2013 Session: 486

• Identifying Chosen Public Transport Connections from GPS Observations
  Abstract: Transport planners around the world are currently searching for innovative strategies for customer-friendly and efficient public transport systems. An important element in this process is the understanding of the passengers' valuation of different elements of public transport trips. One challenge associated with this the observation of the actual passenger behaviour in all its complexity. One way to address this challenge is to use person-based GPS devices for observing the public transport connections chosen by passengers. GPS-based studies have become increasingly popular in the last two decades and their advantages for observing and modelling car and bicycle route choice have been shown by many studies. However, for public transport connection choice modelling the processing routines to extract the chosen connections and their relevant attributes have so far been missing.This paper reports on a first implementation of such a procedure called "public transport map-matching". The basic idea is to first employ a car map-matching procedure for each stage of a public transport trip to determine the route within the public transport network. Then, this route is used to find the most likely public transport line and the respective boarding and alighting stops. Finally, the stages of the public transport trip are joined together including the access and egress stages by walk or bicycle. The procedure is tested using the data from an ongoing GPS study in Zurich - an area in Switzerland with a very dense public transport network.
  Authors: Rieser-Schüssler, Nadine; Axhausen, Kay W.
  Authors: Rieser-Schüssler, Nadine; Axhausen, Kay W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-0588
• Robust Method for Real-Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors
  Abstract: The collection and provision of real time information to passengers is a key issue on current cities for both, traffic managers and travelers. This paper presents a novel methodology for estimating travel times in dense urban road networks using point-to-point detectors. The aim is to fill in the existing gap related to the weakness of existing travel time estimation methodologies, which take into account point-to-point detector devices. Bluetooth is considered as one of the less expensive technologies for estimating travel times, but while on the one hand travel times data collection can be considered as easy, data filtering and data correction require a demanding methodology, 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 MAC addresses for estimating the travel times, especially in dense urban zones, where three main error sources exist: the existence of different modes (private vehicles, pedestrians, buses, bicycle etc.), the existence of more than one possible path between two bluetooth detector devices and the existence of stops or trips ending between two bluetooth devices, creating outliers that need to be identified and discarded. The results of the methodology confirm that outliers are eliminated, as shown by a case study involving 10 Bluetooth detectors, installed at major intersections of Thessaloniki’s central business district. The presented methodology is useful for application related to real-time data provision to advanced traveler information services as well as to underlying traffic models.
  Authors: Mitsakis, Evangelos; Salanova Grau, Josep-Maria; Chrisohoou, Evangelia Ch.; Aifadopoulou, Georgia
  Authors: Mitsakis, Evangelos; Salanova Grau, Josep-Maria; Chrisohoou, Evangelia Ch.; Aifadopoulou, Georgia
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3654
• Estimating Dynamic Workplace Capacities Using Public Transport Smart Card Data, Travel Diary Survey, and Land Use Information
  Abstract: The number and spatial distribution of work locations is a crucial piece of information for any transport demand model. To generate the initial transport demand of MATSim, an activity-based multi-agent simulation framework, it is necessary to determine the number of work locations with high spatial resolution, either on a parcel or even a building level. Commonly applied methods to derive work locations are based on census of entreprises information, unemployment insurance database or combine information of buildings gross floor area and individual work space requirements. As an alternative, we present a methodology which combines public transport smart card transaction data, travel diary survey and building information data sources.Work activities are detected from public transport smart card transactions based on observed activity duration and start time and hence related to public transport stops. To link the observed work activities to individual buildings, a linear programming optimisation technique is applied that minimises the walking time between public transport stops and potential work locations. Information on maximum allowed building gross floor area derived from land use regulation is combined with estimates on individual work space requirements to set boundary conditions and ensure that buildings are only assigned with work activities according to its maximal capacity. To account for private transport based work activities, mode shares as observed in a travel diary are taken into account. Due to the limited number of observations of such surveys, this inflation process is performed on the level of specifically generated mode share zones. To demonstrate the applicability, the proposed approach is implemented for the case of Singapore and the results of this case study critically reviewed.
  Authors: Ordóñez Medina, Sergio; Erath, Alexander
  Authors: Ordóñez Medina, Sergio; Erath, Alexander
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3683
• Robustness and Computational Efficency of Kalman Filter Estimator of Time-Dependent Origin-Destination Matrices Exploiting ICT Traffic Measurements
  Abstract: Origin-Destination (OD) trip matrices, which describe the patterns of traffic behavior across the network, are the primary data input used in principal traffic models and therefore, a critical requirement in all advanced systems that are supported by Dynamic Traffic Assignment models. However, because OD matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts which are provided by an existing layout of traffic counting stations. The availability of new traffic measurements provided by ICT applications allows more efficient algorithms, namely for the real-time estimation of OD matrices based on modified Kalman Filtering approaches exploiting the new data. The quality of the estimations depends on various factors, like the penetration of the ICT devices, the detection layout and the quality of the initial information. Concerning the feasibility of real-time applications, another key aspect is the computational performance of the proposed algorithms for urban networks of sensitive size. This paper presents the results of a set of computational experiments with a microscopic simulation of a network of the business district of Barcelona, which explore the sensitivity of the Kalman Filter estimates with respect to the values of the design factors, and its computational performance.
  Authors: Barceló, Jaume; Montero, Lidia; Bullejos, Manuel; Linares, Mari Paz; Serch, Oriol
  Authors: Barceló, Jaume; Montero, Lidia; Bullejos, Manuel; Linares, Mari Paz; Serch, Oriol
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3919
• UbiActive: Smartphone-Based Tool for Trip Detection and Travel-Related Physical Activity Assessment
  Abstract: Utilizing the computing, communication, and sensing capabilities of smartphones, we developed an Android phone application—named UbiActive—to monitor travel behavior, assess travel-related physical activity, and generate daily activity summaries for smartphone users. We tested the application in the lab setting on three types of Android phones including HTC Magic, HTC MyTouch 4G, and SamSung Nexus S, as well as among a small group of real smartphone users who used a wide range of Android phones. Results from the tests confirmed that UbiActive worked well in collecting real-time travel behavior and physical activity data, assessing travel-related physical activity, and making participants more aware of their travel behavior and travel-related physical activity. The tests also revealed rooms for improvement when it came to UbiActive’s trip detection function and its impact on batter consumption. All of these findings provide useful insights into future improvement of UbiActive and other smartphone-based applications.
  Authors: Fan, Yingling; Chen, Qian; Liao, Chen-Fu; Douma, Frank
  Authors: Fan, Yingling; Chen, Qian; Liao, Chen-Fu; Douma, Frank
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-4250
  Practice-Ready: Yes
• Identifying Chosen Public Transport Connections from GPS Observations
  Authors: Rieser-Schüssler, Nadine
  Authors: Rieser-Schüssler, Nadine
  Year: 2013
  Document Type: Presentation
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-0588
• UbiActive: Smartphone-Based Tool for Trip Detection and Travel-Related Physical Activity Assessment
  Authors: Fan, Yingling
  Authors: Fan, Yingling
  Year: 2013
  Document Type: Presentation
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-4250
• Robustness and Computational Efficency of Kalman Filter Estimator of Time-Dependent Origin-Destination Matrices Exploiting ICT Traffic Measurements
  Authors: Barceló, Jaume
  Authors: Barceló, Jaume
  Year: 2013
  Document Type: Presentation
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3919
• Robust Method for Real-Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors
  Authors: Mitsakis, Evangelos
  Authors: Mitsakis, Evangelos
  Year: 2013
  Document Type: Presentation
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3654
• Estimating Dynamic Workplace Capacities Using Public Transport Smart Card Data, Travel Diary Survey, and Land Use Information
  Authors: Ordóñez Medina, Sergio
  Authors: Ordóñez Medina, Sergio
  Year: 2013
  Document Type: Presentation
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3683