Use of Advanced Traveler Information Systems for Route Choice: Interpretation Based on a Bayesian Model

Liao, Chun-Hsiung; Chen, Chun-Wei

doi:10.1080/15472450.2014.936289

Cited by 15 publications

(7 citation statements)

References 35 publications

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“…information about the location, traffic regulations, routes, emergency services, safety, and warning measures to the traveler's [67]. TIS is meant to offer more precise information for travelers, thereby reducing the various hurdle in real-time [68]. TIS is a combination of technologies like WWW and GIS [69].…”

Section: • Traveler Information System (Tis): Tis Offersmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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Internet of Things (IoT) is an integration of the Sensor, Embedded, Computing, and Communication technologies. The purpose of the IoT is to provide seamless services to anything, anytime at any place. IoT technologies play a crucial role everywhere, which brings the fourth revolution of disruptive technologies after the internet and Information and Communication Technology (ICT). The Research & Development community has predicted that the impact of IoT will be more than the internet and ICT on society, which improves the wellbeing of society and industries. Addressing the predominant system-level design aspects like energy efficiency, robustness, scalability, interoperability, and security issues result in the use of a potential IoT system. This paper presents the current state of art of the functional pillars of IoT and its emerging applications to motivate academicians and researches to develop real-time, energy-efficient, scalable, reliable, and secure IoT applications. This paper summarizes the architecture of IoT, with the contemporary status of IoT architectures. Highlights of the IoT system-level issues to develop more advanced real-time IoT applications have been discussed. Millions of devices exchange information using different communication standards, and interoperability between them is a significant issue. This paper provides the current status of the communication standards and application layer protocols used in IoT with the detailed analysis. The computing paradigms like Cloud, Cloudlet, Fog, and Edge computing facilitate IoT with various services like data offloading, resource and device management, etc. In this paper, an exhaustive analysis of Edge Computing in IoT with different edge computing architectures and existing status are deliberated. The widespread adoption of IoT in society has resulted in privacy and security issues. This paper emphasizes on analyzing the security challenges, privacy and security threats, conventional mitigation techniques, and further scope for IoT security. The features like fewer memory footprints, scheduling, real-time task execution, fewer interrupt, and thread switching latency of Real-Time Operating Systems (RTOS) enables the development of time critical IoT applications. Also, this review offers the analysis of the RTOS's suitable for IoT with the current status and networking stack. Finally, open research issues in IoT system development are discussed.

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Section: • Traveler Information System (Tis): Tis Offersmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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“…Almost all ATIS platforms or other intelligent transportation system (ITS) applications are built based on UE (Antoniou et al, 2015;Bifulco et al, 2014;Karimi & Asavasuthirakul, 2014;Liao & Chen, 2015;Toledo & Beinhaker, 2006;Tsirimpa, 2015), which assumes all the drivers have perfect information about traffic conditions and make the optimal decision independently based on their own interests. In contrast, SO requires a system to have control over all vehicles' routing decisions and to make decisions to minimize the system total travel time as a whole, which makes it more difficult to implement.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Not all users have access to SO information and also not all are able to, or willing to, comply with the SO principle, as suggested in Ng and Sathasivan (2014) and Liao and Chen (2015), which studied the traveler's response to traffic information provided. While assuming all users are SO compliant is unrealistic, one can still exploit the opportunity to have only a fraction of total drivers be SO compliant, if they are motivated to do so.…”

Section: Downloaded By [Hkust Library] At 19:19 31 May 2016mentioning

confidence: 99%

Development of a behaviorally induced system optimal travel demand management system

Chiu

Shelton

2016

Journal of Intelligent Transportation Systems

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active traffic and demand management (ATDM); behaviorally induced system optimal; dynamic traffic assignment; system optimal; travel behaviour; travel demand management (TDM) ABSTRACTThe basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This "passive" way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, system optimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.

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“…Ren et al [24], Huang et al [25], and Sun et al [26] divided travelers into two groups according to whether they assembled the advanced traffic information system (ATIS). Zhong et al [27], Liao and Chen [28], and Zhong et al [29] studied the route choice behavior in the ATIS context.…”

Section: Introductionmentioning

confidence: 99%

Unified Framework for Optimal Routing Choice under Guidance Information

Sun

et al. 2018

Complexity

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In order to satisfy the diverse demand of travel service in the context of big data, this paper puts forward a unified framework for optimal routing choice under guidance information. With consideration of the influence of big data, the scenario analysis of routing choice is implemented, and the routing choice under guidance information is discussed. The optimal routing choice problem is abstracted into the collaboration optimization model of travel route choice, departure time choice, and travel mode choice. Based on some basic assumptions, the collaboration optimization model is formulated as a variational inequality model. The method of successive averages is applied to solve the proposed model. A case study is carried out to verify the applicability and reliability of the model and algorithm.

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Use of Advanced Traveler Information Systems for Route Choice: Interpretation Based on a Bayesian Model

Cited by 15 publications

References 35 publications

An Empirical Study on System Level Aspects of Internet of Things (IoT)

An Empirical Study on System Level Aspects of Internet of Things (IoT)

Development of a behaviorally induced system optimal travel demand management system

Unified Framework for Optimal Routing Choice under Guidance Information

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