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inproceedings by Abdullah Kurkcu

This paper developed a methodology to relate passenger data collected by Wi-Fi and Bluetooth sens... more This paper developed a methodology to relate passenger data collected by Wi-Fi and Bluetooth sensors to scheduled bus departures for the purpose of studying passenger arrival behavior. One major advantage of using these sensors is their simplicity and cost. For stations at which AFC systems are not available, wireless sensors can easily be deployed. The developed Wi-Fi and Bluetooth sensors require are simple to operate, easily transported, and require minimal maintenance. The results pointed out that passenger arrival times at a transit stop are sensitive to the service frequency as it proposed in the literature. Furthermore, Wi-Fi and Bluetooth sensors can be a cost-effective alternative to understanding further and analyze the probabilistic distribution of passenger arrivals and wait times for stops and services where automated passenger data are not available to decision makers and researchers.

Data visualization tool for monitoring transit operation and performance, 2017

Using the automated vehicle location data combined with other technologies such as automated inci... more Using the automated vehicle location data combined with other technologies such as automated incident reporting, transit decision makers can now execute a variety of real-time strategies and performance evaluations. In this study, we show that it is possible to develop an easy to use but powerful web-based tool which acquires, stores, processes, and visualizes bus trajectory data. The developed web-based tool makes it easy for the end users to access stored data and to query it without any delay or external help. Moreover, the tool allows the users to conduct a series of data visualization and analysis operations demonstrating the potential of a such web-based tool for future applications.

This is an on-going study that explores the potential benefits of using pedestrian data for evalu... more This is an on-going study that explores the potential
benefits of using pedestrian data for evaluation and
enhancement of public transportation. The research team
proposes the utilization of Bluetooth (BT) andWiFi technologies
to estimate time-dependent origin-destination (OD) demands
and station wait-times of transit bus and subway users. The
detection approach and a complete system design developed
by the research team is discussed in this paper. Preliminary
results from multiple pilot field studies, that were conducted at
some of the major New York City (NYC) public transportation
facilities, are also presented. The main objective of this study is
to inquire into the various ways this extensive transit rider data
can be used and to establish a general framework through datadriven
pedestrian modeling within transit stations that renders
estimation of key parameters and strategic control of public
transportation services possible.

techreports by Abdullah Kurkcu

Faced with growing number of work zones, the challenge for transportation agencies is to effectiv... more Faced with growing number of work zones, the challenge for transportation agencies is to effectively
manage the impacts of work zones to alleviate congestion and maintain the safety of motorists without
disrupting project schedules. Coordinating work zone activities and improving communication among
agencies have already been practiced by various State DOTs and transportation agencies.
The main objective of this study is to understand the types of projects that can be coordinated and to
evaluate the effectiveness of coordinating short and long-term projects using a cost-benefit analysis
approach to measure the efficiency of various combinations of projects relative to each other and the
status quo.
For this purpose the research team conducted an extensive literature review, determined the state of
practice in other State DOTs and conducted interviews with NJDOT staff to investigate the types of
projects undertaken by NJDOT and if there were already any practice of work zone coordination on NJ
roadways. The team, after consulting with the project panel and the NJDOT Mobility and Systems
Engineering division, devised a work zone coordination framework that utilizes one common work zone
database, including OpenReach and Capital Program Management (CPM) Project Reporting System
(PRS) databases.
Work Zone Coordination Spreadsheet (WCS) tool was developed for providing NJDOT with an easy-touse
tool to evaluate the feasibility and effectiveness of coordinating short and long term work zones and
measure the benefits of various combinations of projects relative to each other and the status quo. This
on-line tool is implemented with a web-based user interface. It integrates all scheduled and active
construction projects from the OpenReach database and planned CPM projects from project reporting
system (PRS) database. It then identifies conflicts between work zone projects and estimates the benefits
of conflict mitigation

The main objective of this project is to develop and conduct limited testing of novel sensors us... more The main objective of this project is to develop and conduct limited testing of novel sensors using Bluetooth technology
(BT) to estimate OD demands and station wait times for users of public transit stations. The NYU research team tested the
feasibility of the utilization of sensors with Bluetooth technology to estimate Origin-Destination (OD) demands and station waittimes
of users of transit systems with a focus on subway systems. For example, if the entrance and exit turnstiles at subway stations
were equipped with this type of sensors, it is possible to capture OD information for some of the riders with activated devices.
Estimation of daily and hourly Origin-Destination (OD) demands and delays is important for transit agencies because it
can help improve their operations, reduce delays, and mitigate cost, among other benefits. The proposed method of tracking
Bluetooth IDs uses inexpensive, small, and easy to deploy wireless detectors / readers with specialized software developed by the
research team. This is a low-cost and viable alternative to traditionally used surveys or other advanced technologies.
Following a literature review and device testing, a series of one-day pilot tests are conducted in coordination with the
MTA to iron out all of the possible hardware and software issues. Following further consultation with the MTA, a full one day to
one week indoor tests are conducted with continuous data collection and monitoring to assess the feasibility and usefulness of longterm
data collection using the proposed sensor technology. Two software tools to post process the collected data and to perform
self-diagnosis and remote data acquisition functions are developed as part of the overall research project. The results and
recommendations are provided to the MTA and other interested transit agencies.

articles by Abdullah Kurkcu

Monitoring nonmotorized traffic is gaining more attention in the context of transportation studie... more Monitoring nonmotorized traffic is gaining more attention in the context of transportation studies. Most of the traditional pedestrian monitoring technologies focus on counting pedestrians passing through a fixed location in the network. It is thus not possible to anonymously track the movement of individuals or groups as they move outside each particular sensor’s range. Moreover, most agencies do not have continuous pedestrian counts mainly because of technological limitations. Wireless data collection technologies, however, can capture crowd dynamics by scanning mobile devices. Data collection that takes advantage of mobile devices has gained much interest in the transportation literature as a result of its low cost, ease of implementation, and richness of the captured data. In this paper, algorithms to filter and aggregate data collected by wireless sensors are investigated, as well as how to fuse additional data sources to improve the estimation of various pedestrian-based performance measures. Procedures to accurately filter the noise in the collected data and to find pedestrian flows, wait times, and counts with wireless sensors are presented. The developed methods are applied to a 2-month-long collection of public transportation terminal data carried out with the use of six sensors. Results point out that if the penetration rate of discoverable devices is known, then it is possible to accurately estimate the number of pedestrians, pedestrian flows, and average wait times in the detection zone of the developed sensors.

This paper investigates the learning behavior of users of State Road 167 high-occupancy toll lane... more This paper investigates the learning behavior of users of State Road 167 high-occupancy toll lanes by use of toll transaction data collected over a 6-month period. The Bayesian stochastic learning algorithm theory was used to model drivers' sequential lane choice decisions. Reward and penalty parameters were used to update users' lane choice probabilities. The results showed that the effect of reward parameters that increased the probability of selection of an alternative after a satisfactory experience was more obvious than the effect of penalty parameters that decreased the probability of selection of an unfavorable choice. Low magnitudes of learning parameters might indicate strong habit formation of users. Moreover, the posterior distributions of learning parameters indicated that user perception heterogeneity existed when the outcomes of choices were evaluated. Finally, user familiarity was investigated with a subsample of less experienced users, and it was shown that the learning rates of more familiar users were lower than those of less familiar users.

The fundamental contribution of this paper is the development of an extended virtual sensor frame... more The fundamental contribution of this paper is the development of an extended virtual sensor framework to provide an automated travel time data collection method as incidents occur. In addition, social media data can be useful for more effective real-time incident response. The proposed framework can easily be modified and used to evaluate travel time effects of incidents on roadways and clearance times and to make use of social media data in obtaining time-critical incident-related information.

Recent advances in mobile networks and an increase in the number of GPS-equipped vehicles have le... more Recent advances in mobile networks and an increase in the number of GPS-equipped vehicles have led to exponential growth in real-time data generation. In the past decade, several online mapping and vehicle tracking services have made their data available to third-party users. This paper explores opportunities for use of real-time traffic data provided by online services and introduces a virtual sensor methodology for collecting, storing, and processing large volumes of network-level data. To assess the validity of the collected data with the proposed methodology, this paper compares these data with data from physical loop detectors and electronic toll tag readers. Statistical analyses show a strong correlation between the travel time measurements from infrastructurebased sensors and virtual sensors. A travel time reliability analysis is then conducted with the virtual sensor data methodology. The results are promising for future research and implementation.

This study aims to explore the potential of using big data in advancing the pedestrian risk analy... more This study aims to explore the potential of using big data in advancing the pedestrian risk analysis including the investigation of contributing factors and the hotspot identification. Massive amounts of data of Manhattan from a variety of sources were collected, integrated, and processed, including taxi trips, subway turnstile counts, traffic volumes, road network, land use, sociodemographic, and social media data. The whole study area was uniformly split into grid cells as the basic geographical units of analysis. The cell-structured framework makes it easy to incorporate rich and diversified data into risk analysis. The cost of each crash, weighted by injury severity, was assigned to the cells based on the relative distance to the crash site using a kernel density function. A tobit model was developed to relate gridcell-specific contributing factors to crash costs that are left-censored at zero. The potential for safety improvement (PSI) that could be obtained by using the actual crash cost minus the cost of "similar" sites estimated by the tobit model was used as a measure to identify and rank pedestrian crash hotspots. The proposed hotspot identification method takes into account two important factors that are generally ignored, i.e., injury severity and effects of exposure indicators. Big data, on the one hand, enable more precise estimation of the effects of risk factors by providing richer data for modeling, and on the other hand, enable large-scale hotspot identification with higher resolution than conventional methods based on census tracts or traffic analysis zones.

Papers by Abdullah Kurkcu

Procedia Computer Science

Transportation Research Record: Journal of the Transportation Research Board

The prioritization of maintenance activities in bridges has great importance in bridge asset mana... more The prioritization of maintenance activities in bridges has great importance in bridge asset management systems as they are mentioned in MAP-21. One of the most commonly used prioritization methodologies in bridge management systems is multi-attribute utility theory process. In this study, the problem is defined as using the additive functional form in this process without testing additive independence (AI) assumption, which is one of the properties of multi-attribute utility theory. This study aims to emphasize the strength of the use of multiplicative functional forms when the multiplicative form is proven to be more appropriate by AI assumption test. To demonstrate this vital point, mathematical expressions are derived for the feasible regions of indifference curves. Then, the optimum region for both additive and multiplicative approaches are calculated using these analytical expressions to demonstrate the difference between the two relation to maximizing utility. This comparison...

Data visualization tool for monitoring transit operation and performance, 2017

Procedia Computer Science

Transportation Research Record: Journal of the Transportation Research Board