Validation of TomTom historical average speeds on freeway segments in Gauteng, South Africa

Gwara, Batsirai (2017-03)

Thesis (MEng)--Stellenbosch University, 2017.

Thesis

ENGLISH ABSTRACT: Traditional methods of traffic data collection, such as inductive loops and road sensors, continue to be the main source of traffic data. The advancement in technology and vehicle tracking methods has proved to be the impetus behind the emerging of alternative and innovative sources of traffic data, such as ITS data sources. ITS sources, such as vehicle probes, are becoming increasingly important due to their low cost and the vast amounts of traffic data produced. However, traffic data from ITS sources raise new concerns about data quality. The quality of probe data in South Africa and other developing countries is unknown. This study sets out to investigate the quality of TomTom historical average speeds on selected freeway segments in South Africa. The study compared TomTom historical speed estimates and reference speeds on six directional segments on the N1 and R21 freeways. The reference data used was Automatic Number Plate Recognition (ANPR) data, a component of Open Road Tolling (ORT) in Gauteng. A freeway segment is the road section between two toll gantries. All 15-minute and 1-hour intervals between 05:00 and 20:00 during the weekdays (Monday – Friday) in February 2015 were grouped and aggregated. The quality measures evaluated were accuracy, completeness, validity, coverage and accessibility. To evaluate accuracy, three error quantities were determined, namely signed error, average absolute speed error (AASE) and speed error bias (SEB). The allowable errors for the signed error, AASE and SEB were ±10 %, 10 km/h and ±7.5 km/h, respectively. TomTom speeds were highly consistent with the reference speeds. The error quantities for the combined freeway segments were less than the allowable errors. The signed errors and AASE for all the six individual freeway segments were also less than the allowable errors. In five of the six sections, the SEB was less than the allowable error. There were no significant differences between the error quantities derived from 15-minute and 1-hour interval speeds for the combined and individual freeway segments. On the other hand, validity was dependent on the selected measure. TomTom speeds were of very high quality based on the signed error and AASE, whereas the same data was of moderate quality based on the SEB. Although the TomTom speeds were within the specified accuracy thresholds, the speed estimates were generally lower than the reference speeds throughout the analysis period. TomTom estimates were better at low speeds and the quality of TomTom estimates declined with an increase in speed. It is possible that the low TomTom speed estimates were due to a sample that was not a true representation of the traffic stream. Importantly, it is possible to enhance the accuracy of TomTom speed estimates by using certain percentile speeds instead of average speeds.

AFRIKAANSE OPSOMMING: Tradisionele metodes vir die insameling van verkeerdata, soos byvoorbeeld induksie lusse en padsensors, is tans die hoofbron van verkeerdata. Die vooruitgang in tegnologie en voertuig monitering is tans die dryfkrag van alternatiewe en innoverende bronne van verkeerdata, soos byvoorbeeld Intelligente Vervoer Stelsels (IVS) databronne. IVS bronne, soos voertuigsondes, se toepaslikheid neem toe weens lae koste en die hoeveelheid data wat versamel word. Een bekommernis aangaande data vanaf IVS bronne is die data kwaliteit. Die kwaliteit van sondes se data in Suid-Afrika en ander ontwikkelende lande is nie geverifieer nie. Hierdie studie ondersoek die kwaliteit van spoed metings vanuit TomTom se historiese data vir deurpadsegmente in Suid-Afrika. Hierdie ondersoek vergelyk TomTom se historiese snelhede verwysing snelhede op ses segmente op die N1 en R21 deurpaaie. Die verwysingdata was afkomstig van outomatiese nommerplaat identifisering (ANPR), ’n komponent van “Open Road Tolling” (ORT) in Gauteng. ’n Segment is gedefinieer as die seksie tussen twee tol stellasies. Alle 15-minuut en 1-uur intervalle tussen 05:00 en 20:00 tydens die weekdae (Maandag-Vrydag) in Februarie 2015 was gegroepeer en opgesom. Die kwaliteitsmaatstawwe wat geëvalueer is sluit akkuraatheid, volledigheid, geskiktheid, dekking en toeganklikheid in. Om akkuraatheid te evalueer was drie foutmaatstawwe bepaal, naamlik getekende fout, gemiddelde absolute spoed fout (AASE) en spoed-fout-vooroordeel (SEB). Die toelaatbare foute vir die getekende fout, AASE en SEB was ±10 %, 10 km/h en ±7.5 km/h, respektiewelik. TomTom snelhede het uitstekend korreleer met die verwysingsnelhede. Die fout meting vir die gekombineerde deurpadsegmente was minder as die toelaatbare foute. Die getekende foute en AASE vir al ses die individuele deurpad segmente was ook minder as die toelaatbare foute. Vir vyf van die ses segmente was die SEB minder as die maksimum waarde. Daar was geen noemenswaardige verskille tussen fout maatstawwe tussen die 15-minuut en 1-uur interval snelhede vir die gekombineerde en individuele deurpad segmente nie. Die geskiktheid van die data was afhanklik van die gekose maatstaaf. TomTom snelhede was van hoë gehalte gebaseer op die getekende fout en AASE, maar was van matige kwaliteit gebaseer op die SEB. Alhoewel die TomTom snelhede binne die voorgeskrewe perke was, was dit in die algemeen laer as die verwysingsnelhede vir die meeste van die analise periode. TomTom voorspellings was beter vir laer snelhede en die kwaliteit van TomTom data het afgeneem met ’n toename in snelheid. Dit is moontlik dat die lae TomTom snelheidvoorspellings ’n gevolg is van ’n monster wat nie ’n ware verteenwoordiging van die verkeerstroom is nie. Die akkuraatheid van snelheidvoorspellings verbeter word deur ‘n sekere persentiel snelheid te gebruik in plaas van gemiddelde snelhede.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/101307
This item appears in the following collections: