Route choice behaviour and travel information in a congested network: Static and dynamic recursive models

Ramos, Giselle de Moraes; Mai, Tien; Daamen, Winnie; Frejinger, Emma; Hoogendoorn, Serge P.

doi:10.1016/j.trc.2020.02.014

Cited by 39 publications

(10 citation statements)

References 52 publications

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“…Our methods can be used with other recursive models developed in the literature, e.g., the dynamic RL (de Moraes Ramos et al, 2020) or stochastic time-dependent RL (Mai et al, 2021) models, and may have applications beyond route choice modeling, for example, the estimation of activity-based models or general structural dynamic discrete choice models with missing data.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Recursive Route Choice Models with Incomplete Trip Observations

Mai¹,

Bui²,

Nguyen³

et al. 2022

SSRN Journal

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Section: Discussionmentioning

confidence: 99%

Estimation of Recursive Route Choice Models with Incomplete Trip Observations

Mai¹,

Bui²,

Nguyen³

et al. 2022

SSRN Journal

Self Cite

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“…Navigation systems were developed to provide specific route guidance exploiting the information about traffic regulations (e.g., road works and lane directions). Navigation systems are able to determine the best paths among destinations (customers to serve) according to the average configuration of the road network (e.g., average link travel time according to time of days (DfT, 2010;De Moraes Ramos et al, 2020;Kessler et al, 2021).…”

Section: Problem Definitionmentioning

confidence: 99%

Emerging Information and Communication Technologies: the Challenges for the Dynamic Freight Management in City Logistics

Comi

Russo

2022

Front. Future Transp.

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Recently, the evolution of emerging information and communication technologies (e-ICTs) has opened the road for developing and implementing new integrated and dynamic city logistics solutions and subsequently for identifying new frontiers of intelligent transport systems (ITSs). The study evolves pointing out the different city logistics groups of actors and their reciprocal interactions in relation to the considered new technologies (i.e., internet of things, block chain, big data, and artificial intelligence), which allow actors to increase their utility exploiting the advancement of current intelligent transport systems. The changes in the generalized path costs supported by each stakeholder are explored, and the modifications guided by e-ICTs are analyzed. The learning process due to the update for within-day and day-to-day dynamics is detailed and formalized. In this way, the current formulation of the classical transport problem (vehicle routing and scheduling) and the new one (pushed from the growth of ecommerce, i.e., courier routing) are explored under the light of the new knowledge derived from the use of e-ICTs. Novelty of the study mainly comprises the analysis of each emerging ICT group and of the formalization, in the classical transport system models (TSM), of the new knowledge for each actor group.

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“…For trajectory data acquired by sensors, researchers have proposed a dynamic discrete choice framework for route choice modelling. For instance, de Moraes Ramos et al constructed static and dynamic recursive logit model to interpret the influence of travel information on route choice behaviour based on GPS tracker data [42]. In recent years, machine learning has become a new approach to route choice modelling [43].…”

Section: Modellingmentioning

confidence: 99%

Influence of smartphone traffic application information on drivers’ route choice behaviours

et al. 2022

IET Intelligent Trans Sys

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The active traffic management system disseminates traffic information to drivers to guide their route choice, so as to alleviate traffic congestion. Most drivers are highly dependent on mobile navigation APP, and the display form of mobile navigation information is of great importance. In order to improve drivers’ compliance with guidance information, this research accommodates for information that disseminate time attribute (when to provide the traffic information) and display format attribute (voice navigation or not, flat map or three‐dimensional [3D] map) and also explores the interaction effects between individual and trip characteristics. A revealed preference (RP) and stated preference (SP) survey consisting of 831 respondents is conducted in Nanjing, China. Then three kinds of panel logit model are established to fit the survey data. According to the model results, it is found that drivers with aggressive style are more sensitive to travel time, and drivers who are familiar with the road network are more sensitive to the 3D map with voice navigation format. The results of parameter estimation are also used for the trade‐off analysis of various exogenous variables. The findings of this study provide useful insights for the development of mobile navigation APPs, personalized path recommendation and congestion pricing strategies.

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Route choice behaviour and travel information in a congested network: Static and dynamic recursive models

Cited by 39 publications

References 52 publications

Estimation of Recursive Route Choice Models with Incomplete Trip Observations

Estimation of Recursive Route Choice Models with Incomplete Trip Observations

Emerging Information and Communication Technologies: the Challenges for the Dynamic Freight Management in City Logistics

Influence of smartphone traffic application information on drivers’ route choice behaviours

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