Heuristic approach in a multimodal travel planner to support local authorities in urban traffic management

Sierpiński, Grzegorz; Staniek, Marcin

doi:10.1016/j.trpro.2017.12.027

Cited by 11 publications

(9 citation statements)

References 9 publications

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“…The data analysis can also produce insights that serve as input for other purposes, such as the improvement of transport service according to users' needs [42], the promotion of changes of users' habits [40] (e.g., the adoption of greener and healthier solutions [13]), and the improvement of journey planners and transport portals, considering their usability and the services they offer [10,45].…”

Section: Related Workmentioning

confidence: 99%

Matching User Preferences and Behavior for Mobility

Basile¹,

Consonni

Manca

et al. 2020

Proceedings of the 31st ACM Conference on Hypertext and Social Media

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Understanding user mobility is central to develop better transport systems that answer users' needs. Users usually plan their travel according to their needs and preferences; however, different factors can influence their choices when traveling. In this work, we model users' preferences, and we match their actual transport use. We use data coming from a mobility platform developed for mobile devices, whose aim is to understand the value of users' travel time. Our first goal is to characterize the perception that users have of their mobility by analyzing their general preferences expressed before their travel time. Our approach combines dimensionality reduction and clustering techniques to provide interpretable profiles of users. Then, we perform the same task after monitoring users' travels by doing a matching between users' preferences and their actual behavior. Our results show that there are substantial differences between users' perception of their mobility and their actual behavior: users overestimate their preferences for specific mobility modes, that in general, yield a lower return in terms of the worthwhileness of their trip.

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Section: Related Workmentioning

confidence: 99%

Matching User Preferences and Behavior for Mobility

Basile¹,

Consonni

Manca

et al. 2020

Proceedings of the 31st ACM Conference on Hypertext and Social Media

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“…This approach endeavors to provide unimodal route guidance to car-only commuters. In another example, Green Travelling Planner represents a multimodal travel planner that combines 11 modes of commuting using a heuristic approach and commuters' travel needs [14]. However, the proposed tool does not use the multi-agent architecture, restricting its scalability and flexibility.…”

Section: Introductionmentioning

confidence: 99%

“…The works discussed in [14,50,52,53] focused on overcoming traffic management issues by deploying centralized architectures. Other works, e.g., [14,50], relied on travel time estimations calculated from historical datasets and did not use live traffic data. These solutions [14,52] did not consider the congestion cost (e.g., carbon emissions) for promoting sustainable travel.…”

mentioning

confidence: 99%

“…Other works, e.g., [14,50], relied on travel time estimations calculated from historical datasets and did not use live traffic data. These solutions [14,52] did not consider the congestion cost (e.g., carbon emissions) for promoting sustainable travel. Finally, the offered solutions [52,53] did not offer a mobile app to guide commuters through the optimum route.…”

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confidence: 99%

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An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

et al. 2021

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The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.

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“…In recent years, in Poland, a number of scientific papers have been published on electromobility and electric vehicles (e.g. [1][2][3][4][5][6][7]). According to the Law on electromobility and alternative fuels of 11 th January 2018 (JoL 2018 item 317) [8], Polish cities are required to develop electromobility plans.…”

Section: Introductionmentioning

confidence: 99%

E-mobility Infrastructure in the Górnośląsko - Zagłębiowska Metropolis, Poland, and Potential for Development

Macioszek¹

2019

World Congress on New Technologies

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Electromobility is a set of activities related to the use of electric vehicles, as well as technical and operational EV solutions, technologies and charging infrastructure, as well as social, economic and legal issues pertaining to the designing, manufacturing, purchasing and using electric vehicles. The article presents results of the survey on e-mobility infrastructure in the Górnośląsko-Zagłębiowska Metropolis, Poland, and potential for development.

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Heuristic approach in a multimodal travel planner to support local authorities in urban traffic management

Cited by 11 publications

References 9 publications

Matching User Preferences and Behavior for Mobility

Matching User Preferences and Behavior for Mobility

An Eco-Friendly Multimodal Route Guidance System for Urban Areas Using Multi-Agent Technology

E-mobility Infrastructure in the Górnośląsko - Zagłębiowska Metropolis, Poland, and Potential for Development

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