Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment
dc.contributor.author | Hannoun, Gaby Joe | en |
dc.contributor.committeechair | Heaslip, Kevin Patrick | en |
dc.contributor.committeechair | Murray-Tuite, Pamela Marie | en |
dc.contributor.committeemember | Hancock, Kathleen L. | en |
dc.contributor.department | Civil and Environmental Engineering | en |
dc.date.accessioned | 2017-11-02T08:00:24Z | en |
dc.date.available | 2017-11-02T08:00:24Z | en |
dc.date.issued | 2017-11-01 | en |
dc.description.abstract | 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. | en |
dc.description.abstractgeneral | Flooding is a natural hazard that occurs with heavy rainfalls and high tides. In extreme situations, a flood in an area results in the evacuation of its occupant. Yet, in many cases, a flood is less severe and may only result in roads closures without necessitating evacuation. During these situations, and as transportation engineers, our ultimate goal is to maintain efficient and safe traffic operations. This thesis introduces a framework that focuses on providing routing assistance to affected vehicles and sending warnings to unaffected ones. It relies on the future connected vehicle environment which enables the communication between a traffic management center and equipped vehicles. The traffic management center collects and processes the information about the link performance measures and the weather and flood forecasts and sends them to the connected vehicles. Each vehicle has an in-vehicle navigation system in which the proposed framework is embedded. The framework, depending on the vehicle’s origin, destination, path and departure time and based on the flood’s characteristics, determines whether the vehicle is affected or not. If the vehicle is unaffected, it will receive a warning with the areas to avoid in case of any deviation and it can resume its trip as intended. If affected, the vehicle will either receive a warning to stay at its origin or routing guidance in the form of hyperpath or a set of alternative paths. The proposed framework has been evaluated on two transportation networks modeled in VISSIM based on the city of Virginia Beach, VA. Using simulated vehicle data and generated flood scenarios, several tests were executed to evaluate the scalability of the framework to different transportation networks along with the sensitivity of the results to variation in flood characteristics, policy-dependent variables and other dependencies. Concentrated, more intense and deeper floods resulted in a higher impact on the system. Yet, the analysis of the output is highly dependent on the location of the origin and destination of the vehicles with respect to the flooded roads. Thus, a lot of the output explanation are specific. Computation time increased with the increase in network size and in the flood depth. Nevertheless, it is still small and reasonable and further increase in both parameters (network size and flood depth) can be tested in future along with multiple techniques that minimize the computation time. This framework addresses the flooding hazard which road users are experiencing more and more nowadays. This hazard brings risks and inconveniences to our daily life. Thus, the development of this framework is of great interest to our society as it is a promising tool that has the potential to offer benefits, in terms of safety and mobility, to roads users exposed to a flood hazard. Its first implementation shows that it is a timely application with a potential to perform even better with future improvements. | en |
dc.description.degree | Master of Science | en |
dc.format.medium | ETD | en |
dc.identifier.other | vt_gsexam:13253 | en |
dc.identifier.uri | http://hdl.handle.net/10919/79911 | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | flooding | en |
dc.subject | routing assistance | en |
dc.subject | connected vehicles | en |
dc.subject | in-vehicle navigation systems | en |
dc.title | Framework for better Routing Assistance for Road Users exposed to Flooding in a Connected Vehicle Environment | en |
dc.type | Thesis | en |
thesis.degree.discipline | Civil Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | masters | en |
thesis.degree.name | Master of Science | en |
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