Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles

Data collection for the provision of real time traveller information services is a key issue, both for the travellers as well as for traffic managers. This paper presents a methodology for estimating travel times in dense urban road networks using point-to-point detectors. The aim is to fill in the gap of existing travel time estimation methodologies, which are based on point-to-point detection devices. Bluetooth (BT) is considered as one of the less expensive technologies for estimating travel times. Data filtering and data correction require rigorous methodologies, which if not correctly applied may result in inaccurate results as compared to other methods. The main difficulty of data processing is to identify the correct set of Media Access Control (MAC) addresses for estimating travel times, especially in dense urban road networks, where three main error sources exist: the co-existence of various transport modes (private vehicles, buses, pedestrians, bicycles etc.), the existence of more than one possible paths between two BT detectors and the existence of stops or trips ending between two BT detectors. These error sources create outliers that need to be identified and taken into account. The results of the proposed methodology confirm that outliers are eliminated, as shown by a case study with 10 BT detectors installed at major intersections of Thessaloniki's Central Business District (CBD).

show abstract

“…The results confirm that data collected by BT detectors can be used for monitoring non-recurrent events (Hainen et al 2011).…”

Section: Literature Reviewsupporting

confidence: 80%

A Robust Method for Real Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors

et al. 2015

View full text Add to dashboard Cite

show abstract

“…In recent years, a number of technologies have emerged enabling travel time information to be collected on public roads (72)(73)(74)(75)(76)(77)(78)(79)(80)(81)(82)(83)(84)(85)(86)(87)(88). The probe data market is not yet mature enough to be able to effectively measure minor movements and side street delay, except where volumes are exceptionally high.…”

Section: Travel Time Data Sourcesmentioning

confidence: 99%

“…The MAC addresses can be matched from station to station to calculate travel times (77)(78)(79)(80)(81). This provides a lower number of samples than from permanent sensors, but there is greater flexibility in setting the locations of the monitoring stations.…”

Section: Travel Time Data Sourcesmentioning

confidence: 99%

Performance Measures for Traffic Signal Systems: An Outcome-Oriented Approach

Day¹,

Bullock²,

Li³

et al. 2014

View full text Add to dashboard Cite

PERFORMANCE MEASURES FOR TRAFFIC SIGNAL SYSTEMS:AN OUTCOME-ORIENTED APPROACH This monograph is a synthesis of research carried out on traffic signal performance measures based on highresolution controller event data, assembled into a methodology for performance evaluation of traffic signal systems. High-resolution data consist of a log of discrete events such as changes in detector and signal phase states. A discussion is provided on the collection and management of the signal event data and on the necessary infrastructure to collect these data. A portfolio of performance measures is then presented, focusing on several different topics under the umbrella of traffic signal systems operation. System maintenance and asset management is one focus. Another focus is signal operations, considered from the perspectives of vehicle capacity allocation and vehicle progression. Performance measures are also presented for nonvehicle modes, including pedestrians, and modes that require signal preemption and priority features. Finally, the use of travel time data is demonstrated for evaluating system operations and assessing the impact of signal retiming activities.

show abstract

“…For this study, the travel times between different points were of interest, as well as the origin-destination characteristics [3] revealed by comparing numbers of matches across different points in the system. Before getting into those details, however, it is interesting to briefly review the results of the matching process.…”

Section: Matching Characteristicsmentioning

confidence: 99%

Traffic Performance of Arterial Highways and Driver Routing Characteristics during a Freeway Detour

Day¹,

Lavrenz²,

Li³

et al. 2017

View full text Add to dashboard Cite

The temporary closure of a section of northbound I-65 between Indianapolis and Chicago had an enormous impact on the roadways where traffic was detoured. This paper examines the impacts of that closure on arterial highways in rural and suburban settings. Vehicle re-identification travel times are used to investigate route choice decisions and the performance of the detour route, while high-resolution controller data is used to examine the quality of progression for a special signal timing plan designed to handle the detour traffic. The route choice analysis shows that about 60% of traffic stayed on the official detour, while 40% used two alternative routes. The three alternative routes had similar median travel times, while one of the two alternatives had much more variability in the travel times. Distributions of travel time and delay per segment were used to examine where delay occurred on the detour route. Most of the delay was attributable to turning movements in rural sections where traffic had to merge into a single lane, while the delay in the signalized portion of the detour route was relatively low. High-resolution data was used to examine the quality of progression in that section in more detail; finding that the signal control policy successfully progressed traffic in the northbound direction along the roadway, and also partially benefited the southbound direction.

show abstract

Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles

Cited by 68 publications

References 6 publications

A Robust Method for Real Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors

A Robust Method for Real Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors

Performance Measures for Traffic Signal Systems: An Outcome-Oriented Approach

Traffic Performance of Arterial Highways and Driver Routing Characteristics during a Freeway Detour

Contact Info

Product

Resources

About