数学建模社区-数学中国

标题: Traffic Prediction for Intelligent Transportation System using Machine Learning [打印本页]
作者: 杨利霞    时间: 2020-11-10 16:06
标题: Traffic Prediction for Intelligent Transportation System using Machine Learning
Traffific Prediction for Intelligent Transportation

3 F7 H9 F7 n, u) \; _0 b
System using Machine Learning

* z/ b% e  t' s7 @2 T* ^/ f/ b4 E6 R3 u. B

6 t+ e0 n# X# M% K
4 I) I  h: H0 W' G7 H- R* L- s/ \* l% J
This paper aims to develop a tool for predicting
0 `+ B" B& M! D5 e  @# Qaccurate and timely traffific flflow Information. Traffific Environment" p1 {$ w# y( M! m  {
involves everything that can affect the traffific flflowing on the* j1 Q1 {" a; A% V7 R; Z
road, whether it’s traffific signals, accidents, rallies, even repairing
! j! N% X. }) X- R% E2 k: _of roads that can cause a jam. If we have prior information. P( j7 N2 D! F  M- {/ ?
which is very near approximate about all the above and many) U3 }9 P  B) _
more daily life situations which can affect traffific then, a driver' x7 r* }! c$ I  C6 S8 H! }  q
or rider can make an informed decision. Also, it helps in the( @" E' |0 o: |% X) I
future of autonomous vehicles. In the current decades, traffific data
* {! f) ^5 v0 v3 yhave been generating exponentially, and we have moved towards
: C5 y& f6 \2 A4 I' _3 r' pthe big data concepts for transportation. Available prediction* T3 ?# Q. q& P' I3 m, j
methods for traffific flflow use some traffific prediction models and
5 s9 A1 K( {3 a7 P: A( Aare still unsatisfactory to handle real-world applications. This fact  v7 Y' x5 C9 }) V' {( v7 o
inspired us to work on the traffific flflow forecast problem build on
3 M5 Y& X  K& C. y* Y: ~the traffific data and models.It is cumbersome to forecast the traffific% y, y9 n1 a& @+ G
flflow accurately because the data available for the transportation6 N3 b$ F; Y& n5 Y
system is insanely huge. In this work, we planned to use machine, P& i6 j  B) v2 n4 K# R
learning, genetic, soft computing, and deep learning algorithms2 d# p2 j' d+ v
to analyse the big-data for the transportation system with- C$ i( W/ k4 e4 [2 y7 w' \$ p" `- x1 W
much-reduced complexity. Also, Image Processing algorithms are
8 l) u1 T+ A$ M' Q9 \. B% B6 Ginvolved in traffific sign recognition, which eventually helps for the
) ?1 r* c& s- y' nright training of autonomous vehicles.2 n4 V' c, f$ q) b, H
; q$ W5 V5 ~1 v" D
/ G* p9 e' |1 n/ x
  t+ }  g$ x2 f7 N7 o
# j# s+ e- Q/ ?# k4 b( H
- Y' n+ D" h( `6 r7 m

09091758.pdf

425.77 KB, 下载次数: 1, 下载积分: 体力 -2 点



欢迎光临 数学建模社区-数学中国 (http://www.madio.net/) Powered by Discuz! X2.5