The paper analyses the expected value of OD volumes from probe with fixed error, error that is proportional to zone size and inversely proportional to zone size. To add realism to the analysis, real trip ODs in the Tokyo Metropolitan Region are synthesised. The results show that for small zone coding with average radius of 1.1km, and fixed measurement error of 100m, an accuracy of 70% can be expected. The equivalent accuracy for medium zone coding with average radius of 5km would translate into a fixed error of approximately 300m. As expected small zone coding is more sensitive than medium zone coding as the chances of the probe error envelope falling into adjacent zones are higher. For the same error radii, error proportional to zone size would deliver higher level of accuracy. As over half (54.8%) of the trip ends start or end at zone with equivalent radius of ≤ 1.2 km and only 13% of trips ends occurred at zones with equivalent radius ≥2.5km, measurement error that is proportional to zone size such as mobile phone would deliver higher level of accuracy. The synthesis of real OD with different probe error characteristics have shown that expected value of >85% is difficult to achieve for small zone coding with average radius of 1.1km. For most transport applications, OD matrix at medium zone coding is sufficient for transport management. From this study it can be drawn that GPS with error range between 2 and 5m, and at medium zone coding (average radius of 5km) would provide OD estimates greater than 90% of the expected value. However, for a typical mobile phone operating error range at medium zone coding the expected value would be lower than 85%. This paper assumes transmission of one origin and one destination positions from the probe. However, if multiple positions within the origin and destination zones are transmitted, map matching to transport network could be performed and it would greatly improve the accuracy of the probe data.
[1]
Franco Davoli,et al.
Road traffic estimation from location tracking data in the mobile cellular network
,
2000,
2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).
[2]
Andrea Vitaletti,et al.
Cell-ID location technique, limits and benefits: an experimental study
,
2004,
Sixth IEEE Workshop on Mobile Computing Systems and Applications.
[3]
Mario Anžek,et al.
Travel Time Information Service Utilising Mobile Phone Tracking
,
2004
.
[4]
Scott Kirkpatrick,et al.
Location Based Services Location Based Services
,
2005
.
[5]
Yasuo Asakura,et al.
TRACKING SURVEY FOR INDIVIDUAL TRAVEL BEHAVIOUR USING MOBILE COMMUNICATION INSTRUMENTS
,
2004
.
[6]
William J. Buchanan,et al.
Critical analysis and error determination of locating-finding techniques in GSM
,
2005,
Int. J. Mob. Commun..
[7]
W. Schneider.
Mobile phones as a basis for traffic state information
,
2005,
Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..
[8]
Jochen Schiller,et al.
Location Based Services
,
2004
.
[9]
Clemens Burgi,et al.
Hybrid Positioning using GPS and GSM Ranging Measurements
,
2004
.