Lane lane departure system on real-time based firmware

detection is an essential component of heavy vehicle management system. Many
different approaches have been proposed till today by researchers but still it
is a challenging task to correctly detect the road lanes in various
environmental conditions. The main purpose of the system is to detect the lane
departure of heavy vehicle such as Trucks, Bus etc., and monitor their every
movement and notify them if they are breaking any law & upload their data
on a webpage. The secondary purpose of these projects is this to avoid
accidents & provide safety to the people. Within the last few years, studies
on Advanced Driver Assistance Systems (ADAS) have been actively conducted and
deployed in modern vehicles; moreover, lane detection and departure warning
systems are important modules of ADAS. The algorithm was designed with speed
and simplicity in mind. It assumes a flat, dark roadway with light colored lane
markers, either solid or dashed, painted on it. This algorithm is based on
finding significant ‘bright’ regions from the image plane and fitting functions
to those identified points which are consistent with the qualitative properties
of roadway lanes and ground to image plane geometric relationships. It
estimates a virtual lane centerline using left and right lane markers if both
are available, otherwise it uses whichever lane marker is visible and a rough
estimate of the lane width.Heavy vehicle management systems are
expected to improve safety & traffic congestion on the roads. In the
present paper, we proposed the design of a handheld real-time lane departure
warning system in combination with auto-taxation system & vehicle
monitoring. Such a device can be used on every road vehicle and dramatically
improve safety. In order to attain our goal, we adopted the technology of
embedded systems. In recent years, the enhancement of embedded calculating
technology has allowed the performance of embedded systems to gain enough
capability to carry out the huge calculations for lane departure warning algorithms
& also with the advancement in wireless sensor networks we will be able to
inform the government sites i.e. RTO website regarding any traffic rule
violation or traffic problems.

This project can be
taken to the next level by using GPS module & Artificial intelligence for
efficient navigation system, using lane departure system on real-time based
firmware & connecting this system with safety features of the vehicle i.e.
if the vehicle is crossing lane in certain safety parameter then it is n ok or
else it is on the way to crash crossing the lane inexplicitly making the AI in
the car to take control of car. It can also be clubbed with a system for
detecting if the driver has been consuming alcohol or not, if yes then the car
will not start.The design is
motivated by the discontinuous availability of valid preview data from the
sensing systems during lane-to-lane transitions for heavy vehicle. The task is
accomplished by the generation of a virtual yaw reference and the utilization
of a robust switching controller to generate steering commands that cause the
vehicle to track that reference. In this way, the open loop lane change problem
is converted into an equivalent virtual reference trajectory tracking problem.
The approach considers optimality in elapsed time at an operating longitudinal
velocity. Although the analysis is performed assuming that the road is
straight, the generalization of the proposed algorithm to arbitrary road
segments is rather straightforward.   Basic idea: ·        
An Embedded system attached on
heavy vehicle such as bus, trucks etc. which monitors there every movement.·        
If that vehicle crosses its
defined lane for more than a certain allotted period of time then the system
must automatically charge the driver with fine.·        
This requires direct linking
with the RTO web portal & database.·        
With this there will also be a
warning given to the driver that he is in wrong lane or entering the wrong lane.

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This system will be used with
other interconnected system for proper order and management of traffic in
orderly fashion.With the random traffic congestion caused by the
drivers in the swift crossing of lane & overtaking the fellow forward
vehicle sometimes end up in creating a roadblock which leads to public
disappointment & chaos. Traffic congestion has become a significant
impediment to the quality of life in urban areas. This traffic is basically
caused because of vehicle crossing their allotted lane & entering others
lane & disturbing the whole traffic system. This is most often seen with
heavy trucks, trailer crossing their allotted lane. This can be maintained by
implementing Heavy Vehicle management auto taxation system. To improve the
quality & safety of a person life this system can prove to be fruitful.  Current Statistics;Crash which occurs due to lane departures can be among the deadliest
collisions. In recent years, nearly 13,000 people died in single-vehicle
run-off-road, head-on, and sideswipe crashes where a passenger vehicle left the
lane unintentionally. Technology designed to help drivers avoid  lane departures can prevent these crashes.
Other technologies aim to keep drivers from drifting out of lanes, either by
providing warnings or steering corrections when they cross a lane line without
signaling or by actively centering them within their lanes. Lane departure
warning (LDW) initially became available in the United StatesOf America on the
Infiniti FX35 in model year 2005 and is becoming increasingly available on new
passenger vehicles. In the previous year, lane departure warning was available
on 63 % of new U.S. passenger vehicle series as standard (6 percent) or
optional (57 percent) equipment.       Technology solution:As per the requirement of the project & high  processing time it is proposed to use ARM
Cortex-M0+ processor i.e. FRDMKL25Z board develop. The FRDMKL25Z is been
provided with accelerometer MMA8451Q which is used along with IR sensor. The
output of both the channels will be clubbed together & based on the pattern
output will be decided. The use of camera makes the system complicated&
use of ARM cortex M0+ with camera makes the system inefficient at that point we
will require high power processor or some other support end processor for the
system to work efficiently Using camera make designing of system accurate but the
cost & programming a DSP & applying canny edge filter for getting the
road edges increases the cost of the system. The whole purpose of this system
is that if the vehicle crosses the lane for beyond a certain limit, it’s
activities will be recorded as he crosses the lane & it will be notified to
the RTO server & base on that the vehicle will be charged.The data of crossing the lane will be recorded using
accelerometer & IR sensor, there will be a delay of few minutes for the
vehicle to make an overtake by crossing the lane, if the vehicle is in the
unauthorized lane then it will be charged also while crossing the lane the
driver will be informed about it through led or buzzer. The data can be made to
be stored in the memory which can be checked at every checkpoint making the
task too tedious or else we can use ZigBee, WSN, NRF, etc. The data can be updated
on think speak website where you can get a free channel in the range of 2.4Ghz
for ZigBee& NRF.  According to pre-requisite posed by the problem
statement the system can also be developed by varied of controllers using node
MCU, Xilinx dsp. Using Node mcu make it a better choice as it has inbuilt esp
chip making it easy for transferring of recorded data over a web portal. Xilinx
controller is digital signal processor which makes it an integral part of
camera sensing system where it can be programmed logically using field
programmable gate array   Using raspberry pi makes the system smart enough for
inter-car communication and relaying the traffic data over the web portal as
well as adjacent cars. This system using raspberry pi is not much preferred as
it works only in compatibility with camera unit making the system costlier.
Using Node MCU and ARM cortex makes the system desirable 

is a platform for Kinetic L Series KL1x (KL14/15) and KL2x (KL24/25) MCUs built
on ARM® Cortex™-M0+ processor. 

Easy access to
MCU I/O, battery-ready, low-power operation, a standard-based form factor
with expansion board options and a built-in debug interface for flash
programming and run-control. 
is supported in the m-bed platform, so the controller gets accessible to
the SDK and free tools that provides experienced embedded developers with
productive and powerful tools for building proof of concepts.
The controller
is integrated with esp chip for inter-communication between the modules
depicting the density of traffic in a region.

MKL25Z128VLK4 in an 80 LQFP package
Capacitive touch slider
MMA8451Q accelerometer
Tri-colour (RGB) LED
coin cell battery, external source
Battery-ready, power-measurement access points
Easy access to MCU I/O via ArduinoR3 compatible

programming interface ­with mass storage
Data logging application

The implementation of this system can be done in various ways as
mentioned below :
Vehicle State Estimation system: A set of sensors that would
periodically determine the speed, steering angle and road curvature of the
Camera Sensing system: Processes the raw images coming from the
camera and identifies the lane marker.
Piezoelectric Sensor: It will sense the potential difference
generated based on the weight of the vehicle.
Lane departure warning alerts
the driver that your car is about to veer out of lane and warns you to get back
into lane. That’s the basic idea, but there are several versions of the
technology available now, including ones that react and steer away from the
lane edge and even keeping the car centered.  All types of lane departure
warning consist of a low-cost system which will have a camera attached in the
windshield near the rear view mirror which continuously monitor the different
types of lane markings of the road ahead.


One should always be alert when the system starts. This is
make-or-break stuff when it comes to driver satisfaction.

speed engage. Lane
departure warning kicks in between 30 mph and 40 mph or the rough metric equivalent,
50-65 kmph. This system isn’t meant for low-speed, stop-and-go driving, partly
because the camera cannot see enough lane markings.

warning: Some
cars will produce sound warning beeps when the car crosses a solid or dotted
lane marking, then the warning will silences itself once it’s away from the
lane edge.

feedback warning: Other cars vibrate the steering wheel or seat cushion. The vibration
the car makes when it’s on, say rough or gravel-covered road, or when the
anti-lock brakes engage. Seat cushion feedback may vibrate the left or right
side, to direct your attention to the offending side of the car.

Mainly speaking, Asian cars are more likely to use audible
warnings, European cars are more likely to use haptic feedback, and American
cars may use either of the above two (but not both on the same car). Audible
versus haptic isn’t really an option. You decide if one or the other is so
important you’ll end up abandoning one brand for another.

feedback: Every car
will show a visual indicator that the car is drifting out of the specified allotted
lane. It’s a pair of striped lane markings, with a car in the middle, mainly
yellow or green lines when LDW is active and everything is well but red or
flashing, on the other side of the lane. In most cars, the instrument panel
indicator isn’t big enough to get the driver’s attention in a hurry, thus the
need for audible or haptic feedback is necessary. Some cars are now putting
lane departure warning icons in the head up display, where it’s more likely to
noticed and clearly visible

versus late warning: Some of the system will let you choose whether the alert and/or
lane correction happens before the car reaches the lane marking, or  if its on the lane marking, or once the car
has gone over. The early alert will sounds safest, but it also means more
alerts which will indicate that you haven’t been paying attention.

audible warning levels: Some system will let you adjust the loudness of the warning. But passengers
who don’t like audible warnings will be less annoyed with softer beeps.


It will help in lane management
and hence will avoid accidents and traffic congestion .It will help monitoring
the vehicle movements Accurate position of vehicle is
not possible. Difficult in

The purpose of this project is to make heavy vehicle follow their
allotted lanes in order to avoid traffic congestion and accidents. With the
help of this project we can monitor the movements of heavy vehicle and notify
them if they are breaking any law and upload the data on the RTO portal

Till now we have been successful in implementing the
accelerometer part of the project for distance measurement. If the car crosses
a range of meters within in a short period then he will be notified about it
through led present on the FRDM board. Combining the output from IR sensor for
identification of lane. The lane departure warning part of this project is almost


                For developing a smart city every system needs to be
interconnected & integrated. This system can be later on combined with
other modules of the smart city and can prove its significance by assisting the
driver and the traffic data for the proper traffic management of the city.



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