Travel time studies with global positioning and geographic information systems: an integrated methodology

Quiroga, Cesar; Bullock, Darcy M.

doi:10.1016/s0968-090x(98)00010-2

Cited by 211 publications

(90 citation statements)

References 7 publications

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“…A vehicle equipped with a Bluetooth device traveling along the freeway is logged and time stamped at time t 1 by the sensor at location 1. After traveling a certain distance is logged and time stamped again at time t 2 by the sensor at location 2. The difference in time stamps τ = t 2 -t 1 measures the travel time of the vehicle equipped with that mobile device, and obviously the speed assuming the distance between both locations is known.…”

Section: Capturing Traffic Data With Bluetooth Sensorsmentioning

confidence: 99%

Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

Barceló

Mercadé

Marqués

et al. 2010

Transportation Research Record: Journal of the Transportation R

180

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From the point of view of the information supplied by an ATIS to the motorists entering a freeway of one of the most relevant is the Forecasted Travel Time, that is the expected travel time that they will experience when traverse a freeway segment. From the point of view of ATMS the dynamic estimates of time dependencies in OD matrices is a major input to dynamic traffic models used for estimating the current traffic state and forecasting its short term evolution. Travel Time Forecasting and Dynamic OD Estimation are two of the key components of ATIS/ATMS and the quality of the results that they could provide depend not only on the quality of the models but also on the accuracy and reliability of the measurements of traffic variables supplied by the detection technology.The quality and reliability of the measurements produced by traditional technologies, as inductive loop detectors, is not usually the required by real-time applications, therefore one wonders what could be expected from the new ICT technologies as for example Automatic Vehicle Location, License Plate Recognition, detection of mobile devices and so on. The main objectives of this paper are: to explore the quality of the data produced by the Bluetooth detection of mobile devices equipping vehicles for Travel Time Forecasting and its use to estimate time dependent OD matrices. Ad hoc procedures based on Kalman Filtering have been designed and implemented successfully and the numerical results of the computational experiments are presented and discussed.

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Section: Capturing Traffic Data With Bluetooth Sensorsmentioning

confidence: 99%

Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

Barceló

Mercadé

Marqués

et al. 2010

Transportation Research Record: Journal of the Transportation R

180

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“…Collection of travel time data at any location can be done by various techniques mentioned in the literature, such as global positioning and geographic information technology (Quiroga, 1998), probe vehicle data (Chen and Chien 2001), support vector regression (Chun- Hsin et al 2004), GPSinstrumented test vehicles (Hunter et al 2006), and vehicular ad-hoc networks (Arbabi and Weigle 2009). However, such advanced methods of data collection are rarely used in developing countries because of the associated strain on financial resources.…”

Section: Data: Requirements and Collection Techniquesmentioning

confidence: 99%

An Integrated Framework for Allocation of New Emergency Response Facilities in Developing Nations

Basu

Aggarwal

Jana

2017

Process Integr Optim Sustain

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Developing countries are majorly resourceconstrained societies which do not have the financial power to invest in meeting all infrastructure needs. Although there are multiple types of emergency response systems (ERS), the most important ones are the basic essentials-fire, medical and police. Along with emergency response planning for man-made emergencies in an urban scenario, there is a gap in the recent literature about integration of basic ERS into a single framework. We propose a novel framework that first evaluates the existing ERS in place and then provides solutions for improvement with the inclusion of additional facilities at optimal locations. Keeping in mind dynamic congestion patterns and land use resource constraints in different areas of the urban space, the proposed facilities are labeled as either permanent or floating. We also propose three different schemes, each with two competing strategies that cater to a specific type of constraint common to developing nations. Through comparison of system performance metrics like first response time, area coverage, and average response time, the ERS pre-and postimplementation of the framework are compared to check for degree of improvement. A case study of the framework is shown using the city of Chandigarh in India as an example. The framework proposed in the paper takes into account the growth and compactness of urban spaces and can be used to continually assess and improve ERS in mixed use urban spaces after fixed periods of time.

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“…They send their current position and speed to a processing server on a regular basis [1]- [4]. The main advantage of this technique is the accuracy of the measurements and the wide geographical coverage.…”

Section: Related Workmentioning

confidence: 99%

“…Quiroga and Bullock [1] relied on sampling theory to conclude that the minimum sample interval is at most half the segment travel time. For highways they propose a segment length of 0.2 miles in combination with a sample interval of 6 seconds.…”

Section: Related Workmentioning

confidence: 99%

Feasibility of expanding traffic monitoring systems with floating car data technology

Vandenberghe

Vanhauwaert

Verbrugge

et al. 2012

IET Intell. Transp. Syst.

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Travel time studies with global positioning and geographic information systems: an integrated methodology

Cited by 211 publications

References 7 publications

Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring

An Integrated Framework for Allocation of New Emergency Response Facilities in Developing Nations

Feasibility of expanding traffic monitoring systems with floating car data technology

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