Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network

Accurate lane localization and lane change detection are crucial in advanced driver assistance systems and autonomous driving systems for safer and more efficient trajectory planning. Conventional localization devices such as Global Positioning System only provide road-level resolution for car navigation, which is incompetent to assist in lane-level decision making. The state of art technique for lane localization is to use Light Detection and Ranging sensors to correct the global localization error and achieve centimeter-level accuracy, but the real-time implementation and popularization for LiDAR is still limited by its computational burden and current cost. As a cost-effective alternative, vision-based lane change detection has been highly regarded for affordable autonomous vehicles to support lane-level localization. A deep learning-based computer vision system is developed to detect the lane change behavior using the images captured by a front-view camera mounted on the vehicle and data from the inertial measurement unit for highway driving. Testing results on real-world driving data have shown that the proposed method is robust with real-time working ability and could achieve around 87% lane change detection accuracy. Compared to the average human reaction to visual stimuli, the proposed computer vision system works 9 times faster, which makes it capable of helping make life-saving decisions in time

The State-of-the-art of Coordinated Ramp Control with Mixed Traffic Conditions

Ramp metering, a traditional traffic control strategy for conventional vehicles, has been widely deployed around the world since the 1960s. On the other hand, the last decade has witnessed significant advances in connected and automated vehicle (CAV) technology and its great potential for improving safety, mobility and environmental sustainability. Therefore, a large amount of research has been conducted on cooperative ramp merging for CAVs only. However, it is expected that the phase of mixed traffic, namely the coexistence of both human-driven vehicles and CAVs, would last for a long time. Since there is little research on the system-wide ramp control with mixed traffic conditions, the paper aims to close this gap by proposing an innovative system architecture and reviewing the state-of-the-art studies on the key components of the proposed system. These components include traffic state estimation, ramp metering, driving behavior modeling, and coordination of CAVs. All reviewed literature plot an extensive landscape for the proposed system-wide coordinated ramp control with mixed traffic conditions.Comment: 8 pages, 1 figure, IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE - ITSC 201

Integrated and adaptive traffic signal control for diamond interchange : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Mechatronics Engineering at Massey University, Albany, New Zealand

New dynamic signal control methods such as fuzzy logic and artificial intelligence developed recently mainly focused on isolated intersection. Adaptive signal control based on fuzzy logic control (FLC) determines the duration and sequence that traffic signal should stay in a certain state, before switching to the next state (Trabia et al. 1999, Pham 2013). The amount of arriving and waiting vehicles are quantized into fuzzy variables and fuzzy rules are used to determine if the duration of the current state should be extended. The fuzzy logic controller showed to be more flexible than fixed controllers and vehicle actuated controllers, allowing traffic to flow more smoothly. The FLC does not possess the ability to handle various uncertainties especially in real world traffic control. Therefore it is not best suited for stochastic nature problems such as traffic signal timing optimization. However, probabilistic logic is the best choice to handle the uncertainties containing both stochastic and fuzzy features (Pappis and Mamdani 1977) Probabilistic fuzzy logic control is developed for the signalised control of a diamond interchange, where the signal phasing, green time extension and ramp metering are decided in response to real time traffic conditions, which aim at improving traffic flows on surface streets and highways. The probabilistic fuzzy logic for diamond interchange (PFLDI) comprises three modules: probabilistic fuzzy phase timing (PFPT) that controls the green time extension process of the current running phase, phase selection (PSL) which decides the next phase based on the pre-setup phase logic by the local transport authority and, probabilistic fuzzy ramp-metering (PFRM) that determines on-ramp metering rate based on traffic conditions of the arterial streets and highways. We used Advanced Interactive Microscopic Simulator for Urban and Non-Urban Network (AIMSUN) software for diamond interchange modeling and performance measure of effectiveness for the PFLDI algorithm. PFLDI was compared with actuated diamond interchange (ADI) control based on ALINEA algorithm and conventional fuzzy logic diamond interchange algorithm (FLDI). Simulation results show that the PFLDI surpasses the traffic actuated and conventional fuzzy models with lower System Total Travel Time, Average Delay and improvements in Downstream Average Speed and Downstream Average Delay. On the other hand, little attention has been given in recent years to the delays experienced by cyclists in urban transport networks. When planning changes to traffic signals or making other network changes, the value of time for cycling trips is rarely considered. The traditional approach to road management has been to only focus on improving the carrying capacity relating to vehicles, with an emphasis on maximising the speed and volume of motorised traffic moving around the network. The problem of cyclist delay has been compounded by the fact that the travel time for cyclists have been lower than those for vehicles, which affects benefit–cost ratios and effectively provides a disincentive to invest in cycling issues compared with other modes. The issue has also been influenced by the way in which traffic signals have been set up and operated. Because the primary stresses on an intersection tend to occur during vehicle (commuter) peaks in the morning and afternoon, intersections tend to be set up and coordinated to allow maximum flow during these peaks. The result is that during off-peak periods there is often spare capacity that is underutilised. Phasing and timings set up for peaks may not provide the optimum benefits during off-peak times. This is particularly important to cyclists during lunch-time peaks, when vehicle volumes are low and cyclist volumes are high. Cyclists can end up waiting long periods of time as a result of poor signal phasing, rather than due to the demands of other road users being placed on the network. The outcome of this study will not only reduce the traffic congestion during peak hours but also improve the cyclists’ safety at a typical diamond interchange

Inter-technology Effects in Intelligent Transportation Systems

This project examines the expected benefits of varying combinations of ITS applications: Freeway Service Patrol, Changeable Message Signs, and Ramp Metering. The research analyzes the simulated results of a stylized network in a microscopic traffic simulator. The traffic network includes parallel roadways, ramp meters and changeable message signs. We have tested these technologies in various combinations. We measure effectiveness as consumers' surplus and define a measure of inter-technology economies. In brief, it is found that additional technologies are sub-additive, and more benefits come from each technology in isolation than when it is bundled with other technologies.Transportation System Management, Inter-technology Economies, Freeway Service Patrol, Changeable Message Signs, Ramp Metering, Intelligent Transportation Systems, Evaluation ,

Mathematical Model and Cloud Computing of Road Network Operations under Non-Recurrent Events

Optimal traffic control under incident-driven congestion is crucial for road safety and maintaining network performance. Over the last decade, prediction and simulation of road traffic play important roles in network operation. This dissertation focuses on development of a machine learning-based prediction model, a stochastic cell transmission model (CTM), and an optimisation model. Numerical studies were performed to evaluate the proposed models. The results indicate that proposed models are helpful for road management during road incidents

Evaluation of the efficiency of mainline and ramp metering in highway traffic management

Text in English; Abstract: English and TurkishIncludes bibliographical references (leaves 70-72)xi, 72 leavesIn the study, the effects of the mainline and ramp control theories on the highway traffic flow are investigate. In order to eliminate to alleviate the traffic congestion problem, which has become a problem in high-population cities, the mainline and ramp controls are considered as a solution, and control networks are emphasized. Examples of applications and results in the world are given. The applicability of the methods to be used by examining the previous studies was first examined on a general model and then on a selected highway network. In the models prepared, vehicle speeds, travel times, flow (volume) concepts, and relationships between them are mentioned. In addition, general information about highway management was also provided before. Control models were examined with the Microscopic Simulation Program, the purpose and types of models applied were compared. The traffic simulation model of the region between K-8 and K-11 on the O-2 highway from Asia to Europe has been created and the effects created by the control have been examined by applying both ramp and mainline metering. Analysis results; It has been observed that the control of ramp and mainline scenarios provides benefits compared to uncontrolled situations. Among the benefits provided; when the analysis of the basic model and mainline metering is applied, it is seen that there is an increase of 20.76% in travel times and an increase of 19.78% in vehicle speeds. Nevertheless, the implications of these control scenarios should be thoroughly investigated. Simulation results show that Ramp Metering (RM) and Mainline Metering (MM) controls can be an effective method in the management of highway-highway connections. In this regard, it is recommended that the control strategies mentioned in intensive highway-to-highway participations be tested in real life in order to increase efficiency.Hazırlanan çalışmada ana yol ve katılım kontrol teorilerinin otoyol trafik akımı üzerindeki etkileri araştırılmıştır. Yüksek nüfuslu şehirlerde bir problem haline gelen trafik tıkanıklığı sorunu, geçiş sırasında oluşan tıkanıklığın ortadan kaldırılması ya da hafifletilmesi amacıyla ana yol ve katılım kontrolleri bir çözüm olarak görülmekte olup kontrol şebekeleri üzerinde durulmuştur. Dünyadaki uygulamalar ve sonuçlarından örnekler verilmiştir. Önceki çalışmalar incelenerek kullanılacak metotların uygulanabilirliği öncelikle genel bir model üzerinde sonrasında da seçilmiş bir otoyol ağı üzerinden uygulanarak incelenmiştir. Hazırlanan modellerde yol ağı ile ilgili araç hızlarına, seyahat sürelerine, akım (hacim) kavramlarına ve aralarındaki ilişkilere değinilmiştir. Ayrıca otoyol yönetimi ile ilgili genel bilgiler de öncesinde sunulmuştur. Kontrol modelleri Mikroskobik Simülasyon Programı ile incelenmiş, amacı, uygulanan model çeşitleri kıyaslamalı olarak anlatılmıştır. Asya Avrupa yönünde O-2 otoyolunda K-8 ile K-11 arasında kalan bölgenin trafik benzetim modeli oluşturulmuş ve hem katılım hem de ana yol kontrolü uygulaması yapılarak, kontrolün yarattığı etkiler incelenmiştir. Analiz sonuçları katılım ve ana yol senaryolarının kontrolünün, kontrolsüz durumlara göre fayda sağladığı görülmüştür. Sağlanan faydalar arasında temel model ve ana yol kontrolünün uygulandığı analizler karşılaştırıldığında; ana yol kontrolünün seyahat sürelerinde % 20,76 kazanç ve araç hızlarında ki % 19,78'lik yükseliş sağladığı görülmektedir. Bununla birlikte, bahsi geçen kontrol senaryoları uygulandığında doğuracağı sonuçlar kapsamlı bir şekilde araştırılmalıdır. Yapılan simülasyon sonuçları katılım (RM) ve anayol (MM) kontrollerinin Otoyol-otoyol bağlantılarının yönetiminde etkili bir yöntem olabileceğini göstermektedir. Bu doğrultuda, verimlilik artışı sağlamak üzere yoğun otoyol-otoyol katılımlarında bahsi geçen kontrol stratejilerinin etkinliğinin gerçek hayatta da sınanması önerilmektedir