A Hybrid Learning Approach to Stochastic Routing

Simon Aagaard Pedersen; Bin Yang; Christian S. Jensen

A Hybrid Learning Approach to Stochastic Routing

Simon Aagaard Pedersen, Bin Yang, Christian S. Jensen

Research output: Contribution to conference without publisher/journal › Poster › Communication

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Abstract

Emerging disruptive innovations in transportation, e.g., autonomous vehicles and transportation-as-a-service, will benefit from high-resolution routing, where travel-time uncertainty is captured accurately.

Original language	English
Publication date	2019
Number of pages	1
Publication status	Published - 2019
Event	Kick-off: AI for the people - Rendsburggade 14, Aalborg, Denmark Duration: 19 Nov 2019 → 19 Nov 2019

Other

Other	Kick-off: AI for the people
Location	Rendsburggade 14
Country/Territory	Denmark
City	Aalborg
Period	19/11/2019 → 19/11/2019

Keywords

Transportation
Road networks
Artificial Intelligence

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1 PhD thesis

Towards Efficient Stochastic Routing in Road Networks
Pedersen, S. A., 2022
Research output: PhD thesis

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@conference{77d92dfeaa79402a81d95ae396f1953a,

title = "A Hybrid Learning Approach to Stochastic Routing",

abstract = "Emerging disruptive innovations in transportation, e.g., autonomous vehicles and transportation-as-a-service, will benefit from high-resolution routing, where travel-time uncertainty is captured accurately.",

keywords = "Transportation, Road networks, Artificial Intelligence",

author = "Pedersen, {Simon Aagaard} and Bin Yang and Jensen, {Christian S.}",

year = "2019",

language = "English",

note = "Kick-off: AI for the people ; Conference date: 19-11-2019 Through 19-11-2019",

}

TY - CONF

T1 - A Hybrid Learning Approach to Stochastic Routing

AU - Pedersen, Simon Aagaard

AU - Yang, Bin

AU - Jensen, Christian S.

PY - 2019

Y1 - 2019

N2 - Emerging disruptive innovations in transportation, e.g., autonomous vehicles and transportation-as-a-service, will benefit from high-resolution routing, where travel-time uncertainty is captured accurately.

AB - Emerging disruptive innovations in transportation, e.g., autonomous vehicles and transportation-as-a-service, will benefit from high-resolution routing, where travel-time uncertainty is captured accurately.

KW - Transportation

KW - Road networks

KW - Artificial Intelligence

M3 - Poster

T2 - Kick-off: AI for the people

Y2 - 19 November 2019 through 19 November 2019

ER -

A Hybrid Learning Approach to Stochastic Routing

Abstract

Other

Keywords

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Research output

Towards Efficient Stochastic Routing in Road Networks

Cite this