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Author: Hamad Bader Almobayedh Publisher: ISBN: Category : Autonomous vehicles Languages : en Pages : 118
Book Description
Intersections are locations with higher likelihood of crash occurences and sources of traffic congestion as they act as bottlenecks compared with other parts of the roadway networks. Consequently, connected and automated vehicles (CAVs) can help to improve the efficiency of the roadways by reducing traffic congestion and traffic delays. Since CAVs are expected to take control from drivers (human control) in making many important decisions, thus they are expected to minimize driver (human) errors in driving tasks. Therefore, CAVs potential benefits of eliminating driver error include an increase in safety (crash reduction), smooth vehicle flow to reduce emissions, and reduce congestion in all roadway networks. Since CAV implementations are currently in early stages, researchers have found that the use of traffic modeling and simulation can assist decision makers by quantifying the impact of increasing levels of CAVs, helping to identify the effect this will have on future transportation facilities. The main objective of the current study was to simulate the potential impacts CAVs may have on traffic flow and delay at a typical urban signalized intersection. Essentially, to use a microscopic traffic simulation software to test future CAV technology within a virtual environment, by testing different levels of CAVs with their associated behaviors across several scenarios simulated. This study tested and simulated the impact of CAVs compared with conventional vehicles at a signalized intersection. Specifically, I analyzed and compared the operations of the signalized intersection when there are only conventional vehicles, conventional vehicles mixed with CAVs, and when there are only CAVs. The most current PTV Vissim 11 software was used for simulating different percentages of three different types of CAVs and conventional vehicles in the traffic stream at the intersection. These are three different levels of automated vehicles that are already installed in PTV Vissim 11, which are AV cautious, AV normal, and AV all-knowing. All these automated vehicles were tested in different scenarios in this study. Real data from an existing signalized intersection in the city of Dayton, Ohio were used in the PTV Vissim software simulation. The traffic count data used in the Vissim intersection model were for morning peak hour. The existing signal timing data for the intersection used were first optimized using Synchro. The results from Vissim simulation show that CAVs could reduce the queue delay by about 12%, the stopped delay by about 17%, the vehicle travel time by about 17%, and the queue length by about 22%. Because of that, CAVs can substantially reduce congestion at urban signalized intersections.
Author: Hamad Bader Almobayedh Publisher: ISBN: Category : Autonomous vehicles Languages : en Pages : 118
Book Description
Intersections are locations with higher likelihood of crash occurences and sources of traffic congestion as they act as bottlenecks compared with other parts of the roadway networks. Consequently, connected and automated vehicles (CAVs) can help to improve the efficiency of the roadways by reducing traffic congestion and traffic delays. Since CAVs are expected to take control from drivers (human control) in making many important decisions, thus they are expected to minimize driver (human) errors in driving tasks. Therefore, CAVs potential benefits of eliminating driver error include an increase in safety (crash reduction), smooth vehicle flow to reduce emissions, and reduce congestion in all roadway networks. Since CAV implementations are currently in early stages, researchers have found that the use of traffic modeling and simulation can assist decision makers by quantifying the impact of increasing levels of CAVs, helping to identify the effect this will have on future transportation facilities. The main objective of the current study was to simulate the potential impacts CAVs may have on traffic flow and delay at a typical urban signalized intersection. Essentially, to use a microscopic traffic simulation software to test future CAV technology within a virtual environment, by testing different levels of CAVs with their associated behaviors across several scenarios simulated. This study tested and simulated the impact of CAVs compared with conventional vehicles at a signalized intersection. Specifically, I analyzed and compared the operations of the signalized intersection when there are only conventional vehicles, conventional vehicles mixed with CAVs, and when there are only CAVs. The most current PTV Vissim 11 software was used for simulating different percentages of three different types of CAVs and conventional vehicles in the traffic stream at the intersection. These are three different levels of automated vehicles that are already installed in PTV Vissim 11, which are AV cautious, AV normal, and AV all-knowing. All these automated vehicles were tested in different scenarios in this study. Real data from an existing signalized intersection in the city of Dayton, Ohio were used in the PTV Vissim software simulation. The traffic count data used in the Vissim intersection model were for morning peak hour. The existing signal timing data for the intersection used were first optimized using Synchro. The results from Vissim simulation show that CAVs could reduce the queue delay by about 12%, the stopped delay by about 17%, the vehicle travel time by about 17%, and the queue length by about 22%. Because of that, CAVs can substantially reduce congestion at urban signalized intersections.
Author: Abdullah Baz Publisher: ISBN: Category : Autonomous vehicles Languages : en Pages : 98
Book Description
One of the most critical subjects in Intelligent Transportation System (ITS) nowadays is the autonomous vehicle (AV). It is rapidly improving, and it will have a substantial positive effect on traffic safety and efficiency. Most of auto manufacturer companies and tech industries are spending a lot of money on research for developing autonomous vehicles. AV would have an excellent contribution to managing and controlling intersections. This study introduces a decision-making algorithm for autonomous vehicles at an intersection to optimize the intersection capacity and minimize delay time by using Game Theory mathematical models. This model using vehicle-to-infrastructure (V2I) communication features that will be available in AV so that vehicles are able to communicate with roadside unit (RSU) and with each other to determine which one goes first, depending on different factors such as their speeds and locations, and vehicle size, taking in consideration the safety of the vehicles so we can have collision free intersection. Two different mathematical models were developed; one with %100 autonomous vehicles and the other one is when we have mix traffic, autonomous vehicles, and ordinary vehicles. A simulation model was developed using a standard microscopic simulation platform VISSIM to implement this algorithm. A comparison of the proposed method and two other ordinary intersection control method; traffic lights, and roundabout was made to calculate the total delay of the intersection for each intersection management method. The simulation ran on three different traffic volume, High, moderate, and low volume. Moreover, three different speeds for each traffic volume. The results shows that the proposed system reduces the total delay by more than 65 percent compared with the roundabout, and about 85 percent comparing with a signalized intersection. Another simulation was done for the second scenario, mixed traffic, also a comparison between the proposed methods; roundabout, and the signalized intersection was made for the same cases of various speeds and volume. For model two, results show 30% reduction in delay compared to the roundabout and 89% compared to signalized intersections.
Author: Lipika Deka Publisher: Elsevier ISBN: 0128142960 Category : Transportation Languages : en Pages : 350
Book Description
Transportation Cyber-Physical Systems provides current and future researchers, developers and practitioners with the latest thinking on the emerging interdisciplinary field of Transportation Cyber Physical Systems (TCPS). The book focuses on enhancing efficiency, reducing environmental stress, and meeting societal demands across the continually growing air, water and land transportation needs of both people and goods. Users will find a valuable resource that helps accelerate the research and development of transportation and mobility CPS-driven innovation for the security, reliability and stability of society at-large. The book integrates ideas from Transport and CPS experts and visionaries, consolidating the latest thinking on the topic. As cars, traffic lights and the built environment are becoming connected and augmented with embedded intelligence, it is important to understand how smart ecosystems that encompass hardware, software, and physical components can help sense the changing state of the real world. - Bridges the gap between the transportation, CPS and civil engineering communities - Includes numerous examples of practical applications that show how diverse technologies and topics are integrated in practice - Examines timely, state-of-the-art topics, such as big data analytics, privacy, cybersecurity and smart cities - Shows how TCPS can be developed and deployed, along with its associated challenges - Includes pedagogical aids, such as Illustrations of application scenarios, architecture details, tables describing available methods and tools, chapter objectives, and a glossary - Contains international contributions from academia, government and industry
Author: Rahul Anuj Patel Publisher: ISBN: Category : Languages : en Pages : 110
Book Description
Connected and autonomous vehicle (CAV) technologies can revolutionize the way we transport people and goods and may soon be publicly available, however proper planning for these technologies is crucial to their successful integration into our transportation systems. CAVs can reduce following headways and increase roadway capacity and stability, as well as allow for new, more efficient intersection controls with wireless communication capabilities. This work is twofold: (1) evaluating the traffic congestion impacts of AVs and reservation-based intersection control on real large-scale city networks in Texas using DTA and (2) developing methods to find optimal configurations of reservations and signals in a city network. The first part of this thesis evaluates CAV behavior impacts by simulating different mixed CAV and human vehicle (HV) demand scenarios. Results show improvements in network efficiency with increases in CAV penetration. Reservations were observed to perform better than signals in most scenarios. Namely, the Austin downtown network resulted in a 78% reduction in travel time. However, signals outperformed reservations in some high demand cases on arterial networks due to the reservation's first-come-first-serve (FCFS) policy allocating more capacity to local roads, resulting in arterial progression interruption and queue spillback onto close-proximity streets. The discovered paradoxical effects imply that some intersections are better suited for reservation control than others. The second part of this thesis finds and characterizes favorable mixed-configurations of reservation-based controls and signalized controls in a large city network which minimize total system travel times. As this optimization problem is bi-level and challenging, we propose three different methods to heuristically find effective mixed-configurations. The first method is an intersection ranking method uses simulation to assign a score to each intersection in a network based on localized potential benefit to system travel time under reservation control and then ranks all intersections accordingly. The second is another ranking method, however uses linear regression to predict an intersection's localized score. Finally, we present a genetic algorithm which iteratively approaches high-performing network configurations yielding minimal system travel times. We test the methods on the downtown Austin network and find configurations which are less than half controlled by reservation intersections that improve travel times beyond an all-reservation controlled network. Overall, our results show that the genetic algorithm finds the best performing configurations with the initial score-assigning ranking method performing similarly but much more efficiently. We finally find that favorable reservation placement is in consecutive chains along highly trafficked corridors
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Abstract : Connected and Automated Vehicles (CAVs) coupled with Intelligent Transportation Systems (ITS) have been able to impact significantly to the transportation and automotive sector by improving traffic mobility, increasing fuel efficiency and reducing emissions. The research intends to develop optimization algorithms by utilizing the velocity bounds provided by a traffic simulation program and generate an optimal velocity trajectory to reduce power-losses and improve drivability in vehicles. The developed optimal velocity trajectory algorithms are modified for the applications of Eco -Approach and Departure (Eco A/D) at signalized intersections and Co-operative Adaptive Cruise Control (CACC). The fuel consumption during Eco-A/D is minimized by reducing idling times at traffic intersections. The CACC algorithm allows vehicles in a platoon to maintain a closer inter-vehicular gap and improve the efficiency of the platoon. Lastly, the simulation results generated by test cases are presented and future work is discussed to translate the simulation-based results to real-world improvement.
Author: Nikolas Thomopoulos Publisher: Emerald Group Publishing ISBN: 1803823496 Category : Transportation Languages : en Pages : 220
Book Description
This volume is a valuable source of ACT information for developing holistic research methods and global policies for making progress towards the SDGs.
Author: Mahmoud Faraj Publisher: ISBN: Category : Autonomous vehicles Languages : en Pages : 110
Book Description
Road congestion in urban environments, especially near signalized intersections, has been a major cause of significant fuel and time waste. Various solutions have been proposed to solve the problem of increasing idling times and number of stops of vehicles at signalized intersections, ranging from infrastructure-based techniques, such as dynamic traffic light control systems, to vehicle-based techniques that rely on optimal speed computation. However, all of the vehicle-based solutions introduced to solve the problem have approached the problem from a single vehicle point of view. Speed optimization for vehicles approaching a traffic light is an individual decision-making process governed by the actions/decisions of the other vehicles sharing the same traffic light. Since the optimization of other vehicles' speed decisions is not taken into consideration, vehicles selfishly compete over the available green light; as a result, some of them experience unnecessary delay which may lead to increasing congestion. In addition, the integration of dynamic traffic light control system with vehicle speed optimization such that coordination and cooperation between the traffic light and vehicles themselves has not yet been addressed. As a step toward technological solutions to popularize the use of autonomous vehicles, this thesis introduces a game theoretic-based cooperative speed optimization framework to minimize the idling times and number of stops of vehicles at signalized intersections. This framework consists of three modules to cover issues of autonomous vehicle individual speed optimization, information acquisition and conflict recognition, and cooperative speed decision making. It relies on a linear programming optimization technique and game theory to allow autonomous vehicles heading toward a traffic light cooperate and agree on certain speed actions such that the average idling times and number of stops are minimized. In addition, the concept of bargaining in game theory is introduced to allow autonomous vehicles trade their right of passing the traffic light with less or without any stops. Furthermore, a dynamic traffic light control system is introduced to allow the cooperative autonomous vehicles cooperate and coordinate with the traffic light to further minimize their idling times and number of stops. Simulation has been conducted in MATLAB to test and validate the proposed framework under various traffic conditions and results are reported showing significant reductions of average idling times and number of stops for vehicles using the proposed framework as compared to a non-cooperative speed optimization algorithm. Moreover, a platoon-based autonomous vehicle speed optimization scheme is posed to minimize the average idling times and number of stops for autonomous vehicles connected in platoons. This platoon-based scheme consists of a linear programming optimization technique and intelligent vehicle decision-making algorithm to allow vehicles connected in a platoon and approaching a signalized intersection decide in a decentralized manner whether it is efficient to be part of the platoon or not. Simulation has been conducted in MATLAB to investigate the performance of this platoon-based scheme under various traffic conditions and results are reported, showing that vehicles using the proposed scheme achieve lower average values of idling times and number of stops as compared to two other platoon scenarios.
Author: Tariq Rahim Rahimi Publisher: ISBN: Category : Automated vehicles Languages : en Pages : 102
Book Description
This research is an introduction to the topic of simulating vehicles capable of being connected with the infrastructure. The connectivity helps vehicles make better decisions and improves the general traffic flow. It is built around SUMO, an open source traffic simulation software developed by German Aerospace Center (DLR) of traffic studies. Three different scenarios of an urban intersection are simulated. First, an isolated intersection with current traditional traffic is simulated. Then, a camera connected with traffic light is simulated as a form of infrastructure to vehicle connectivity. The camera detects the vehicles in a specific distance from the stop line and adapts the traffic lights in order for the vehicles to pass the intersection safely. Third scenario is where vehicles are given some characteristics of autonomous and connected vehicles sporting less gap between each other, near perfect driving, and faster perception-reaction time. The main goal of our work is to be able to simulate how vehicles with some sort of connectivity impact traffic flow. We used the output from the fixed scenario as our base and compared the numbers we got from the second and third scenarios. We found out that the second scenario yields a better traffic flow with lesser delay and queue length. Moreover, the third scenario had cut more than half of the delay and queue length. In this study, we took an urban intersection and used it as an isolated one. We think if three parameters can have this much effect on traffic flow, having a fully connected and autonomous vehicle will have a larger effect on reducing collisions and congestions. My professor, colleagues and I are planning to do further studies of different intersections and roadways and evaluate its applicability.
Author: Hamad Bader Almobayedh
Author: Hamad Bader Almobayedh
Author: 林亦琴
Author: Abdullah Baz
Author: Christian Claudel
Author: Lipika Deka
Author: Rahul Anuj Patel
Author: 
Author: Nikolas Thomopoulos
Author: Mahmoud Faraj
Author: Tariq Rahim Rahimi