Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment

Flooding can severely disrupt transportation systems. When safety measures are limited to road closures, vehicles affected by the flooding have an origin, destination, or path segment that is closed or soon-to-be flooded during the trip's duration. This thesis introduces a framework to provide...

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Main Author: Hannoun, Gaby Joe
Other Authors: Civil and Environmental Engineering
Format: Others
Published: Virginia Tech 2017
Subjects:
Online Access:http://hdl.handle.net/10919/79911
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-799112020-09-29T05:39:43Z Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment Hannoun, Gaby Joe Civil and Environmental Engineering Heaslip, Kevin Patrick Murray-Tuite, Pamela Marie Hancock, Kathleen L. flooding routing assistance connected vehicles in-vehicle navigation systems Flooding can severely disrupt transportation systems. When safety measures are limited to road closures, vehicles affected by the flooding have an origin, destination, or path segment that is closed or soon-to-be flooded during the trip's duration. This thesis introduces a framework to provide routing assistance and trip cancellation recommendations to affected vehicles. The framework relies on the connected vehicle environment for real-time link performance measures and flood data and evaluates the trip of the vehicle to determine whether it is affected by the flood or not. If the vehicle is affected and can still leave its origin, the framework generates the corresponding routing assistance in the form of hyperpath(s) or set of alternative paths. On the other hand, a vehicle with a closed origin receives a warning to wait at origin, while a vehicle with an affected destination is assigned to a new safe one. This framework is tested on two transportation networks. The evaluation of the framework's scalability to different network sizes and the sensitivity of the results to various flood characteristics, policy-related variables and other dependencies are performed using simulated vehicle data and hypothetical flood scenarios. The computation times depends on the network size and flood depth but have generally an average of 1.47 seconds for the largest tested network and deepest tested flood. The framework has the potential to alleviate the impacts and inconveniences associated with flooding. Master of Science 2017-11-02T08:00:24Z 2017-11-02T08:00:24Z 2017-11-01 Thesis vt_gsexam:13253 http://hdl.handle.net/10919/79911 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic flooding
routing assistance
connected vehicles
in-vehicle navigation systems
spellingShingle flooding
routing assistance
connected vehicles
in-vehicle navigation systems
Hannoun, Gaby Joe
Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
description Flooding can severely disrupt transportation systems. When safety measures are limited to road closures, vehicles affected by the flooding have an origin, destination, or path segment that is closed or soon-to-be flooded during the trip's duration. This thesis introduces a framework to provide routing assistance and trip cancellation recommendations to affected vehicles. The framework relies on the connected vehicle environment for real-time link performance measures and flood data and evaluates the trip of the vehicle to determine whether it is affected by the flood or not. If the vehicle is affected and can still leave its origin, the framework generates the corresponding routing assistance in the form of hyperpath(s) or set of alternative paths. On the other hand, a vehicle with a closed origin receives a warning to wait at origin, while a vehicle with an affected destination is assigned to a new safe one. This framework is tested on two transportation networks. The evaluation of the framework's scalability to different network sizes and the sensitivity of the results to various flood characteristics, policy-related variables and other dependencies are performed using simulated vehicle data and hypothetical flood scenarios. The computation times depends on the network size and flood depth but have generally an average of 1.47 seconds for the largest tested network and deepest tested flood. The framework has the potential to alleviate the impacts and inconveniences associated with flooding. === Master of Science
author2 Civil and Environmental Engineering
author_facet Civil and Environmental Engineering
Hannoun, Gaby Joe
author Hannoun, Gaby Joe
author_sort Hannoun, Gaby Joe
title Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
title_short Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
title_full Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
title_fullStr Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
title_full_unstemmed Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
title_sort framework for better routing assistance for road users exposed to flooding in a connected vehicle environment
publisher Virginia Tech
publishDate 2017
url http://hdl.handle.net/10919/79911
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