Archive for the ‘vehicular’ Category

WikiRank and Car Traffic Data

Thursday, March 19th, 2009

Wikirank uses Wikipedia’s traffic data to see what’s interesting on the web. One could use car traffic data to spot what’s interesting on our streets. The question of course is how ;-)

Why I blog this? It’s relevant to Ilias’ research. Plus, Licia will start a cool project on using mobile data for navigating cities – she currently has an opening on that – check her website! For more, stay tuned.

Seminar: Research on Intelligent Transportation Systems in Taiwan

Friday, May 23rd, 2008

George D. Magoulas is co-organizing a very interesting seminar  on the  13th of June (Friday) at 1:30pm in Room 124 (Senate House North Block – Pdf map). The speaker is Prof. Tsu-Tian Lee, the President of the National Taipei University of Technology.

In the 21st century, the mainstream of technology development is the interdisciplinary integration, together with the human-centred technologies (HT) that emphasizes on friendly service for human rather than the forced adaptation by human. Intelligent Transportation Systems (ITS), an integrated discipline of sensing, controls, information technology, electronics, communications and traffic management with transportation systems, represents a typical human-centred large-scale and highly complex dynamic system. It is aimed to provide the traveler information to increase safety, efficiency, and reduce traffic jam, therefore a more humanistic transportation system.  Accordingly, new research topics emerge. Specifically, increasing machine intelligence (Machine IQ), human-in-the-loop control system technology (Human-centred Control), human-based intelligent dialogue interface technology (Human-based Interfacing), vision and communication supported and enhancement systems (Smart Vision, Smart Networking), human physical conditions detection and intelligent control technology (Intelligent Control), multi-agent for large-scale systems to support information analysis (Large-Scale System Analysis). Thus, fundamental research and technology development on ITS in Taiwan is devoted to following major studies.

Crowdsourcing traffic information

Friday, November 16th, 2007

“You’re sitting in a traffic jam, late for a meeting, watching the estimated time of arrival on your satnav’s display creep later and later as it takes account of the fact that, right now, you’re not going anywhere. Do you cancel, try another route, or wait it out?

TomTom, the Dutch maker of navigation devices, is claiming to put an end to this kind of dilemma with a new service it launched today in the Netherlands, dubbed High Definition Traffic. It tracks the paths of about 4 million Vodafone mobile phone users to expand the amount of traffic information available“. More on FT’s tech blog.

DelFly: Tiny Robotic Ornithopter Spy

Saturday, November 3rd, 2007

BoingBoing has a video of a tiny camera-carrying ornithopter developed at the Delft University of Technology. The ornithopter has a 35 cm wingspan and can carry a camera and video transmitter for 17 minutes. The next model will have a 10 cm wingspan.

As usual, the researcher “suggests that it could be used to locate victims in collapsed buildings”. If that happens before they’re used for police surveillance or military targetting, I’ll be pleasantly surprised.

Vehicles and pervasive computing

Sunday, May 27th, 2007

As you might now I attended PerCom a couple of months ago.

During the panel discussion, there was an interesting conclusion that vehicles are the most pervasive devices available today.
If you think about it vehicles contain a large number of sensors:

  • Speed
  • Acceleration
  • Yaw, G sensors (for ESP)
  • Temperature (environment, engine, tires)
  • Light sensors (automatic lights etc)
  • Fuel consumption, oxygen level, CO2 levels
  • GPS, Navigation system, maps etc.
  • Noise (to automatically regulate car radio volume)

Furthermore, modern vehicles have a number of ways to communicate (FM Radio (RDS,TMC), Bluetooth, GSM, soon 802.11n (WAVE) ). In my opinion, all these features already constitute vehicles as mobile sensor platforms. By exploiting already available sensors we can design numerous applications:

  • Road traffic monitoring (using acceleration and speed sensors)
  • Distributed pollution and temperature monitoring
  • Parking information
  • Formation of platoons of vehicles (e.g. maximize road capacity)
  • Dissemination of warning information
  • Accident avoidance (e.g. break when approaching a red light fast)
  • Visual enhancement (e.g. provide information on the windshield about traffic ahead, red light warning).
  • Landmarks/advertisement
  • Communication between vehicles (voice/file sharing etc)

All these application can be implemented either centrally (e.g. using GSM) or in an Ad-Hoc manner. Although the first approach is more reliable and fast it has some disadvantages:

  • Centralized data may be outdated and the response time may not meet the real-time requirements. Especially if we want local information (like “is the traffic light ahead red?”, “is there a parking spot within 100m?”)
  • Current centralized communication solutions (GSM, WiMAX) may not be able to handle the burden of real-time monitoring of hundreds of thousands of vehicles. These services are allready congested with million of mobile phone users.
  • Infrastructure could be quite expensive, especially if the area to be covered is large. Furthermore, infrastructure may not be available, especially in remote and isolated areas (you haven’t been on mountains in Greece ;) ).
  • Ad-hoc service is free and it can provide more concentrated local information (e.g. advertisements etc)

However, there are a lot of research issues in order to implement all these Ad-Hoc applications:

  • We need robust routing protocols that work both in dense urban areas and sparser areas (e.g. DTN).
  • We need dissemination protocols that take into account the interest of the vehicles/drivers to avoid flooding the drivers with unnecessary information and cause congestion to the network
  • We need MAC protocols that are able to deliver information to high-speed moving vehicles.
  • We need extremely robust trust and security mechanisms because there are human lives at risk!!

My last year’s research was manly focused on two areas:
How to exploit the navigation system of the car to route and disseminate messages, and how to use the Publish/Subscribe communication paradigm to achieve that.

Navigation systems are becoming more and more popular. A part from navigation suggestions, navigation systems provide valuable information that is currently not generally used. First of all, the GPS unit provides the vehicle’s geographical location. Furthermore, the NS map provides various geographical information: street names and numbers, location of points of interest (like fuel stations, train stations, etc), kilometer ranges, etc. This information may be extended to include the location of known infostations so that the vehicle can geographically route information to them.

At the same time, the most important information that the NS provides is the suggested route of the vehicle: This information 1)makes the mobility patterns of the vehicles more predictable. Additionally, 2)it can be exploited to extract interests, which can be used to design efficient routing and dissemination protocols and to filter information that is only relevant to the driver without his/her intervention (for example an accident warning affects only vehicles that will drive near the accident).

Therefore, in the last months I examined how we exploit the navigation systems (suggested routes to predict mobility patterns and to extract subscriptions) in order to design a vehicular routing algorithm and a Publish/Subscribe system.

You can find the results here
There is also some additional work on Pub/sub issues but we have to wait the reviewers first :)

Ilias Leontiadis

Mapping Traffic Flow

Thursday, May 24th, 2007

New will enable drivers to find the quickest route to their final destination.

A Boston-based company has integrated new trafficking software into its map database so that drivers can find the most optimal route based on speed rather than distance. The software determines the average speed of roadways across the United States based on two years of historical traffic-speed data collected from commercial fleet vehicles; it uses real-time global positioning software and road sensors from the department of transportation.

Vehicular nets: a promising application of reputation models

Monday, May 7th, 2007

In Italy, hackers have introduced erroneous messages into the traffic signal sent to GPS devices (article). This exemplifies the pay someone to do your assignment need of security for vehicular networks. Part of the needed security mechanims may be offered by reputation (trust) models as two recent papers show:

A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks (pdf)
On the Benefits of Cheating by Self-Interested Agents in Vehicular Networks (pdf)

IP Datagrams on Avian Carriers

Wednesday, February 28th, 2007

From a recent article: Scientists with the Robot Engineering Technology Research Center of east China’s Shandong University of Science and Technology say they implanted micro electrodes in the brain of a pigeon so they can command it to fly right or left or up or down.

How does this relate to networks? There is a RFC standard (RFC 1149) on using pigeons to carry IP datagrams.

(And if you are really interested in the absurd, look at this article on similar work on sharks!)

Learning and Inferring Transportation Routines

Wednesday, January 31st, 2007

This paper (whose extended journal version has been recently accepted) proposes a hierarchical Markov model that learns and infers a user’s daily movements.

Nissan tests intelligent transportation system

Friday, January 19th, 2007

by Jonathan Goddard

Nissan tests intelligent transportation system Image
Nissan tests intelligent transportation system Image Nissan tests intelligent transportation system Image

See larger / more images / slideshow

20 September 2006 – Nissan is testing a newly developed intelligent transportation system, which it is hoped will allow vehicle-to-infrastructure communication to reduce traffic accidents and ease congestion.

The test, slated to begin on 1 October and conclude in 2009, is in Kanagaw – 25km from Tokyo. Around 10,000 drivers, who must be subscribers to Nissan’s CARWINGS navigation service, are expected to participate.

The advanced road traffic system uses information obtained from nearby vehicles and roadside optical beacons to alert drivers to potential danger from approaching vehicles. The information is received by an onboard antenna on the vehicle, and the system uses the information to warn drivers when they are speeding in restricted zones. It also provides drivers with fastest-route information using “probe data” – information on the position and speed of vehicles obtained by wireless communications technology.

Based on the results of the test, Nissan is planning to implement its intelligent transportation system in Japan and then globally in the future as part of its efforts to help reduce traffic accidents and congestion. In Japan, Nissan has set a target of halving the number of traffic fatalities or serious injuries involving Nissan vehicles by 2015 compared with the 1995 level

Modelling the Spread of Rumours in Complex Social Networks

Thursday, January 18th, 2007

A while back Mazir gave an interesting talk whose abstract is below. One of the directions of future research is to model the spread of rumours in a web of trust. That might be of interest to some of us.

Rumours are an important form of social communications, and their
spreading plays a significant role in a variety of human affairs. Standard
models of rumours do not take into account the topology of the
underlying social interaction networks along which rumours spread. In
this talk I introduce a new stochastic model for the spread of rumours
in large-scale online social networks which are characterized by highly
complex connectivity patterns. I derive a set of mean-field equations
for the dynamics of the model on such networks and use analytical and
numerical solutions of these equations to examine the critical
properties and dynamics of rumour spreading on several models of
complex social networks.

Dynamic Congestion Charge & Vehicular Ad-Hoc Networks

Wednesday, December 6th, 2006

Comments on Sensor Web Design Studies for Realtime Dynamic Congestion Pricing (here)

Situation: Traffic congestion is a fundamental problem. To avoid it on some streets, one may charge drivers accessing those streets. For simplicity, one usually charges a fixed rate (e.g., London congestion charge).  However, dynamic pricing is preferable – one charges depending on information about local road events, public event calendars, road segments, and congestion patterns.
Problem: The pricing model needs to gather such information.
Proposal: This paper proposes to do so by collecting readings from sensors and from aircrafts/UAVs with video cameras.
Future: To extend this proposal, one may be inspired by existing work on ad-hoc vehicular nets (e.g.,  by Ilias‘ recent work). What about  ‘Realtime Dynamic Congestion Charge with Vehicular Ad-Hoc Networks’?