Collision avoidance in Vehicular Networks using V2V-V2R communication By Avanti Chimote Charan Hebri...
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Transcript of Collision avoidance in Vehicular Networks using V2V-V2R communication By Avanti Chimote Charan Hebri...
Collision avoidance in Vehicular Networks using V2V-V2R communication
By
Avanti Chimote Charan Hebri
Kuppuraj GunasekaranSandeep N L
Saravanan Sathananda Manidas
Agenda Motivation for the Project Requirements of Collision Avoidance System Existing Approaches Proposed Architecture Work Flow in Detail Improving Vehicle to Roadside connectivity Collision Detection Mechanism Simulation Expected Results Future Work
Motivation• Stop sign and Intersection Violation
• Left or Right turn at Intersection crashes
Intersection Crash statistics
http://safety.transportation.org/htmlguides/freewaycrash/types_of_probs.htm
Requirements for Collision Avoidance System
Critical response time for Alerts Reliable data transfer Energy efficiency Accurate Speed Measurement Security
Integrity and Authenticity
Intersection Collision Avoidance using Wireless Sensor Network Jungsook Kim, Juwan Kim, IEEE, 2009
Existing approaches to Collision Avoidance
Vision based system Deploy Wireless sensor Network(WSN) on the
roads
-A Vision-Based Approach to Collision Prediction at Traffic IntersectionsStefan Atev, Hemanth Arumugam, Osama Masoud, Ravi Janardan, Senior Member, IEEE, and Nikolaos P. Papanikolopoulos, Senior Member, IEEE,2005
-Infrastructure Collision-Avoidance Concept for Straight-Crossing-Path Crashes at Signalized Intersections Robert A. Ferlis,2002
Existing approaches to Collision Avoidance
Co-operative Vehicle to Vehicle (V2V)
Enhancing VANET Connectivity Through Roadside Units on HighwaysSok-Ian Sou and Ozan K. Tonguz, Member, IEEE, 2011
Proposed System Architecture
•Combination of V2V and V2R approach•DSRC- Dedicated Short Range Communication
End to End Working• RSU connects with OBU by WSA (Wave Service Advertisement)
• Cars near Intersection connects RSU by Control CH
• Cars communicate with RSU by service channel
• Separate RSU for Control and Service channel depending on the arrival rate of the vehicles.
OBURSU
OBU
RSU
OBU
Intersection Collision Avoidance System Architecture ,Zaydoun Yahya Rawashdeh and Syed Masud Mahmud,IEEE,2008
CCHZSCHZ
State transition diagram
Vehicles connect to RSU by Control
Channel Vehicle enters Service Channel range
RSU adds vehicle to polling list to
query status
RSU sends polling message
OBU replies by sendingStatus message eg:
Velocity,position
Broadcast to otherVehicles by
RSU
RSU send itsStatus after Every T sec
RSU sends warning
Message to OBU for Collision
Proposed Architecture to improve Vehicle to RSU
connectivity
System Model• The Roadside Unit (RSU)
acts as WAVE providers that keep advertising their presence and the offered services through periodic broadcasts.
• WSA(Wave Service Advertisements)
Control information sent by the RSUs over CCHs
Improving V2R connectivity to provides ITS applications in IEEE 802.11p/ WAVE VANET’SClaudia Campolo, Antonella Molinaro, IEEE, 2011
System model Contd.
• WBSS(Wave-based Basic Service Set)
Set up after WSAs are sent
Data exchange over the SCHs can only occur after the vehicle successfully receives the WSA
• The signal strength of the RSU should be tuned to the network latency and the lane speed at that location, so as to not miss any vehicles coming in its range
• To relieve the RSU of too much computation and keep it real-time, the Vehicle is expected to send the GPS location using the DSRC Service Channel.
• This channel is exclusively reserved for the GPS data from vehicle and is informed of this and is tuned to sufficient bandwidth.
System model Contd.
• However, there are some concerns due to a separate channel dedicated like switching between channels can cause delay etc. which needs to be addressed
• So the RSU will now be receiving the location updates from the vehicles.
• Using this information the RSU will determine the nearest vehicle to the intersection.
• There are 2 methods to compute the distance of the vehicle from the intersection
1) Pairwise Computation method
2) Pairwise Computation using Historic data
System model Contd.• To avoid the shadowing effect sometimes when a larger
building or a larger vehicle shadows other vehicles, we use the mechanism of piggybacking the WAVE based parameters which would further reduce the communication gap between the Vehicles and the RSUs.
• Piggybacking
Periodic short status messages(Beacons) used to transmit WSAs
There is a chance that WSA information sent is missed by a vehicle
For vehicles that miss a WSA, beacons that are piggybacked with WSA fields are sent
System model Contd.
• If RSU directly detected data could be sent to the RSU
• If WSAs are missed but received from the piggybacked frame of other vehicle,
Directly transmit to the RSU
Transmit to the nearest neighbor which in turn transmits to the RSU
• The warning system is installed on the vehicles to receive the alert messages
• The alert messages are optimized to not be very long (close to 1 byte in size) and is pre-constructed in the RSU so that the real-time communication is efficient
Communication model for collision avoidance
Different Communication Model exist:
1) Based on Vehicles:
General warning :broadcast message to all vehicles in range(nearby accident information, road condition, etc)
Selective Warning: Message sent only to the affected vehicle(expecting collision)
2) Based on Warning Initiator:
Push Method: Here the Vehicle will send its current data including direction,speed,accelearion to the RSU for constant time interval
Pull Method: Here the RSU will initiate the status message by asking for the individual vehicle information.
We Use Selective warning with push method since this will avoid extra message overhead involved in pull method. Also, we are interested only in collision avoidance.
Challenges in Collision Warning• As the time needed to avoid collision (TA) should be less than the elapsed
time to the collision (TC) in order to avoid a collision, we need to increase the speed of detection and reduce the communication cost.
• To speed up collision detection (increasing TC), we need: centralized location of computations, selecting the range of vehicle covered.
• To reduce the TA, we need good cost function with respect to real-time communication protocol.
Cost function for calculating TA: TA = tmessage + treceive + tresponse + tbrake + V/A
tmessage- time taken by RSU to generate and transmit message treceive- time taken by driver to receive message tbrake – time for braking v/a- velocity and acceleration of the vehicle
Scenario for Issuing Warning• There should be a good threshold in the system to prevent false
alarms.• Time-To-Collision (TC) is computed by the pair-wise collision
detection algorithm while Time-To- Avoidance (TA) in Miller and Huang’s peer-to-peer collision warning system [2] is computed based on vehicle kinetics, network latency, and human response time. This holds good for v2v communication.
• If TC>TA, then warning is not issued, however if TC~TA ,then the nearby RSU issues warning to the driver.
• There exists a tradeoff between providing drivers valuable information in time and avoiding distraction to driver due to huge number of messages.
[2]R. Miller and Q. Huang, “An Adaptive Peer-to-Peer Collision WarningSystem”, Proc. of Vehicular Technology Conference (VTC) Spring2002, Birmingham, Alabama.
Scenario for Issuing Warning
• To handle such a scenario, we provide a threshold TC- TA < k, where k can be adjusted based on the driver’s choice.
• There seems to be no fixed k and it will depend on road condition, vehicle speed limit, intersection type.
• Thus different factors are involved in deciding upon a good
threshold for issuing warning.• We just know the criteria for issuing warning, but how we will
determine the distance at which a vehicle is given warning?
Minimum Distance Warning• The minimum warning distance required to inform a driver before intersection
crossing is calculated using the below parameters:[1]
v0 - velocity of the vehicle a –vehicle braking deceleration, tdriver -driver’s response time to brake, tmachine - combination of braking system and warning system response time and tinformation -constant information time, which is a time determined by the
assistance system to allow the driver to react and prepare the driver to stop
[1] INTERSAFE, D40.4 Requirements for intersection safety applications,28 Oct 2005.
RSU MODEL
The communication between the RSU and vehicle agents are regulated inside the administration zone which is the spatial domain that determines the region of authority of an intersection agent to coordinate vehicle agents in the approaching and passing vehicles.
Communication And Computation• Initially, the Vehicle pushes its status information to the RSU unit nearby.
• Next, the RSU asks for a register request and assigns a unique id to the vehicle. This will be required only for security architecutre.
• Finally the RSU sends collision message to the vehicle if needed based on its own computation.
• Computation can be performed by pairwise detection or preselection[3].
• In pairwise, the time for each car to reach the future collision point is calculated with velocity of each car and r is the vector of co-ordinate of car(x,y) and the size of the vehicle.This has high computational cost.
[3]Collision Pattern Modeling and Real-Time Collision Detection atRoad Intersections Flora Dilys Salim, Seng Wai Loke, Andry Rakotonirainy, Bala Srinivasan, Shonali KrishnaswamyProceedings of the 2007 IEEE Intelligent Transportation Systems ConferenceSeattle, WA, USA, Sept. 30 - Oct. 3, 2007
Collision DetectionX=(y2-y1)-(x2tan@2-x1tan@1)/tan@1 – tan@2
Y=(x2-x1)-(y2tan@2-y1tan@1)/cot@1 – cot@2
@-angle between the horizontal line and the trajectory of car
Time for each car to reach the Collision Point:
TTX1 = |r-r1|/|v1| sign((r-r1).v1)
TTX2 = |r-r2|/|v2| sign((r-r2).v1)
v- velocity of each car
r- vector of (x,y) collision point coordinate
| TTX1 - TTX2| < s, where s size of region rather than coordination point.
Pre-selection Detection Mechanism
• In preselection,we use historical collision pattern that exists in the intersection region. Hence, the computation is not pairwise but only selected vehicles are used collision detection which follow the predetermined pattern.
• Initially ,statistical work and analysis is needed to identify collision patters for each intersection point.
• After, the system learns, RSU can apply the collision detection based on the vehicle direction,angle,manoeuvre,speed.
• This results in lesser computation since computation is performed only for set of vehicle pairs which match the pattern data.
• If some collision is not predicted by the RSU, it is added to the existing pattern data.
RESULTS (Expected)• Packet Loss should be less in case of V2V-V2R communication
with fixed RSU when compared to the V2V communication.• The mechanism of piggybacking WAVE based parameters
over beacons should further reduce the communication gap between the Vehicles and the RSUs and prevent data packet loss.
• By introducing additional number of RSUs based on the Lane distance and the traffic density the delay time can be significantly reduced and communication can be made more effective. (There is of course a trade-off between cost and effective communication)
• The Expected Throughput should be better for V2V-V2R communication compared to the V2V Communication Model.
RESULTS (Expected)• The solution is fully compliant with 802.11p/WAVE
specifications and incurs little-to-none over-head, by leveraging on packets already foreseen to be transmitted on the Control Channel and on largely available self-positioning capabilities of vehicles.
• The Dedicated Control Channel in the DSRC is highly secured and is responsible for safely delivering the Alert messages to the Vehicles.
• The Service channels apart from hosting WBSS (WAVE Based Basic Service Set) can be used to communicate the Vehicle Location effectively to the RSUs thereby reducing further overhead.
VANET Simulators
• Deploying and testing VANETs involves very high cost and intensive labor.
• VANET Simulations often involve large and heterogeneous scenarios and must account for many specific characteristics found in a vehicular environment.
• Vehicular mobility generators are needed to increase the level of realism in VANET simulations.
• Network simulators perform detailed packet-level simulation of source, destinations, data traffic transmission, reception, background load, route, links, and channels
VANET Simulators• VANET simulators provide both traffic flow simulation and
network simulation
A survey and comparative study of simulators for vehicular ad hoc networks (VANETs) Francisco J. Martinez1, Chai Keong Toh, Juan-Carlos Cano, Carlos T. Calafate and Pietro Manzoni
VANETMOBISIM• VanetMobiSim is an extension for the CANU Mobility Simulation
Environment (CanuMobiSim), a flexible framework for user mobility modeling.
• CanuMobiSim is a JAVA based simulator and can generate movement traces in different formats, supporting different simulation/emulation tools for mobile networks (NS2, GloMoSim, QualNet, NET) .
• It also includes parsers for maps in the Geographical Data Files (GDF) standard and provides implementations of several random mobility models as well as models from vehicular dynamics.
VANETMOBISIM• The VanetMobiSim extension focuses on vehicular mobility,
and features new realistic automotive motion models at both macroscopic and microscopic levels.
• At macroscopic level, VanetMobiSim can import maps from the US Census Bureau TIGER/Line database, or randomly generate them using Voronoi tesselation.
• It also adds support for multi-lane roads, separate directional flows, differntiated speed constraints and traffic signs at intersections.
Reference – vanet.eurecom.fr
VANETMOBISIM• At microscopic level, VanetMobiSim implements new mobility
models, providing realistic Vehicle-to-Vehicle and Vehicle-to-Infrastructure/Roadside interaction.
• According to these models, vehicles regulate their speed depending on nearby cars, overtake each other and act according to traffic signs in presence of intersections.
• VanetMobiSim mobility patterns have been validated against TSIS-CORSIM - a well known and validated traffic generator - proving the high level of realism reached by VanetMobiSim.
Reference – vanet.eurecom.fr
HOW IT WORKS?The simulation scenario for VanetMobiSim is defined in XML
format. A simulation area is specified using the <universe> tag.
<universe>
[<dimx>dimension</dimx>]
[<dimy>dimension</dimy>]
[<step>step</step>]
[<seed>seed</seed>]
[<extension>extension_parameters</extension>]
[<node>node_parameter</node>]
[<nodegroup>nodegroup_parameters</nodegroup>]
</universe>
VanetMobiSim – Vehicular Ad hoc Network mobility (Manual)Extension to the CanuMobiSim frameworkCopyright © 2005-2006 Institut Eurécom/Politecnico di Torino
HOW IT WORKS?Adding a Global Extension to Simulation
An instance of global extension is added using the <extension> tag.
<extension class=”class_name” [name=”instance_name”]>
[extension_parameters]
</extension>
A node is added to simulation using the <node> tag.
<node [class=”class_name”] id=”node_id”>
[<position>position_parameters</position>]
[<type>type_of_node</position>]
[<extension>extension_parameters</extension>]
</node>
VanetMobiSim – Vehicular Ad hoc Network mobility (Manual)Extension to the CanuMobiSim frameworkCopyright © 2005-2006 Institut Eurécom/Politecnico di Torino
HOW IT WORKS?Sample of Global Extension
<extension name="PosGen" class="de.uni_stuttgart.informatik.canu.tripmodel.generators.RandomInitialPositionGenerator"/>
<extension name="TripGen" class="de.uni_stuttgart.informatik.canu.tripmodel.generators.RandomTripGenerator" >
<reflect_directions>false</reflect_directions>
<minstay>20.0</minstay> <maxstay>100.0</maxstay>
</extension>
HOW IT WORKS?Sample NodeGroup in an Input Scenario
<nodegroup n="10">
<extension class="polito.uomm.IDM_IM" initposgenerator="PosGen" tripgenerator="TripGen">
<minspeed>10.0</minspeed>
<maxspeed>20.0</maxspeed>
<step>0.1</step>
<b>0.5</b>
</extension>
</nodegroup>
HOW IT WORKS?• The VANETMobiSIM takes the scenario xml file as an Input
and generates the Movement file.• The movement file is used as a source by the NS-2 simulator
to simulate the Network. • The NS-2 Simulator has four phases:
1) Implement protocol models
2) Setup simulation scenario, i.e. create tcl file describing type of scenario, e.g. number of nodes, kind of agent working on nodes etc.
3) Run simulation, i.e. Run the tcl file
4) Analyze simulation results, i.e. by GNU Awk and gnuplot• The NS-2 simulation can also visualized using NAM
CHALLENGES IN SIMULATION• Introducing Beaconing support in DSRC when simulating the
scenario’s using VANETMobiSIM and NS-2. There exists no parameter to specify Beaconing support in NS-2.
• Handling highly mobile nodes which don’t stay for longer timeframe for the network to stabilize the topology.
• Extracting the results from huge trace files produced by NS-2 to evaluate our metrics requires complex awk parsers to process the necessary information.
• Simulating shadowing scenarios.
Sample Simulation
Future Work
• Evaluate the metrics in the presence of Obstructions.• Evaluate the metrics based on realistic Vehicular traces
available• Make use of Simulators to simulate much more complex
Urban traffic scenarios and investigate the Network parameters using NS-2.
• Try to simulate shadowing effects using Simulators as well and evaluate the performance.
Thank you!!