Route Choice With Real Time Information
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Route Choice With Real Time Information
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Author : Eran Ben-Elia
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2011-03
Route Choice With Real Time Information written by Eran Ben-Elia and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03 with categories.
In recent years information systems are being designed to assist people to make more efficient travel choices under conditions of growing uncertainty. Although travel demand modelers have analyzed the response to real-time information, usually this has been done under the questionable assumptions of rational decision-making. In reality, people can make completely different choices when their decisions are based on information or on experience. Improving behavioral assumptions could well increase the realism of transport demand models. This book describes an experimental approach to study route choice with real-time information. It provides both researchers and practitioners with valuable knowledge on the roles of information and learning in travel behavior and how statistics and state-of-the art discrete choice models can be applied to analyze and model travel behavior in risky and uncertain environments. This book will be especially useful to transportation policy makers and analysts, researchers and students.
Behavioral Insights In Route Choice Models With Real Time Information
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Author : Eran Ben-Elia
language : en
Publisher:
Release Date : 2007
Behavioral Insights In Route Choice Models With Real Time Information written by Eran Ben-Elia and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Route Choice Behavior Of Freeway Travelers Under Real Time Traffic Information Provision Application Of The Best Route And The Habitual Route Choice Mechanisms
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Author : Rong-Chang Jou
language : en
Publisher:
Release Date : 2005
Route Choice Behavior Of Freeway Travelers Under Real Time Traffic Information Provision Application Of The Best Route And The Habitual Route Choice Mechanisms written by Rong-Chang Jou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Automobile driving on highways categories.
Adaptive Route Choice In Stochastic Time Dependent Networks
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Author : Jing Ding-Mastera
language : en
Publisher:
Release Date : 2016
Adaptive Route Choice In Stochastic Time Dependent Networks written by Jing Ding-Mastera and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Transportation networks are inherently uncertain due to random disruptions; meanwhile, real-time information potentially helps travelers adapt to realized traffic conditions and make better route choices under such disruptions. Modeling adaptive route choice behavior is essential in evaluating Advanced Traveler Information Systems (ATIS) and related policies to better provide travelers with real-time information. This dissertation contributes to the state of the art by estimating the first latent-class routing policy choice model using revealed preference (RP) data and providing efficient computer algorithms for routing policy choice set generation. A routing policy is defined as a decision rule applied at each link that maps possible realized traffic conditions to decisions on the link to take next. It represents a traveler's ability to look ahead in order to incorporate real-time information not yet available at the time of decision. A case study is conducted in Stockholm, Sweden and data for the stochastic time-dependent network are generated from hired taxi Global Positioning System (GPS) traces through the methods of map-matching and non-parametric link travel time estimation. A latent-class Policy Size Logit model is specified with two additional layers of latency in the measurement equation. The two latent classes of travelers are policy users who follow routing policies and path users who follow fixed paths. For the measurement equation of the policy user class, the choice of a routing policy is latent and only its realized path on a given day can be observed. Furthermore, when GPS traces have relatively long gaps between consecutive readings, the realized path cannot be uniquely identified. Routing policy choice set generation is based on the generalization of path choice set generation methods, and utilizes efficient implementation of an optimal routing policy (ORP) algorithm based on the two-queue data structure for label correcting. Systematic evaluation of the algorithm in random networks as well as in two large scale real-life networks is conducted. The generated choice sets are evaluated based on coverage and adaptiveness. Coverage is the percentage of observed trips included in the generated choice sets based on a certain threshold of overlapping between observed and generated routes, and adaptiveness represents the capability of a routing policy to be realized as different paths over different days. It is shown that using a combination of methods yields satisfactory coverage of 91.2%. Outlier analyses are then carried out for unmatching trips in choice set generation. The coverage achieves 95% for 100% threshold after correcting GPS errors and breaking up trips with intermediate stops, and further achieves 100% for 90% threshold. The latent-class routing policy choice model is estimated against observed GPS traces based on the three different sample sizes resulting from coverage improvement, and the estimates appear consistent across different sample sizes. Estimation results show the policy user class probability increases with trip length, and the latent-class routing policy choice model fits the data better than a single-class path choice model or routing policy choice model. This suggests that travelers are heterogeneous in terms of their ability and willingness to plan ahead and utilize real-time information. Therefore, a fixed path model as commonly used in the literature may lose explanatory power due to its simplified assumptions on network stochasticity and travelers' utilization of real-time information.
Travelers Route Choice Behavior In Risky Networks
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Author : Hengliang Tian
language : en
Publisher:
Release Date : 2013
Travelers Route Choice Behavior In Risky Networks written by Hengliang Tian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Automobile drivers categories.
The accurate modeling of travelers route choice decision making when faced with unreliable (risky) travel times is necessary for the assessment of policies aimed at improving travel time reliability. Two major objectives are studied in this thesis. The first objective is to evaluate the applicability of a process model to route choice under risk where the actual process of decision making is captured. Traditionally, we adopt "as-if" econometric models to predict peoples route choice decisions. The second objective is to investigate travelers capability to incorporate future real-time traffic information into their current route choice decision making. Two separate stated preference (SP) surveys were conducted for each objective. The first SP survey used an interactive map in a computer based test. The second SP survey used a full-scale high-fidelity driving simulator. Compared with econometric models, process models have been rarely investigated in travel decision making under risk. A process model aims to describe the actual decision making procedure and could potentially provide a better explanation to route choice behavior. A process model, Priority Heuristic (PH), developed by Brandstatter et al. (2006) is introduced to the travel choice context and its probabilistic version, Probabilistic Priority Heuristic (PPH), is developed and estimated in this study. With data collected from a stated preference (SP) survey which is based on an animated computer interface, one econometric model, Rank-Dependent Expected Utility (RDEU) model, and two other alternative models were compared with the PPH model in a cross validation test to investigate their data-fitting and predictive performance. Our results show that the PPH model outperforms the RDEU model in both data-fitting and predictive performance. This suggests that the process modeling paradigm could be a promising new area in travel behavior research. With the advance of information and telecommunication technology, real-time traffic information is increasingly more available to help travelers make informed route choice decisions when faced with unreliable travel times. A strategic route choice refers to a decision taking into account future diversion possibilities at downstream nodes based on real-time information not yet available at the time of decision-making. Based on the data collected from a driving simulator experiment and a matching PCbased experiment, a mixed Logit model with two latent classes, strategic and nonstrategic route choice, is specified and estimated. The estimates of the latent class probabilities show that a significant portion of route choice decisions are strategic and subjects can learn to make more strategic route choice as they have more experience with the decision scenarios. Non-parametric tests additionally show that network complexity adversely affects travelers strategic thinking ability in a driving simulator environment but not in a PC environment and a parallel driving task only affects strategic thinking ability in a difficult scenario but not a simple one. In addition, we find that peoples strategic thinking ability are influenced by their gender and driving experience (mileage) in the non-parametric analysis, but not in the modeling work. These findings suggest that a realistic route choice model with real-time traffic information should consider both strategic and non-strategic behavior, which vary with the characteristics of both the network and the driver.
Route Choice Behavior In A Driving Simulator With Real Time Information
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Author : Hengliang Tian
language : en
Publisher:
Release Date : 2010
Route Choice Behavior In A Driving Simulator With Real Time Information written by Hengliang Tian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Automobile driving simulators categories.
Decision Field Theoretical Analysis And Modelling Of Dynamic Route Choice Deliberation Process
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Author : Hoda M. Talaat
language : en
Publisher:
Release Date : 2008
Decision Field Theoretical Analysis And Modelling Of Dynamic Route Choice Deliberation Process written by Hoda M. Talaat and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Automobile drivers categories.
Intelligent Transportation Systems applications require a thorough understanding of drivers' route choice behaviour in a complex network under real-time information. This research attempts to describe and model route choice behaviour at the disaggregate individual level and from a psychological decision-making process perspective. We base our proposed behavioural route choice theory and model of the drivers' mental deliberation process on the scientifically-sound Decision Field Theory (DFT). DFT is a process-oriented modelling ground of individuals' decision making that simulates the evolution of preferences during deliberation. Laboratory experiments are conducted that expose human subjects to realistic network and traffic conditions while monitoring and recording their route choices under varying experimental conditions. Recorded data are used for analyzing drivers' route choices and for the development and calibration of a DFT-based route choice theory and framework. A simple "mixed reality" simulator is developed to serve as an experimentation platform. The mixed reality platform enables a driver to use a Backpedal steering device to navigate through a microscopic simulation model of the waterfront portion of downtown Toronto. Analysis results reveal the significance of the impacts of some situational factors (e.g. information content, information reliability, and inertia effects), and some personal factors (e.g. gender differences), on drivers' route choice attitudes. Estimation of the DFT route choice model parameters is performed based on the experimental observations. Genetic algorithms are used as the optimization tool to calibrate model parameters and minimize the discrepancy between model output and observed behaviour. The developed DFT model is used to study the impact of time pressure constraints on drivers' compliance behaviour. Variations in impact trends are estimated with varying information characteristics (form and reliability). Finally, an alternative structural-oriented parameter estimation methodology is adopted for comparative purposes. In the structural-oriented methodology, the deliberation time dimension is completely ignored during the estimation of the model parameters. Analysis results reveal the superiority of the process-oriented DFT route choice model in improving the credibility of route choice predictions. Furthermore, the developed DFT model contributes to enhancing the understanding of the impact and the influence mechanisms of personal/situational factors on drivers' route choice attitudes.
Intelligent Transportation Related Complex Systems And Sensors
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Author : Kyandoghere Kyamakya
language : en
Publisher: MDPI
Release Date : 2021-09-01
Intelligent Transportation Related Complex Systems And Sensors written by Kyandoghere Kyamakya and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Technology & Engineering categories.
Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems.
Determinants Of Route Choice And Value Of Traveler Information
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Author : Lei Zhang
language : en
Publisher:
Release Date : 2011
Determinants Of Route Choice And Value Of Traveler Information written by Lei Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Drivers receive value from traveler information in several ways, including the ability to save time, but perhaps more important is the value of certainty as it affects other personal, social, safety, or psychological factors. This information can be economically valued. The benefit of reduction in driver uncertainty when information is provided at the beginning of the trip is the main variable measured in this research. User preferences for routes were assessed as a function of the presence and accuracy of information while controlling for other trip and route attributes. Data were collected in a field experiment in which 113 drivers, given real-time travel time information with varying degrees of accuracy, drove four alternative routes between a preselected origin - destination pair in the Twin Cities, Minnesota, metropolitan area. Ordinary regression, multinomial, and rank-ordered logit models produced estimates of the value of information with some variation. Results showed that travelers were willing to pay up to $1 per trip for pre-trip travel-time information. The value of information is higher for commute and event trips and when congestion on the usual route is heavier. The accuracy of the traveler information was also a crucial factor. Travelers will not pay for information unless they perceive it to be accurate. Most travelers (70%) prefer that such information be provided free by the public sector, whereas some (19%) believe that it is better for the private sector to provide such service at a charge.
Route Choice Behavior In Risky Networks With Real Time Information
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Author : Michael D. Razo
language : en
Publisher:
Release Date : 2010
Route Choice Behavior In Risky Networks With Real Time Information written by Michael D. Razo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Real-time rendering (Computer graphics) categories.