Chapter 7.2: Semi-Autonomous Intelligent Transportation System
Key Contributions
- The approach presents an integrated study of an intelligent transportation system covering all the various concepts which are separately studied in the literature.
- The study proposes architecture of the transportation systems of the future covering both decentralized vehicle control and a centralized management control.
- The approach is designed for diverse semi-autonomous vehicles operating in a scalable environment, which is the likely future of the transportation system.
- The approach is a positive step towards creation of a traffic simulation tool for diverse and unorganized traffic.
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Chapter 7.3: Congestion Avoidance in City Traffic
Key Contributions
- Proposing city traffic as a scenario to study traffic congestion.
- Proposing the importance of considering traffic lights in decision making regarding routes.
- Proposing a simple routing algorithm that eliminates the high density of traffic and hence minimizes congestion.
- Stressing frequent short term re-planning of the vehicle in place of long term (complete) infrequent re-planning.
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Chapter 8.2-8.3: Reaching Destination before Deadline with Intelligent Transportation Systems
Key Contributions
- Decentralized agents at the intersections are proposed which record the traffic speeds and variations along with time. The use of centralized agents (or single agent systems) for such an approach is common, which is however not a scalable approach. The use of decentralized agents for traffic speeds is also common. Here recording an extra deviation factor helps in answering the user query.
- A new problem of start time prediction is studied, where a user may adapt the algorithm based on the penalty of late arrival. A single factor governs the performance. Guidelines enable a user to set the parameter.
- Using the existent notion of advanced driver information system, the twin problems of start time prediction and routing are solved.
- A graph search method is proposed to compute the route and the start time for the vehicle. The algorithm attempts to select a route which is the shortest in length, has a high reliability and gives the latest starting time.
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Chapter 8.4-8.5: Reaching Destination before Deadline with Cooperative Intelligent Transportation Systems
Key Contributions
- The notion of cooperative traffic lights is introduced which is biased to allow vehicles which are running late to pass through.
- The concept of cooperative lane changes is introduced by which a lane change attempts to minimize some vehicle from running late.
- Different states of a vehicle which desires to be on time are designed which include being comfortable on time, running a little late (may still reach even without cooperation), running very late (difficult to reach without cooperation) and impossible to reach (given up).
- A cost metric is designed which maps the different states of a vehicle running late to a consciousness of being late, used for decision making regarding all cooperative measures.
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In-Page Links
- Intelligent Management of the Transportation System
- Quick Links
- Chapter 7.2: Semi-Autonomous Intelligent Transportation System
- Chapter 7.3: Congestion Avoidance in City Traffic
- Chapter 8.2-8.3: Reaching Destination before Deadline with Intelligent Transportation Systems
- Chapter 8.4-8.5: Reaching Destination before Deadline with Cooperative Intelligent Transportation Systems
- Continue to Series Home
Whats New
- Inauguration of the Centre of Intelligent Robotics from 2nd to 3rd January, 2020
- Paper presented at CICT 2019 at IIIT Allahabad. The paper is a part of the ASEAN funded project.
- 2 Papers presented at IEEE CEC Wellington are available online.
- Paper at Computational Intelligence published in an issue.
- Hosted Teun Mentzel at IIIT Allahabad for framing the incubation program NewGen IEDC
- Hosted the first advisory board meeting of the NewGen IEDC incubation project
- Delivered a talk at IEEE CIS Summer School at IIIT Allahabad
- Visited UBL Jakarta under the ASEAN project scheme. Delivered talks at multiple venues.
- Delivered talks on Artificial Intelligence at GAT Bangalore
- Participated and presented 2 papers at the IEEE CEC 2019