Estimating freeway traffic measures from mobile phone location data

Gao, Hongyan; Liu, Fasheng

doi:10.1016/j.ejor.2013.02.044

Cited by 32 publications

(10 citation statements)

References 9 publications

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“…With field studies on connected vehicle testbeds, there is a growing body of literature that involve PV data to estimate travel times, traffic speeds, flow, and density (Hellinga and Fu (1999); Fu and Hellinga (2000); Kwella and Lehmann (2000); Chen and Chien (2000); Cheu et al (2002); Cetin et al (2005);Lin et al (2008); Sohn and Hwang (2008); Liu and Ma (2009); Kianfar and Edara (2010); Calabrese et al (2011); Gao and Liu (2013); Feng et al (2014); Seo et al (2015)). These traffic parameters are rather direct from PVs compared to delays and QLs which require statistical inference.…”

Section: Literature Reviewmentioning

confidence: 99%

Queue length estimation from probe vehicles at isolated intersections: Estimators for primary parameters

Comert

2016

European Journal of Operational Research

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This paper develops estimators for market penetration level and arrival rate in finding queue lengths from probe vehicles at isolated traffic intersections. Closed-form analytical expressions for expectations and variances of these estimators are formulated. Derived estimators are compared based on squared error losses. Effect of number of cycles (i.e., short-term and long-term performances), estimation at low penetration rates, and impact of combinations of derived estimators on queue length problem are also addressed. Fully analytical formulas with unknown parameters are derived to evaluate how queue length estimation errors change with respect to percent of probe vehicles in the traffic stream. Developed models can be used for the real-time cycle-to-cycle estimation of the queue lengths by inputting some of the fundamental information that probe vehicles provide (e.g., location, time, and count). Models are evaluated using VISSIM microscopic simulations with different arrival patterns. Numerical experiments show that the developed estimators are able to point the true arrival rate values at 5% probe penetration level with 10 cycles of data. For low penetrations such as 0.1%, large number of cycles of data is required by arrival rate estimators which are essential for overflow queue and volume-to-capacity ratios. Queue length estimation with tested parameter estimators is able to provide cycle-to-cycle errors within ±5% of coefficient of variations with less than 5 cycles of probe data at 0.1% penetration for all arrival rates used.

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Section: Literature Reviewmentioning

confidence: 99%

Queue length estimation from probe vehicles at isolated intersections: Estimators for primary parameters

Comert

2016

European Journal of Operational Research

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“…By comparing profiles with travel survey statistics, they demonstrated validation potential of the call detail records for this purpose. Gao and Liu [69] used the clustering technique to identify whether different phones travel in the same vehicle. They used mobile phone data to determine speed, vehicle counts, type, and density.…”

Section: Call Detail Record and Network Signalization Datamentioning

confidence: 99%

Sensing Human Activity for Smart Cities’ Mobility Management

Šemanjski¹,

Gautama²

2016

Smart Cities Technologies

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Knowledge about human mobility patterns is the key element towards efficient mobility management. Traditionally, these data are collected by paper/phone household surveys or travel diaries and serve as input for transportation planning models. In this chapter, we report on current state-of-the-art techniques for sensing human activity and report on their applicability for smart city mobility management purposes. We particularly focus on the use of location-enabled devices and their potential towards replacing traditional data collection approaches. Furthermore, to illustrate applicability of smartphones as ubiquitous sensing devices we report on the use of Routecoach application that was used for mobility data collection in the city of Leuven, Belgium. We provide insights into lessons learned, ways in which collected data were used by different stakeholders, and identify existing gaps and future research needs in this field.

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“…Alternative related studies have also been conducted. Gao and Liu (2013) attempted to examine the methods used to estimate traffic measures using information from mobile phones, accounting for the fact that each vehicle likely contains more than one phone because of the popularity of mobile phones. Steenbruggen et al (2015) used mobile phone data to provide new spatio-temporal tools for improving urban planning and reducing inefficiencies in current urban systems.…”

Section: Studies On Using Mobile Phone Location Datamentioning

confidence: 99%

Toward utilizing mobile phone users’ location data in tourism

Yamamoto

2016

JGTR

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This study aims to identify the number of visitors in different periods and their characteristics based on the location data of mobile phone users collected by the mobile phone company. The sites studied in this survey are tourist destinations in Ishikawa Prefecture and Toyama city, including Kanazawa city, which became nationally popular after the Hokuriku Shinkansen opened in 2015. The opening of the Hokuriku Shinkansen brought more visitors to many areas. However, it also led to fewer visitors in some other areas. Its positive effect was remarkable in Kanazawa.

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Estimating freeway traffic measures from mobile phone location data

Cited by 32 publications

References 9 publications

Queue length estimation from probe vehicles at isolated intersections: Estimators for primary parameters

Queue length estimation from probe vehicles at isolated intersections: Estimators for primary parameters

Sensing Human Activity for Smart Cities’ Mobility Management

Toward utilizing mobile phone users’ location data in tourism

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