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Samy El-Tawab defense slides Samy El-Tawab defense slides Presentation Transcript

  • FRIEND: A Cyber-Physical System for Traffic Flow Related Information Aggregation and Dissemination Samy El-Tawab Advisor: Professor S. Olariu PhD Defense Intelligent Networking and Systems (iNetS) Research Group Department of Computer Science Old Dominion UniversityPhD Defense Samy El-Tawab July 27th , 2012
  • Outline  Introduction  Motivation and background  Objectives and goals  System infrastructure  Physical components  Reasoning about traffic flow parameters  Communication protocol in FRIEND  Decision making in FRIEND  Summary  Future research ideasPhD Defense Samy El-Tawab July 27th , 2012
  • Driving on highway If you are driving on highway What would you need? Image reference: www.driversedguru.comPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • Introduction • Vehicular Ad-Hoc Network (VANET) is a type of Mobile ad-hoc network (MANET) that allows communications between nearby vehicles and between vehicles and roadside infrastructure • Intelligent Transportation Systems (ITS) are advanced appli-cations which aim to provide innovative services relating to different modes of transport and traffic management and make safer, more coordinated, and „smarter‟ use of transport networks http://media.nowpublic.netPhD Defense Samy El-Tawab July 27th , 2012
  • More about Vehicular Networks… • Main characteristics – uses vehicles as network nodes – road side units as fixed nodes – nodes move relative to each other but within the constraints of the road infrastructure – limited communication range – high mobility of nodesPhD Defense Samy El-Tawab July 27th , 2012
  • VANET – a closer look • Vehicle-to-Vehicle (V2V) • Vehicle-to-Infrastructure (V2I) • Infrastructure -to-Infrastructure (I2I)PhD Defense Samy El-Tawab July 27th , 2012
  • And more about ITS… • Responsibilities: – basic management systems : • car navigation • traffic signal control systems • automatic number plate recognition • speed cameras – to more advanced applications: • monitor applications: security CCTV systems • parking guidance and information systems • weather information • bridge de-icing systemsPhD Defense Samy El-Tawab July 27th , 2012
  • However… • Although all these sensing technologies: – inductive loop detectors – magnetic sensors – passive and active – ultrasound sensors – infrared sensors – microwave sensors – laser sensors – video image processorsPhD Defense Samy El-Tawab July 27th , 2012
  • Even VANET • A typical VANET system for reporting traffic conditions consists of vehicles exchanging information about their position and speed with each other • The vehicles then use this information to determine where traffic slowdowns are occurring and report that information to other vehicles – NOTICE: an architecture for the notification of traffic incidentsPhD Defense Samy El-Tawab July 27th , 2012
  • VANET applications • Traffic monitoring: to monitor the highway, to give information about the flow, speed and density on road • Incident detection: to detect and notify drivers about incidents on highway • Weather alerts: ice, foggy, heavy rain and tornado watch • Emergency situations: closed road, maintenance and planned evacuationsPhD Defense Samy El-Tawab July 27th , 2012
  • Our classification of VANET applications Real-Time Traffic Monitoring Incident Detection Traffic Information System Weather Alert System Backup Warning System Data Collection on Highways Temperature Monitoring on HighwaysPhD Defense Samy El-Tawab July 27th , 2012
  • What we need? • Integrating resources and capabilities at the nexus between the cyber and physical worlds, (a cyber-physical system for traffic flow-related information aggregation and dissemination) FRIEND will contribute to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions • We anticipate providing the drivers with a meaningful, color- coded, at-a-glance view of flow conditions ahead, alerting them to traffic eventsPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • Motivation • FRIEND explores the integration of wireless networking with lightweight roadside infrastructure into a cyber-physical system (CPS) that enables – privacy-aware detection of traffic-related events – the dissemination to the driving public of such aggregated information both in the form of a color-coded traffic status report and traffic advisories in the case of serious incidentsPhD Defense Samy El-Tawab July 27th , 2012
  • Objectives and goals – in brief • To collect traffic data about the traffic flow • To aggregate the collected data in a way that allows to detect and/or to anticipate traffic-related events • To disseminate relevant traffic related information to the driving publicPhD Defense Samy El-Tawab July 27th , 2012
  • Objectives and goals using V2I or I2I • Traffic data collection • Traffic status dissemination V2I • Traffic advisories dissemination • Acquiring coarse-grain incident location information • Acquiring fine-grain incident location information I2I • Acquiring fine-grain information about backup dynamicsPhD Defense Samy El-Tawab July 27th , 2012
  • Problem definition By using already existing infrastructure: to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions and provide the drivers with a meaningful, color-coded, at-a glance view of flow conditions ahead, alerting them to any traffic eventPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND - physical components smart cat‟s eyes (SCE) • The cat‟s eye nodes are deployed uniformly along the road on both sides as lane separators • The intention is for smart cat‟s eyes (SCEs) to replace, in the near future, the ubiquitous cat‟s eyesPhD Defense Samy El-Tawab July 27th , 2012 *Photo Credit :http://www.catseyeroadstuds.com
  • FRIEND - physical components smart cat‟s eyes (SCE) - components • Architecture: Each SCE is a compact, self-contained package. It contains several types of sensors (including magnetometers), a radio transmitter, an RFID tag, a micro-controller, a solar panel and a lithium battery • Power consumption • Communication technology: SCE features a narrowband frequency-shift keying (FSK) data transceiver as well as one of many possible types of RFID tagsPhD Defense Samy El-Tawab July 27th , 2012 *Photo Credit :http://www.catseyeroadstuds.com
  • FRIEND - physical components smart cat‟s eyes (SCE) - features • suitable for edge line of road and pavement • can work more than three years which promotes energy efficiency and environmental friendliness • load-bearing more than 20 ton as two reinforced veins are designed on the top • edges to strengthen compression resistance and protect the solar panel against compression • waterproof and unbreakable: the solar panel, electronics and optics are fitted insidePhD Defense Samy El-Tawab July 27th , 2012 *Photo Credit :http://www.catseyeroadstuds.com
  • FRIEND - physical components roadside units (RSU)• RSU: deployed at regular intervals - consists of – GPS – radio transceiver – a laptop-class embedded computing device – on-board battery packs charged by solar panels• Role: – To collect and aggregate traffic-related information from the passing cars as well as by interchanging information, on an intermittent basis with adjacent RSUsPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND - physical components roadside units (RSU) – does it exist?• Examples from interstate 64 highwayPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND - the vehicular model • Event Data Recorder (EDR) • GPS receiver • Wireless transceiver • Digital built-in map • Radar • Smart wheels – Temperature sensor – Electronic stability control system – RFID readerPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND - the vehicular modelthe event data recorder - EDR • The EDR record transactions that occurs in the previous area • These transactions contains: time, location, max speed, min speed, lane changingPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND - the vehicular modelEDR - transactionsPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – traffic terms • Historical data • Speed, density and flow rate • Headway distance, safe headway distancePhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – evaluatingPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – evaluating - conclude • Evaluating the probability of large headway distances in co- directional traffic – Question: given that m cars are deployed uniformly at random in a single lane of traffic of one kilometer and given that dependable radio communications between cars require a maximum inter-car distance of 200 meters2 what is the probability that there is end-to-end radio connectivity between the m cars? – Answer: the number of cars per kilometer must be at least 16 in order to have a better than even chance for connectivity, it takes about 23 cars per kilometer for end-to-end connectivity to be present with 90% probabilityPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – evaluating - clarify • If there were 12 co-directional cars in the window, the probability of no end-to-end connectivity between them would be about 86%. • The probability decreases with the number of co-directional lanes of traffic in each directionPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – more evaluating  Evaluating the expected size of a cluster • Where m cars and n the number of inter-car spaces and d corresponds to the maximum effective transmission rangePhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – average headway distance • The following are the steps performed by the RSU to calculate the average headway distance – RSUi (in time period [t0, t1]) receives number of records from different vehicles, its record includes time, location, speed and lane – RSUi calculate the location of each vehicle at time T within same lane – RSUi sorts the records and calculate the headway distance between each vehicle – RSUi update headway buffer with headway distances recorded – RSUi compare the headway in the buffer with any received headway data from vehicles – the recorded data in the buffer can give us an indication for the traffic density on the highway at the RSUiPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – communication protocols adjacent RSUs • To detect initial stages of congestion or when an incident having occurred in the segment between them triggers changes in the traffic flow • To gain the fine-grain determination of the location of the accident • To support the propagation of the color-coded traffic status reports to vehicles along the roadwayPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – communication protocols RSU communication with vehiclesPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – communication protocols communication from SCEs to RSUs • We use simple narrowband FSK radio data transmitters that turn on within milliseconds, and draw only 10-20mA • Adjacent-channel interference and jamming are very real problems, but can be mitigated by using a frequency-agile narrow-band system • Since this communication does not require a high data rate, we choose to use narrow-band FSK data transceivers in SCEsPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – communication protocols communication between adjacent SCEsPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – communication protocols communication from vehicles to SCEs • FRIEND assumes the use RFID technology as the communication medium between the smart wheels and SCEs – the RFID reader in the smart wheels allows the vehicle to inform the SCEs about speed, stability loss due to road conditions (if any) and ambient temperature – the SCEs collect data sent from vehicles every t, where t depends on highway conditions – the RFID reader in the smart wheels transmits an object identity using electromagnetic waves in the SCE, an RFID tag stores its ID in memory – the RFID reader which is installed in the vehicle wheels emits RF radio waves eliciting a signal back from the tag. We use RFID with radio range (up to approximately 3m)PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – color-coded states • Level of Service (LoS) is a measure used in ITS by traffic engineers to assess the effectiveness of various elements of transportation infrastructure – A = Free flow – B = Reasonably free flow – C = Stable flow – D = Approaching unstable flow – E = Unstable flow – F = Forced or breakdown flowPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – color-coded states - transitions • In order to avoid spurious transitions between colors, FRIEND has a built-in “laziness” that records traffic flow trends without necessarily taking immediate action • Example: the reported status is yellow if the internal Markov chain is in any of the three yellow statesPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – color-coded states – mapping • FRIEND employs to effect state transitions in the internal Markov chain are – the average headway distance (AHD) – maximum speed aggregated (Speed) – historical data collected over a longer time of monitoring data at the same localePhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident classification Incidents Blocking Moving Non- Incidents Incidents blocking IncidentsPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident expected flow 1/3PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident expected flow 2/3PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident expected flow 3/3PhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident detection algorithm • Task 0: RSU initialization: Initially, we assume that RSUi just started to collect data • Task 1: Incident detection: RSUi is notified of an incident or RSUi notices change of speed or density of RSU-RSU[i,j] – A notification of lane changing in the same location in the previous RSU-RSU area in a short time, identifies the possibility of an incident – Threshold Thi can be determined from historical data, the higher the threshold the more time needed to detect an incident and the less chance to generate alarmsPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – incident detection algorithm – Task 1-1: Identifying RSU-RSU: Determining which RSU-RSU[i,j] area where incident occurs ”Global view” – Task 1-2 : Identifying segment and location: Identify segment with incident; vehicles that changed lanes in the last segment report lane change Lc and location of lane change – Task 1-3: Classifying the incident • Task 2: Information disseminationPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-relateddecisions – incident information dissemination • Different types of events or incidents requires different levels of propagation depending on how critical the incident and how long it stays • Drivers would like to receive information that affects their decision rather than just notification about incidents that will be solved by the time they reach this point on the highway – GPS with life traffic information can give warning messages about incident that far away from other vehicles – Virginia 511 offered by Virginia Department of Transportation (VDOT) is a similar example of a service that disseminate information on a website or mobile applicationPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-relateddecisions – incident information dissemination • In FRIEND, the more the incident stays, the further the information will be propagated • FRIEND compares different densities with the level or distance of propagation bearing in mind the principle of locality • We have two aims for information propagation – to prevent secondary accidents  Stage I – notify drivers far away from the accident of an expected delay by updating there coloring system  Stage IIPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – stage I • Focus on the first goal which notifying vehicles with short distance to an accident – the RSU is responsible of informing the previous RSU immediately of the incident in inform the vehicles passing beside it of the incident – the more time the incident takes to be cleared, the more frequently previous RSU will be informed of the incidentPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – stage II • We obey two rules: – to track the source of the incident to be able to track the movement of vehicles after the event is cleared – To send a long time to live message every T, this message target far away vehicles in order to be able to take the decision of keep going or take an exit • The decision of switching between stages I and II depends on the average headway distance (AHD), speed of vehicles and historical data, time and day of the incidentPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – stage II – track head and tail • Head of a backup • Tail of a backup • Knowing the length of the backup and tracking the Head and Tail are important information that can be propagated and used in Stage II to inform approaching vehicles of an incident at a specific locationPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – stage II – track head and tailPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – making traffic-related decisions – stage II – information sent • The information sent between adjacent RSU(s) is the following – Time: the time of last update – Head location – Tail location – Incident clearance flag – Average speed of arriving vehicles at the RSUt – Average speed of moving vehicles at the RSUhPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – evaluation • The use ONE simulator – We adopted a two-lane highway similar to Interstate US13 highway in Virginia, USA – The model assume fixed nodes between the two lanes which represents SCEs along the highway – Another fixed nodes every one mile – Highway length approx. 11miles – Max speed for vehicles 55 miles/hr – Model movement : Map based movementPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – measure • Our model compares the ratio of messages dropped over all messagesPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND – measure • we study the idea of having two, three or four SCEs detecting vehicles at high speedPhD Defense Samy El-Tawab July 27th , 2012
  • FRIEND vs. Virginia 511 • VDOT lately latched a system that ( telephone, mobile application and website) • Centralized vs. distributedPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • Concluding remarks • We built the complete theoretical system FRIEND – The strongest point of FRIEND is using infra-structure already exist – We defined our nodes in details – We showed the communication protocol between different nodes – We calculated mathematically • the expected headway distance in free-flow traffic in a single lane L • the probability of large headway distances in co-directional traffic • the expected cluster size – We showed the mapping algorithm between the traffic flow parameters and the 10 Markov chain statesPhD Defense Samy El-Tawab July 27th , 2012
  • More concluding remarks • We built the complete theoretical system FRIEND – We classified the incidents on highways – We designed an incident detection algorithm – We described our information dissemination algorithm with the two stages – We showed how to track the backup dynamicsPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • Directions for future work • Enhance the energy efficiency both of data collection and data dissemination • Exploit existing (or anticipated) correlation of traffic data to put RSUs “to sleep” instead of mandating them to continually collect data • Perfect an efficient way whereby the vehicles wake up the RSUs in sparse trafficPhD Defense Samy El-Tawab July 27th , 2012
  • More future work … • Better understand the triggers that signal to FRIEND trends in the traffic flow that need immediate action to prevent congestion from building up • Evaluate the effect of traffic buildup in the case of a serious incident – One idea is to merge two backups on the highway in case of different incidents occurring at the time and impacting the traffic flow – Another idea to calculate the expected backup length by timePhD Defense Samy El-Tawab July 27th , 2012
  • More and more • Extending the current simulation model for FRIEND by incorporating more realistic assumptions • Hands on: Study the SCE(s) by doing couple of experiments: – Number of vehicles that a SCE can detect on a highway I-81 – Power consumptions after couple of weeks – Exact cost of one SCEPhD Defense Samy El-Tawab July 27th , 2012
  • PhD Defense Samy El-Tawab July 27th , 2012
  • Publications, presentations, posters and book chapters • Samy El-Tawab, and Stephan Olariu: ”Intelligent Road Detection” in The College of William and Mary‟s 8th Annual Graduate Research Symposium, Williamsburg, Virginia, March 2009. My paper was awarded a prize for Excellence in Scholarship • Samy El-Tawab, Mahmoud Abuelela, and Yan Gongjun: ”Real-Time Weather Notification System using Intelligent Vehicles and Smart Sensors”, First International Workshop on Intelligent Vehicular Networks (InVeNET 2009) Co-Located with IEEE MASS 2009, October 12th, 2009 - Macau SAR, China • Yan Gongjun, Danda B. Rawat, and Samy El-Tawab: ” Ticket-based Reliable Routing in VANET”, First International Workshop on Intelligent Vehicular Networks (InVeNET 2009) Co-Located with IEEE MASS 2009, October 12th , 2009 - Macau SAR, ChinaPhD Defense Samy El-Tawab July 27th , 2012
  • More publications … • Book Chapter: Samy El-Tawab, and Yan Gongjun: ”Safety and Commercial Applications”, Advances in Vehicular Ad-Hoc Networks: Developments and Challenges. A book edited by Prof. Mohamed K. Watfa University of Wollongong, UAE • Book Chapter: Yan Gongjun, Samy El-Tawab, and Danda B. Rawat: ”Reliable Routing Protocols in VANETs”, Advances in Vehicular Ad-Hoc Networks: Developments and Challenges. A book edited by Prof. Mohamed K. Watfa University of Wollongong, UAE • Poster: Samy El-Tawab, and Stephan Olariu:”Monitoring Queue-ends on highways using Smart Sensors”, 11th Annual Student Research Poster Session, Christopher Newport University, VA , USA November 2009PhD Defense Samy El-Tawab July 27th , 2012
  • And more… • Samy El-Tawab, and Stephan Olariu: ”FIRMS: A Framework for Intelligent Road Monitoring System using Smart Sensors” in the International Journal of Information Sciences and Computer Engineering, Vol.1 No.2 2010 pages 1-6. • Samy El-Tawab ”Integrity, vulnerability and security for Vehicular Networks” in The Doctoral Consortium of the 2010 IEEE International Conference on Networking, Sensing and Control April 11-13, 2010 Chicago, IL, USA • Samy El-Tawab, and Stephan Olariu ”A Cyber Physical System for Highway Applications in Vehicular Networks” in the 9th International Conference on Mobile Systems, Applications, and Services- PhD Forum” June 28th-July 1st , 2011,Washington, DC, USAPhD Defense Samy El-Tawab July 27th , 2012
  • Even more… • Samy El-Tawab, Stephan Olariu and Mohammad Almalag ”FRIEND: A Cyber-physical System for Traffic Flow Related Information aggrEgatioN and Dissemination” in IEEE VTP 2012 workshop June 25th, 2012 in the IEEE WoWMoM 2012, San Francisco, CA, USAPhD Defense Samy El-Tawab July 27th , 2012
  • Thank You - Questions
  • Standard VANET application classification Applications in VANET Safety Commercial Applications ApplicationsHigh Priority Low Priority Monitoring and Entertainment Safety Safety Service ApplicationsApplications Applications Applications
  • Lane detection using GPS• In FRIEND, SCE(s) can play a good role in this case• We can also use interpolation to estimate the current location of the car within the road at each sample point ni