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3. Departure Time Planner using V2V and V2I Communication

Travel time information helps commuters plan their travel efficiently. They will be able to make decisions on what route to take, what mode to take, what time to start the journey, etc. It also helps transportation agencies understand the spatiotemporal evolution of traffic conditions on the road network. However, obtaining travel time information is not trivial and has not been explored sufficiently for heterogeneous conditions. Towards addressing this issue, the present project proposes to use Dedicated Short-Range Communication (DSRC) devices and the Wi-Fi sensors to gather continuous spatiotemporal traffic stream data, develop a traffic state estimation and prediction methodology, and finally develop a departure time planner application. Towards achieving this goal, the following objectives are envisioned: 

  • Design and develop applications to integrate Wi-Fi sensors with DSRC devices
  • Develop an application for real-time data collection and communication from DSRC devices to the storage server
  • Develop traffic state estimation methodology for corridors, incorporating the spatiotemporal data
  • Develop corridor-level state prediction methodology using advanced traffic flow models and theory
  • Develop a departure time planner based on the predictions made in the earlier step
  • Knowledge creation and capacity building by providing platform to faculty, students (Masters & Ph.D) and professionals on field sensors, real-time data collection, and data analytics for departure time planner.

The project development will be done mainly by IIT Madras. C-DAC will help IIT M in instrumenting the vehicles by supplying the hardware and developing appropriate application for data collection. C-DAC will absorb the technology through continuous interaction with the IIT M project team and knowledge transfer program towards the end of the development.

Expected outcome

  • Application for integrating WiFi-based sensors with the C-DAC’s DSRC devices to collect and communicate (V2V and V2I) the continuous spatiotemporal traffic stream information
  • Empirical and theory supported approach to traffic state estimation and prediction using DSRC-based on sparse sensor instrumentation
  • Departure time planner algorithms utilizing the traffic state estimation and prediction methods

Industry connect

M/s. ITS Planners and Engineers Pvt. Ltd., Hyderabad has shown interest in the final solution being developed. IIT Madras has an agreement with MTC, Chennai, to instrument their buses for traffic data collection.

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Contact us

Section Head, Intelligent Transportation & Networking Section (ITNS)
Centre for Development of Advanced Computing (C-DAC) Thiruvananthapuram
Kerala - 695 033, Email:
Tel: +91 471 2726731, +91 471 2723333

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