U.S. and abroad are being reconstructed or rehabilitated, it becomes increasingly important to plan and design freeway work zones with the utmost in safety and efficiency. Central to the effective design of work zones is being able to understand how drivers behave as they approach and enter a work zone area. While simple and complex microscopic models have been used over the years to analyze driver behavior, most models were not designed for application in work zones and thus do not capture the interdependencies between lane-changing and car-following vehicle movements along with the drivers’ cognitive and physical characteristics. With the use of psychology’s field theory, this dissertation develops a framework for creating vector-based, explanatory, deterministic microscopic models, to enhance our understanding of driver behavior in work zones and better aid freeway planners and designers. In field theory, an agent (i.e. the driver) views a field (i.e. the area surrounding the vehicle) filled with stimuli and perceives forces associated with each stimuli once these stimuli are internalized. Based on this theory, the new modeling framework, Modified Field Theory (MFT), is designed to directly incorporate drivers’ perceptions to roadway stimuli along with vehicle movements for drivers of different cognitive and physical abilities. From this framework, specific microscopic models, such as a simple freeway work zone car following model, can be created. It is postulated that models derived from this framework would more accurately reflect the driver decision-making process, naturally modeling the effects of external stimuli such as innovative geometric configurations, lane closures, and technology applications such as variable message boards. A simple freeway work zone car following model was created using the MFT framework. Two MFT car-following agents were created and calibrated. The second agent (Agent 2) followed the first agent (Agent 1) through a one-lane segment of freeway. Car-following data for Agent 2 was plotted on a graph of relative speed vs. distance to the lead vehicle, showing car-following behavior. Car-following behavior for Agent 2 was validated against Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center (TFHRC) Living Laboratory data for simple freeway work zone car-following (Driver 15). The car-following behavior of Agent 2 replicated the “spiraling” trend observed in Driver 15. Unlike other models (such as Wiedemann), this model does not ‘force’ these trends to occur; these trends occur naturally, as a result of the perception-reaction time delay and the nature of the forces involved. Additionally, unusual car following trends reported for Driver 15 were replicated in Modified Field Theory when conditions surrounding each event were synthetically recreated. Results demonstrated that the Modified Field Theory framework can successfully replicate the process by which a driver scans the driving environment and reacts to their surroundings. Microscopic models can successfully be created using this framework. Results demonstrated that models created from this framework naturally recreate behavioral trends observed in empirical data, and that these models are capable of replicating driving behavior in unusual scenarios, such as the car following behavior of a subject vehicle when the lead vehicle has a strong sudden acceleration event. Before this model can be applied to work zones, other calibration and validation efforts are required

Poster Session: 2017 Community Engagement and Research Symposium

List of posters presented at the 6th annual Community Engagement and Research Symposium, held Friday, March 3, 2017, at the University of Massachusetts Medical School, Worcester, MA. Some presenters agreed to make the full text of their posters available; these posters can be viewed in the symposium\u27s Poster Archive