Report on Traffic Flow Forecasting, as One of the important component of the intelligent transportation system.

Pratiksha Narayan Autade, Krishna T Mdrewar


The interest in smart transportation vehicles stems from the integration of new information sy
stems on the problems caused by traffic accidents and the simulation of realtime real and com
munication. Traffic is increasing worldwide due to driving, urbanization, population growth a
nd rapid population change. Congestion reduces the efficiency of transportation and increases
 travel time, air pollution and fuel consumption. Now the development of the road has caused 
new disasters, caused more accidents around the world, smart transportation is a good choice 
to overcome such problems. Smart transportation is designed for city/state/private road transp
ortation organization.
According to the backend and hardware components, the system offers solutions for the drive
r console unit, electronic ticketing machine, passenger information system and vehicle arrival
 system. Intelligent Transportation Systems offers transportation companies a solution for bus
 dispatch and tracking with the help of technologies such as GPS, WiFi and GPRS. Smart tran
sport supports better public transport services, keeping transport revenue, public safety and se
curity in mind. This article mainly discusses the impact of ITS on traffic and various applicati
on areas. In addition, the document highlights the use of vehicle tracking and technology that 
can make our rides safer, designed and cheaper, as well as the use of various forms of transpo
rtation important to national security.



Full Text:

 Subscribers Only


Chennai Metropolitan Development Administration; Chennai Metropolitan Area Master Pla

n Draft II, Tsoom Fwv. Tamil Nadu, Is Nrias teb, 2008.

World Bank India, Development Dialogue; Infrastructure Spending Boosts Growth, World

Bank India Bulletin, New Delhi, India, 2009.

J. Levine, S. E. under wood; MultiAttribute Analysis of Intelligent Transportation System P

lanning Goals, Transpn Res.-C., Cilt. 4(2), s. 101-1 101-197-111, 1996.

MA Chowdhury, A. Sadek; Planning Fundamentals for Intelligent Transport Systems, Artec

h House, London, 2003.

Intelligent Transportation System standards program strategic plan for 2o1 1- 14" by

B.Christie,Ann D.,San G., Suzanne s. , R.I.T.A., US Dept. of Transportation (FHWA-JPO-1 1-052), page


L. Weston, V. Tshitoyan, J. Dagdelen, O. Kononova, A. Trewartha, et al., Named entity recognition

and normalization applied to large-scale information extraction from the materials science literature,

J. Chem. Inf. Model. 59 (9) (2019) 3692–3702.

G. Savino, R. Lot, M. Massaro, M. Rizzi, I. Symeonidis, S. Will, J. Brown, Active safety system for

powered two wheelers: a systematic review, J. Traf. Injury Prev. 21 (1) (2020) 78–86

N.J. Eck, J. Waltman, Bibliometric mapping of the computational intelligence field, Int. J.

Uncertain. Fuzziness Knowledge-Based Syst. 15 (5) (2007) 625–645.

O. Grembek, A. Kurzhanskiy, A. Medury, P. Varaiya, M. Yu, Making intersections safer with I2V

communication, Transport. Res. C Emerg. Technol. 102 (2019) 396–410

H. Askari, A. Khajepour, M.B. Khamesee, Z.L. Wang, Embedded self-powered sensing systems for

smart vehicles and intelligent transportation, Nano Energy 66 (2019) 104103.



  • There are currently no refbacks.