Are We Ready for Smart Transport? Analysis of Attitude Towards Public Transport in Budapest

In every case of serious development that concerns the majority of society, it is vital to analyze the current social opinion on the particular service and to analyze the possible effects, that the elements of the system being developed, could have. This is no different, when it comes to smart cities, more specifically smart traffic systems, even if these developments are to serve the improvement of people’s living conditions. It is essential to determine what the decisive factors are for the man of today in choosing a mode of transport; which attributes influence that decision; what sort of opinion that individual has about different urban modes and whether he/she is ready to utilise smart means of transport. Furthermore,it is inevitable to explore, what would make people choose smart solutions (e.g. autonomous vehicles). Current article is to showcase the responses to the above questions of people living in the Hungarian capital, Budapest. The article begins with an overview of the international literature on smart cities and their transport system. Afterwards, the results of a research sponsored by the Hungarian Ministry of Human Capacities are presented, followed by the conclusions based on the results obtained

Game Theoretic Analysis of Road User Safety Scenarios Involving Autonomous Vehicles

Interactions between pedestrians, bikers, and human-driven vehicles have been a major concern in traffic safety over the years. The upcoming age of autonomous vehicles will further raise major problems on whether self-driving cars can accurately avoid accidents; on the other hand, usability issues arise on whether human-driven cars and pedestrians can dominate the road at the expense of the autonomous vehicles which will be programmed to avoid accidents. This paper proposes some game theoretical models applied to related traffic scenarios. In the first two games the reciprocal influence between a pedestrian and a vehicle (either autonomous or not) is analyzed, while the third game investigates the intersection of two vehicles, possibly autonomous. The games have been simulated in order to demonstrate the theoretical analysis and the predicted behaviors. These investigations can shed new lights on how novel urban traffic regulations could be required to allow for a better interaction of vehicles and a general improved management of traffic and communication vehicular networks.Comment: Accepted at 'IEEE International Symposium on Personal, Indoor and Mobile Radio Communications' 9-12 September 2018 - Bologna, Italy. Special Session on 'Wireless Technologies for Connected and Autonomous Vehicles'. 7 pages, 5 figure

The Challenges Facing Autonomous Vehicles and The Progress in Addressing Them

Autonomous vehicles are an emerging technology that faces challenges, both technical and socioeconomic. This paper first addresses specific technical challenges, such as parsing visual data, communicating with other entities, and making decisions based on environmental knowledge. The technical challenges are to be addressed by the fields of image processing, Vehicle to Everything Communication (V2X), and decision-making systems. Non-technical challenges such as ethical decision making, social acceptance, and economic pushback are also discussed. Ethical decision making is discussed in the framework of deontology vs utilitarianism, while social acceptance of utilitarian autonomous vehicles is also investigated. Last, the likely economic impact is described

Look Both Ways: Intersections Of Past And Present In The Shaping Of Relations Between Cyclists, Pedestrians, And Driverless Cars

Driverless cars are expected to transform society in many ways. Since nowadays most collisions are due to human error, safety is among the most anticipated benefits of the technology. The promise of near zero fatalities on roads appears in many industry statements and government reports. Because of that, every collision, especially involving fatalities, receives much attention from the media and public. That kind of scrutiny resembles the early days of the conventional automobiles. In those days, automobiles – also called “horseless carriages” – were not well received by the majority of the population. Cars brought conflicts and fatalities on roads to a level never seen before. The automobile industry, using public relations, shifted society’s perception about who belongs to the roads, and who should be blamed for the rise of fatalities. That shift influenced legislation and tort law in motor-vehicle centric ways. It also created cities with infrastructure focused on the automobile at the expense of other means of transportation. Today, one of the most difficult challenges for driverless cars is the unpredictability of pedestrian and cyclist behaviour. To accelerate the deployment of the technology, some are considering the necessity of law enforcement against pedestrians and other street users. Centred on urban environments, pedestrians and cyclists, and with an interdisciplinary and advocacy-oriented approach, this thesis seeks to contribute to the debate about the safety and deployment of driverless cars, its influence on law and legislation, and how a car-centred view of the technology may limit its potentialities

The social perspective on policy towards local shared autonomous vehicle services (LSAVS)

The transport policy discourse posits Shared Autonomous Vehicles (SAVs) as a more sustainable solution for the implementation of road automation technology. A successful implementation of SAV services strongly depends on being able to meet user's needs, as well as responding to their expectations. For this reason, the public has a central role in the definition of appropriate and realistic policies for the design, regulation and adoption of new automated mobility services. However, whilst there has been considerable attention to individuals' attitudes towards road transport automation, few have applied participatory or co-design methods to help define new SAV services. Moreover, most of the existing studies have also been hypothetical rather than examining vehicles in real service settings. This paper addresses these imbalances through reporting a two-stage research initiative. Initially a local shared automated vehicle service (LSAVS) concept was examined in a co-design workshop (Stage 1), leading to the development of a conceptual framework for social acceptance. This was then applied (Stage 2) in qualitative empirical research into the experiences of participants who rode in two different live prototype LSAVS. It was found that social considerations such as equity in access to mobility services, social inclusion, environmental protection, and concerns about control over interpersonal interactions emerged as strong acceptance factors within participants' construction of the conceptual services and responses to exposure to actual services. However, broad socio-political aspirations beyond transport policy were also important. It is concluded that achieving high levels of social acceptance where these utopian expectations meet commercial realities and public-sector constraints will be a major policy challenge facing any attempt to introduce an LSAVS with strong sustainable mobility credentials

Assessing Pedestrian Safety Conditions on Campus

Pedestrian-related crashes are a significant safety issue in the United States and cause considerable amounts of deaths and economic cost. Pedestrian safety is an issue that must be uniquely evaluated in a college campus, where pedestrian volumes are dense. The objective of this research is to identify issues at specific locations around UCF and suggest solutions for improvement. To address this problem, a survey that identifies pedestrian safety issues and locations is distributed to UCF students and staff, and an evaluation of drivers reactions to pedestrian to vehicle (P2V) warning systems is studied through the use of a NADS MiniSim driving simulator. The survey asks participants to identify problem intersections around campus and other issues as pedestrians or bicyclists in the UCF area. Univariate probit models were created from the survey data to identify which factors contribute to pedestrian safety issues, based off the pedestrian\u27s POV and the driver\u27s POV. The models indicated that the more one is exposed to traffic via walking, biking, and driving to campus contributes to less safe experiences. The models also show that higher concerns with drivers not yielding, unsafety of crossing the intersections, and the number of locations to cross, indicate less safe pedestrian experiences from the point of view of pedestrians and drivers. A promising solution for pedestrian safety is Pedestrian to Vehicle (P2V) communication. This study simulates P2V connectivity using a NADS MiniSim Driving Simulator to study the effectiveness of the warning system on drivers. According to the results, the P2V warning system significantly reduced the number of crashes in the tested pre-crash scenarios by 88%. Particularly, the P2V warning system can help decrease the driver\u27s reaction time as well as impact velocity if the crash were to occur

도심 교차로에서의 자율주행을 위한 주변 차량 경로 예측 및 거동 계획 알고리즘

학위논문(박사)--서울대학교 대학원 :공과대학 기계항공공학부,2020. 2. 이경수.차랑용 센싱 및 처리기술이 발달함에 따라 자동차 기술 연구가 수동 안전 기술에서 능동 안전 기술로 초점이 확장되고 있다. 최근, 주요 자동차 제작사들은 능동형 차간거리 제어, 차선 유지 보조, 그리고 긴급 자동 제동과 같은 능동 안전 기술이 이미 상업화하고 있다. 이러한 기술적 진보는 사상률 제로를 달성하기 위하여 기술 연구 분야를 능동 안전 기술을 넘어서 자율주행 시스템으로 확장시키고 있다. 특히, 도심 도로는 인도, 사각지대, 주차차량, 이륜차, 보행자 등과 같은 교통 위험 요소를 많이 갖고 있기 때문에 고속도로보다 사고 발생률과 사상률이 높으며, 이는 도심 도로에서의 자율주행은 핵심 이슈가 되고 있다. 많은 프로젝트들이 자율주행의 환경적, 인구학적, 사회적, 그리고 경제적 측면에서의 자율주행의 효과를 평가하기 위해 수행되었거나 수행 중에 있다. 예를 들어, 유럽의 AdaptIVE는 다양한 자율주행 기능을 개발하였으며, 구체적인 평가 방법론을 개발하였다. 또한, CityMobil2는 유럽 전역의 9개의 다른 환경에서 무인 지능형 차량을 성공적으로 통합하였다. 일본에서는 2014년 5월에 시작된 Automated Driving System Research Project는 자율주행 시스템과 차세대 도심 교통 수단의 개발 및 검증에 초점을 맞추었다. 기존 연구들에 대한 조사를 통해 자율주행 시스템은 교통 참여자들의 안전도를 향상시키고, 교통 혼잡을 감소시키며, 운전자 편의성을 증진시키는 것이 증명되었다. 다양한 방법론들이 인지, 거동 계획, 그리고 제어와 같은 도심 도로 자율주행차의 핵심 기술들을 개발하기 위하여 사용되었다. 하지만 많은 최신의 자율주행 연구들은 각 기술의 개발을 별개로 고려하여 진행해왔다. 결과적으로 통합적인 관점에서의 자율주행 기술 설계는 아직 충분히 고려되어 않았다. 따라서, 본 논문은 복잡한 도심 도로 환경에서 라이다, 카메라, GPS, 그리고 간단한 경로 맵에 기반한 완전 자율주행 알고리즘을 개발하는 것을 목표로 하였다. 제안된 자율주행 알고리즘은 비통제 교차로를 포함한 도심 도로 상황을 차량 거동 예측기와 모델 예측 제어 기법에 기반하여 설계되었다. 본 논문은 동적, 정적 환경 표현 및 종횡방향 거동 계획을 중점적으로 다루었다. 본 논문은 도심 도로 자율주행을 위한 거동 계획 알고리즘의 개요를 제시하였으며, 실제 교통 상황에서의 실험 결과는 제안된 알고리즘의 효과성과 운전자 거동과의 유사성을 보여주었다. 실차 실험 결과는 비통제 교차로를 포함한 도심 시나리오에서의 강건한 성능을 보여주었다.The foci of automotive researches have been expanding from passive safety systems to active safety systems with advances in sensing and processing technologies. Recently, the majority of automotive makers have already commercialized active safety systems, such as adaptive cruise control (ACC), lane keeping assistance (LKA), and autonomous emergency braking (AEB). Such advances have extended the research field beyond active safety systems to automated driving systems to achieve zero fatalities. Especially, automated driving on urban roads has become a key issue because urban roads possess numerous risk factors for traffic accidents, such as sidewalks, blind spots, on-street parking, motorcycles, and pedestrians, which cause higher accident rates and fatalities than motorways. Several projects have been conducted, and many others are still underway to evaluate the effects of automated driving in environmental, demographic, social, and economic aspects. For example, the European project AdaptIVe, develops various automated driving functions and defines specific evaluation methodologies. In addition, CityMobil2 successfully integrates driverless intelligent vehicles in nine other environments throughout Europe. In Japan, the Automated Driving System Research Project began on May 2014, which focuses on the development and verification of automated driving systems and next-generation urban transportation. From a careful review of a considerable amount of literature, automated driving systems have been proven to increase the safety of traffic users, reduce traffic congestion, and improve driver convenience. Various methodologies have been employed to develop the core technology of automated vehicles on urban roads, such as perception, motion planning, and control. However, the current state-of-the-art automated driving algorithms focus on the development of each technology separately. Consequently, designing automated driving systems from an integrated perspective is not yet sufficiently considered. Therefore, this dissertation focused on developing a fully autonomous driving algorithm in urban complex scenarios using LiDAR, vision, GPS, and a simple path map. The proposed autonomous driving algorithm covered the urban road scenarios with uncontrolled intersections based on vehicle motion prediction and model predictive control approach. Mainly, four research issues are considered: dynamic/static environment representation, and longitudinal/lateral motion planning. In the remainder of this thesis, we will provide an overview of the proposed motion planning algorithm for urban autonomous driving and the experimental results in real traffic, which showed the effectiveness and human-like behaviors of the proposed algorithm. The proposed algorithm has been tested and evaluated using both simulation and vehicle tests. The test results show the robust performance of urban scenarios, including uncontrolled intersections.Chapter 1 Introduction 1 1.1. Background and Motivation 1 1.2. Previous Researches 4 1.3. Thesis Objectives 9 1.4. Thesis Outline 10 Chapter 2 Overview of Motion Planning for Automated Driving System 11 Chapter 3 Dynamic Environment Representation with Motion Prediction 15 3.1. Moving Object Classification 17 3.2. Vehicle State based Direct Motion Prediction 20 3.2.1. Data Collection Vehicle 22 3.2.2. Target Roads 23 3.2.3. Dataset Selection 24 3.2.4. Network Architecture 25 3.2.5. Input and Output Features 33 3.2.6. Encoder and Decoder 33 3.2.7. Sequence Length 34 3.3. Road Structure based Interactive Motion Prediction 36 3.3.1. Maneuver Definition 38 3.3.2. Network Architecture 39 3.3.3. Path Following Model based State Predictor 47 3.3.4. Estimation of predictor uncertainty 50 3.3.5. Motion Parameter Estimation 53 3.3.6. Interactive Maneuver Prediction 56 3.4. Intersection Approaching Vehicle Motion Prediction 59 3.4.1. Driver Behavior Model at Intersections 59 3.4.2. Intention Inference based State Prediction 63 Chapter 4 Static Environment Representation 67 4.1. Static Obstacle Map Construction 69 4.2. Free Space Boundary Decision 74 4.3. Drivable Corridor Decision 76 Chapter 5 Longitudinal Motion Planning 81 5.1. In-Lane Target Following 82 5.2. Proactive Motion Planning for Narrow Road Driving 85 5.2.1. Motivation for Collision Preventive Velocity Planning 85 5.2.2. Desired Acceleration Decision 86 5.3. Uncontrolled Intersection 90 5.3.1. Driving Phase and Mode Definition 91 5.3.2. State Machine for Driving Mode Decision 92 5.3.3. Motion Planner for Approach Mode 95 5.3.4. Motion Planner for Risk Management Phase 98 Chapter 6 Lateral Motion Planning 105 6.1. Vehicle Model 107 6.2. Cost Function and Constraints 109 Chapter 7 Performance Evaluation 115 7.1. Motion Prediction 115 7.1.1. Prediction Accuracy Analysis of Vehicle State based Direct Motion Predictor 115 7.1.2. Prediction Accuracy and Effect Analysis of Road Structure based Interactive Motion Predictor 122 7.2. Prediction based Distance Control at Urban Roads 132 7.2.1. Driving Data Analysis of Direct Motion Predictor Application at Urban Roads 133 7.2.2. Case Study of Vehicle Test at Urban Roads 138 7.2.3. Analysis of Vehicle Test Results on Urban Roads 147 7.3. Complex Urban Roads 153 7.3.1. Case Study of Vehicle Test at Complex Urban Roads 154 7.3.2. Closed-loop Simulation based Safety Analysis 162 7.4. Uncontrolled Intersections 164 7.4.1. Simulation based Algorithm Comparison of Motion Planner 164 7.4.2. Monte-Carlo Simulation based Safety Analysis 166 7.4.3. Vehicle Tests Results in Real Traffic Conditions 172 7.4.4. Similarity Analysis between Human and Automated Vehicle 194 7.5. Multi-Lane Turn Intersections 197 7.5.1. Case Study of a Multi-Lane Left Turn Scenario 197 7.5.2. Analysis of Motion Planning Application Results 203 Chapter 8 Conclusion & Future Works 207 8.1. Conclusion 207 8.2. Future Works 209 Bibliography 210 Abstract in Korean 219Docto