Abstract
Bluetooth (BT) time-stamped media access control (MAC) address data have been used for traffic studies worldwide. Although Bluetooth (BT) technology has been widely recognised as an effective, low-cost traffic data source in freeway traffic contexts, it is still unclear whether BT technology can provide accurate travel time (TT) information in complex urban traffic environments. Therefore, this empirical study aims to systematically evaluate the accuracy of BT travel time estimates in urban arterial contexts. There are two major hurdles to deriving accurate TT information for arterial roads: the multiple detection problem and noise in BT estimates. To date, they have not been fully investigated, nor have well-accepted solutions been found. Using approximately two million records of BT time-stamped MAC address data from twenty weekdays, this study uses five different BT TT-matching methods to investigate and quantify the impact of multiple detection problems and the noise in BT TT estimates on the accuracy of average BT travel times. Our work shows that accurate Bluetooth-based travel time information on signalised arterial roads can be derived if an appropriate matching method can be selected to smooth out the remaining noise in the filtered travel time estimates. Overall, average-to-average and last-to-last matching methods are best for long (>1 km) and short (≤1 km) signalised arterial road segments, respectively. Furthermore, our results show that the differences between BT and ground truth average TTs or speeds are systematic, and adding a calibration is a pragmatic method to correct inaccurate BT average TTs or speeds. The results of this research can help researchers and road operators to better understand BT technology for TT analysis and consequently to optimise the deployment location and configuration of BT MAC address scanners.
Highlights
Accurate travel time (TT) or speed measures, such as average TTs or average travel speeds, are critical for road operators to monitor, evaluate, and manage the performance of a road network, and for road users to make well-informed route choices [1, 2]
A typical 4 phase can be identified from these 96 time sets; phase1, roughly from 23:00–06:00, when the traffic volume was quite low, the MAC-to-volume ratio (MtVR) was subject to the penetration rate, stationary media access control (MAC) addresses, traffic signal settings, and multiple BT devices of a vehicle; phase 2, from 06:00–08:00, the traffic volume was significantly increasing, the MtVR decreased because the stationary MAC addresses’ impact was weakening and the proportion of discoverable BT devices that have not been captured was increasing; phase 3, from 08:00–18:00, the MtVR fluctuated in a narrow range, indicating the fluctuation of traffic volume and the reach of the capacity of a BT MAC address scanners (BMSs); and phase 4, from 18:00–23:00, the traffic volume was decreasing, causing the MtVR decreases
To evaluate the accuracy of BT travel time measures, this study investigated the following factors: the multiple detection problem and TT estimate noise. rough the development and implementation of the methods in a case study, the following three issues were identified
Summary
Accurate travel time (TT) or speed measures, such as average TTs or average travel speeds, are critical for road operators to monitor, evaluate, and manage the performance of a road network, and for road users to make well-informed route choices [1, 2]. BT traffic monitoring systems rely on the identification of unique BT media access control (MAC) addresses of in-vehicle discoverable BT devices, such as onboard stereos, hands-free kits, and global positioning system (GPS) navigation modules Because of their low capital and installation costs, BT MAC address scanners (BMSs) can be installed on a massive scale at critical locations of a road network, such as signalised intersections along arterial roads, to detect MAC addresses at different times and locations [11] and provide network-wide performance indicators in real time [12].
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