Industrial Consultancy & Sponsored Research (IC&SR) , IIT Madras
Technology Category/ Market
Category –Automotive
Applications – Transport systems, Automation, Automobiles
Industry –Automotive/ Transportation Systems
Market -The global intelligent transportation system market is projected to grow from $22.91 billion in 2021 to $42.80 billion in 2028, at a CAGR of 9.34%
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Problem Statement
- Existing technologies fall short in accurately predicting arrival times due to their inability to handle the dynamic and complex nature of heterogenous traffic.
- Key issues include traffic variability, diverse modes of transportation, loss of GPS/GPRS data, detours etc.
- Hence, there is a need for an advanced system for traffic pattern analysis and arrival time prediction that can overcome the limitations and challenges posed by the existing technologies and patents.
Technology
The system includes:
- Vehicle monitoring unit (VMU)
- Data filtering and storing unit (DFSU)
- Computational module
- A vehicle monitoring unit (VMU) adapted to receive and store the data of the vehicle which includes ateast a GPS sensor module and a GPRS module
- Data filtering and storing unit (DFSU) adapted to store the trajectory data of VMU in a retrievable format where the trip length is divided into multiple sections and data of vehicles section wise is stored as cluster data
A computational module has three modules:
- A real-time Vehicle status (RVSM) module adapted to receive, store and process vehicle trajectory data received from VMU and DFSU, .
- A nearest neighbor Search (NNS) module adapted to determine a cluster-set data using the processed data received from RVSM & to identify the cluster set, whose cluster data from DFSU matches the current vehicle trajectory data of a specific section of the trip length and also plurality of previous sections of the trip length
- A travel time prediction (TTP) module adapted to predict travel time using processed data from RVSM and cluster set data from NNS.
The Method involves:
- Storing Information-stores information representing prior travel-patterns of a plurality of vehicles.
- Determining Arrival Time-The system determines the arrival time at the destination based on data from DFSU at the commencement of travel.
- Receiving Information-The system receives information in a vehicle monitoring unit (VMU) data as trajectory data with a GPS sensor module and a GPRS module.
- Real-Time Section Wise Trajectory Data-The system receives real-time section wise trajectory data representing a cluster data of the current travel
- Calculating Travel Time-calculates the travel time based on the received real-time cluster data.
Key Features/ Value Proposition
Technical Perspective:
- Discloses a system mountable on vehicles for predicting trip travel time of the vehicles from an origin to a destination of each vehicle
- The said system intelligently identifies the overtaking of the buses to give the correct next bus and its arrival time information to the passenger at the location of interest.
User Perspective:
- Efficient system that directs operator in real time, speeds with which the vehicle is moving as well as the driving characteristics of the driver such as acceleration and deceleration.
- The system provides alert about arrivals, speed violations, bunching, and route deviation and navigate for dynamic routing and scheduling of buses and can be for all types of vehicles such as taxi, para-transit, emergency vehicles etc.
Questions about this Technology?
Contact for Licensing
sm-marketing@imail.iitm.ac.in
ipoffice2@iitm.ac.in
Research Lab
Prof. LELITHA DEVI V
Prof. SHANKAR RAM C S
Department of Civil Engineering
Intellectual Property
- IITM IDF Ref. 1207
- IN409992-Granted
Technology Readiness Level
TRL-5
Technology Validateed in relevant Environment