Approaches for High Efficiency and Safety in Cooperative-Intelligent Transportation Systems

Cooperative-intelligent transportation systems (C-ITS) are a powerful solution to handle the problems of the transportation sector such as traffic incidents, traffic congestions, air pollution, and global warming. Ultimately, C-ITS have been developed for the safety and efficiencies of road and fuel. Using advanced vehicular communications such as dedicated short-range communication (DSRC) or cellular communication, vehicles and road infrastructures cooperate for the safety and the efficiencies, unlike the traditional intelligent transportation systems (ITS). Therefore, in C-ITS, it is important for the vehicles and the road infrastructures to retrieve necessary information in a timely manner. To achieve several goals of C-ITS (e.g., the safety and the efficiencies of road and fuel), we aim for service efficiency, fuel efficiency, and effective attack detection. To this end, we propose the following approaches. First, we introduce a data dissemination system in a bidirectional road scenario for efficient data services. Second, we propose an eco-driving guidance and eco-signal system to reduce fuel consumption and improve traffic flow at signalized intersections. Third, we investigate speed harmonization and merge control to manage the mixed traffic that consists of human-driven vehicles and connected automated vehicles (CAVs) at the bottleneck areas on highways. Finally, we propose a method to detect malicious information attacks in platoons. Through a field or realistic simulation test, we evaluate the performance of our approaches and demonstrate the trustable results. Our proposed data dissemination system contributed to improving the service efficiency by enhancing vehicle-to-vehicle (V2V) data sharing. We effectively reduced the fuel consumption at the signalized intersection, comparing to a scenario without the eco-guidance, improving the traffic flow using the eco-signal mechanism. In the merge areas on highways, CAVs effectively reduced the fuel consumption by controlling the arrival speed of mixed traffic using the speed harmonizationthe merge control alleviated the congestion level by assigning priority to vehicles at the merge area. Using our proposed attack detection method, we can quickly detect various attacks regarding attack duration, falsification size, and falsified information. To sum up, our approaches enhance the safety and improve the efficiencies of fuel and data service effectively, in realizing the potential of safe and efficient C-ITS.N1 Introduction 1 1.1 Motivation 1 1.2 Objectives 3 1.3 Challenges 6 1.4 Approaches 8 1.5 Dissertation Contributions 10 1.5.1 RSU-assisted Adaptive Scheduling for Vehicle-to-Vehicle Data Sharing in Bidirectional Road Scenarios 11 1.5.2 Field Evaluation of Vehicle to Infrastructure Communication-Based Eco-Driving Guidance and Eco-Signal System 12 1.5.3 Speed harmonization and merge control using connected automated vehicles on a highway lane closure: A reinforcement learning approach 13 1.5.4 An Approach to Detecting Malicious Information Attacks for Platoon Safety 14 1.6 Dissertation Organization 14 2 RSU-assisted Adaptive Scheduling for Vehicle-to-Vehicle Data Sharing in Bidirectional Road Scenarios 16 2.1 Introduction 16 2.2 Related Work 20 2.3 System Architecture 23 2.4 Hybrid Centralized and Ad hoc data scheduling (HCA) problem 28 2.5 RSU Cooperation-based Adaptive Scheduling (RCAS) Algorithm 31 2.5.1 Centralized data scheduling 32 2.5.2 Dynamic clustering mechanism 38 2.5.3 Ad hoc data scheduling via V2V communication 43 2.6 Performance Evaluation 45 2.6.1 Setup 45 2.6.2 Simulation Results 48 2.7 Summary 53 3 Field Evaluation of Vehicle to Infrastructure Communication based Eco-driving Guidance and Eco-signal System 54 3.1 Introduction 54 3.2 Proposed System 57 3.2.1 System architecture 58 3.2.2 Eco-guidance and eco-signal mechanisms 59 3.3 Evaluations and Results 67 3.3.1 Test scenarios 68 3.3.2 Test results 71 3.4 Summary 78 4 Speed harmonization and merge control using connected automated vehicles on a highway lane closure: A reinforcement learning approach 81 4.1 Introduction 81 4.2 Related Works 86 4.3 Reinforcement Learning 89 4.3.1 Q-Learning 89 4.3.2 DQN 91 4.4 Methodology 92 4.4.1 Test Environment of Vehicles and Highway 93 4.4.2 DQN Framework 94 4.5 Performance Evaluation 106 4.5.1 Simulation Setup 106 4.5.2 State of the Practice Algorithms 108 4.5.3 Performance Evaluation 109 4.6 Summary 118 5 An Approach to Detecting Malicious Information Attacks for Platoon Safety 120 5.1 Introduction 120 5.2 Related Work 123 5.3 Platoon and Attack Models 127 5.3.1 Platoon model 128 5.3.2 Attack models 130 5.4 Methodology 133 5.4.1 Architecture of LMID 133 5.4.2 Training/Test data sets 135 5.5 Performance Evaluation 137 5.5.1 Setup 138 5.5.2 Evaluation results 141 5.6 Summary 149 6 Conclusions 151 References 164 Summary in Korean 180차세대 지능형교통시스템은 (C-ITS) 교통사고, 교통혼잡, 공기 오염, 지구온난화와 같은 교통 분야에서 발생하는 문제들을 해결하기 위해 효과적으로 사용될 수 있는 시스템이다. 이러한 차세대 지능형교통시스템은 안전성과 연료 및 도로 효율성을 개선하는 것을 궁극적인 목표로 하고 있다. 전통적인 지능형교통시스템과는 달리 차세대 지능형교통시스템에서는 차량의 단거리 전용통신이나 셀룰러 이동통신과 같은 발전된 통신기술들을 통해 여러 차량과 도로 구조물 간 협업의 중요성을 강조한다. 이러한 협업을 통해 교통의 안전과 효율성이 개선되게 된다. 그러므로 여러 차량과 도로 구조물이 교통시스템의 원활한 작동을 위해 필수적인 정보들을 제시간에 받을 수 있도록 하는 것은 매우 중요하다. 본 논문에서는 다음과 같은 방법을 통해 차세대 지능형교통시스템의 궁극적인 목적들을 이루고자 한다. 첫째, 양방향 도로환경에서 데이터 서비스의 효율성을 증가시키기 위한 데이터 분배 시스템을 제안한다. 둘째, 신호등이 있는 교차로에서 연료 효율성뿐만 아니라 교통의 흐름을 개선하기 위한 에코드라이브 안내와 에코 신호 시스템을 제안한다. 셋째, 무인차량과 유인 차량이 공존하는 고속도로 병목 지점에서 발생하는 교통체증과 연료 효율성 문제를 해결하기 위한 속도유지기법과 차량 합류기법을 제안한다. 넷째, 고속도로에서 도로효율뿐만 아니라 연료 효율성을 높여주는 소대별 차량운행기술의 안전을 위해 허위정보공격감지기법을 제안한다. 이러한 기법들을 평가하기 위해 실제 차량을 이용한 현장실험 또는 현실성을 반영한 시뮬레이션 실험이 행해졌고 다음과 같은 결과를 얻을 수 있었다. 우선 데이터 분배기술을 통해 차량 간의 정보교환을 극대화함으로써 데이터 서비스의 효율성을 증가시킬 수 있었다. 또한, 에코드라이브 안내와 에코 신호 시스템의 유무를 비교함으로써 에코드라이브 안내 기법이 연료소비 감소에서 큰 기여를 할 수 있다는 점과 에코 신호 시스템이 교통의 혼잡을 줄이는 데 큰 역할을 할 수 있다는 점을 확인할 수 있었다. 게다가 고속도로에서 무인차량은 속도유지 기법을 통해 다른 차량들이 병목 지점에 도달하는 속도를 조절함으로써 연료소비 효율성 증대에 기여할 수 있었다. 그리고 차량 합류기법을 통해 무인차량에 합류 우선순위를 부여함으로써 합류지점에서의 혼잡도를 효과적으로 감소시킬 수 있음을 확인하였다. 마지막으로 제안된 공격탐지기법을 통해 공격 주기, 거짓 정보 종류와 그 크기에 관한 다양한 유형의 공격들을 제 빨리 탐지할 수 있음을 확인할 수 있었다.DoctordCollectio

An Approach to Detecting Malicious Information Attacks for Platoon Safety

Malicious attacks reduce the benefits of cooperative adaptive cruise control (CACC) such as safety, driving convenience, traffic flow, and fuel efficiency, by destabilizing the stability. To reinforce the resiliency of a CACC based platoon of connected and automated vehicles (CAVs), this work investigates a detection method for malicious information attacks in the platoon. In this work, we propose an attack detection method, called LMID (long short-term memory (LSTM) based malicious information detection). We consider two attack models: correlated attacks and non-correlated attacks. In our attack scenarios, one of the platoon members attacks the platoon using the attack models. Using PLEXE, a well-known platoon simulator, we develop a simulation framework to implement attack scenarios and evaluate the proposed detection method. LMID is trained depending on the length of input data and analyzed under various scenarios regarding platoon trajectories, attack types, and an emergency brake case. We have shown that without fast detection of such attacks, crashes may happen within a platoon. The simulation results demonstrate that LMID detects the malicious information attacks with higher than 96% accuracy and the attacks are detected very quickly. The performance evaluation indicates the superiority of the proposed detection method under various circumstances. © 2013 IEEE.1

Speed harmonisation and merge control using connected automated vehicles on a highway lane closure: a reinforcement learning approach

A lane closure bottleneck usually leads to traffic congestion and a waste of fuel consumption on highways. In mixed traffic that consists of human-driven vehicles and connected automated vehicles (CAVs), the CAVs can be used for traffic control to improve the traffic flow. The authors propose speed harmonisation and merge control, taking advantage of CAVs to alleviate traffic congestion at a highway bottleneck area. To this end, they apply a reinforcement learning algorithm called deep Q network to train behaviours of CAVs. By training the merge control Q-network, CAVs learn a merge mechanism to improve the mixed traffic flow at the bottleneck area. Similarly, speed harmonisation Q-network learns speed harmonisation to reduce fuel consumption and alleviate traffic congestion by controlling the speed of following vehicles. After training two Q-networks of the merge mechanism and speed harmonisation, they evaluate the trained Q-networks under various conditions in terms of vehicle arrival rates and CAV market penetration rates. The simulation results indicate that the proposed approach improves the mixed traffic flow by increasing the throughput up to 30% and reducing the fuel consumption up to 20%, when compared to the late merge control without speed harmonisation. © 2020 The Institution of Engineering and Technology.FALS

Metal Decoration Effects on the Gas-Sensing Properties of 2D Hybrid-Structures on Flexible Substrates

We have investigated the effects of metal decoration on the gas-sensing properties of a device with two-dimensional (2D) molybdenum disulfide (MoS2) flake channels and graphene electrodes. The 2D hybrid-structure device sensitively detected NO2 gas molecules (>1.2 ppm) as well as NH3 (>10 ppm). Metal nanoparticles (NPs) could tune the electronic properties of the 2D graphene/MoS2 device, increasing sensitivity to a specific gas molecule. For instance, palladium NPs accumulate hole carriers of graphene/MoS2, electronically sensitizing NH3 gas molecules. Contrarily, aluminum NPs deplete hole carriers, enhancing NO2 sensitivity. The synergistic combination of metal NPs and 2D hybrid layers could be also applied to a flexible gas sensor. There was no serious degradation in the sensing performance of metal-decorated MoS2 flexible devices before/after 5000 bending cycles. Thus, highly sensitive and endurable gas sensor could be achieved through the metal-decorated 2D hybrid-structure, offering a useful route to wearable electronic sensing platforms

Bifunctional Sensing Characteristics of Chemical Vapor Deposition Synthesized Atomic-Layered MoS₂

Two-dimensional (2D) molybdenum disulfide (MoS₂) atomic layers have a strong potential to be adopted for 2D electronic components due to extraordinary and novel properties not available in their bulk foams. Unique properties of the MoS₂, including quasi-2D crystallinity, ultrahigh surface-to-volume, and a high absorption coefficient, have enabled high-performance sensor applications. However, implementation of only a single-functional sensor presents a limitation for various advanced multifunctional sensor applications within a single device. Here, we demonstrate the charge-transfer-based sensitive (detection of 120 ppb of NO₂) and selective gas-sensing capability of the chemical vapor deposition synthesized MoS₂ and good photosensing characteristics, including moderate photoresponsivity (∼71 mA/W), reliable photoresponse, and rapid photoswitching (<500 ms). A bifunctional sensor within a single MoS₂ device to detect photons and gas molecules in sequence is finally demonstrated, paving a way toward a versatile sensing platform for a futuristic multifunctional sensor

Chemical Sensing of 2D Graphene/MoS₂ Heterostructure device

We report the production of a two-dimensional (2D) heterostructured gas sensor. The gas-sensing characteristics of exfoliated molybdenum disulfide (MoS₂) connected to interdigitated metal electrodes were investigated. The MoS₂ flake-based sensor detected a NO₂ concentration as low as 1.2 ppm and exhibited excellent gas-sensing stability. Instead of metal electrodes, patterned graphene was used for charge collection in the MoS₂-based sensing devices. An equation based on variable resistance terms was used to describe the sensing mechanism of the graphene/MoS₂ device. Furthermore, the gas response characteristics of the heterostructured device on a flexible substrate were retained without serious performance degradation, even under mechanical deformation. This novel sensing structure based on a 2D heterostructure promises to provide a simple route to an essential sensing platform for wearable electronics