Browsing by Author "Abi Aad, Mirla"
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- Evaluating Responses to Contraflow for Hurricane EvacuationAbi Aad, Mirla (Virginia Tech, 2018-01-24)The very high travel demands associated with hurricane evacuations require some strategies, such as contraflow sections, to be included in hurricane evacuation plans. However, the response or reaction of the evacuees to these strategies has not been given much attention in the past. This study concentrated on one particular strategy, contraflow segments, and investigated evacuees' willingness to use them through an animated survey. Usable data was collected from 821 respondents. The first part of the study dealt with six factors (service availability, police presence, exit location, entry congestion, availability of multiple entries, and limited choice) which were studied independently and compared against individual background characteristics. The distribution of the responses from the survey indicated that the presence of multiple entries or the availability of information about services increased the likelihood of evacuees switching to contraflow lanes, while the presence of police personnel for instance did not greatly alter the decision. Other factors like entry congestion or exits well before or well after initially desired ones decreased the willingness to use contraflow lanes. In the case where contraflow lanes were the only option on the main evacuation route (without the regular lane alternative), evacuees were willing to take detours to avoid the use of contraflow facilities. However, the effects of the above listed factors were associated with the background characteristics of the evacuees as the odds ratios in this study indicated. Previous contraflow or reverse lane experience for instance attenuated the effect of entry congestion on avoiding contraflow lanes. Contraflow experience on the other hand increased the likelihood of using the first entry when two entries were available and increased the willingness to switch to contraflow lanes when information about services was provided. Also, evacuation experience, presence of passengers affecting stops, and having dependents in the family improved the willingness to use contraflow lanes given information about services. Other characteristics like living in a hurricane prone area increased the inclination to use contraflow in the presence of police personnel and having passengers affecting destination choice increased the willingness to detour and avoid contraflow when regular lanes were not part of the main evacuation route from the respondent's origin. The second part of the study dealt with congestion and information about congestion levels along the regular and contraflow lanes. Different combinations of levels of congestion and information were presented to the respondents in the animated part of the survey. Respondents indicated their preference for contraflow or regular lanes in these scenarios. This data was used to develop a conditional logit model which predicted choice based on the presented options. Evacuees demonstrated an overall willingness to switch to contraflow lanes when these lanes were less congested than the regular lanes. However, with similar congestion levels on the regular and contraflow lanes, willingness to switch to contraflow lanes decreased as congestion levels increased. Information about upcoming congestion influenced evacuees' route choice decisions. Information motivated switching to contraflow lanes when conveying better downstream conditions along these lanes. Overall, evacuees demonstrated a willingness to benefit from any congestion improvement offered by contraflow lanes as opposed to assumptions in the literature claiming underutilization of these segments due to drivers' discomfort and unfamiliarity.
- Infrastructure Condition Assessment and Prediction under Variable Traffic Demand and Management ScenariosAbi Aad, Mirla (Virginia Tech, 2022-11-08)Departments of Transportation (DOTs) are responsible for keeping their road network in a state of good repair while also aiming to reduce congestion through the implementation of different traffic control and demand management strategies. These strategies can result in changes in traffic volume distributions, which in turn affect the level of pavement deterioration due to traffic loading. To address this issue, this dissertation introduces an integrated simulation-optimization framework that accounts for the combined effects of pavement conditions and traffic management decision-making strategies. The research focuses on exploring the range of possible performance outcomes resulting from this integrated modeling approach. The research also applied the developed framework to a particular traffic demand management strategy and assessed the impact of dynamic tolls around the specific site of I-66 inside the beltway. The integrated traffic-management/pavement-treatment framework was applied to address both the operational and pavement performance of the network. Aimsun hybrid macro/meso dynamic user equilibrium experiments were used to simulate the network with a modified cost function taking care of the dynamic pricing along the I-66 tolled facility. Furthermore, the framework was expanded to include the development of a systematic and comprehensive methodology to optimize the allocation of networkwide pavement treatment work zones over space and time. The proposed methodology also contributed to the development of a surrogate function that reduces the optimization computation burden so that researchers would be able to conduct work zone allocation optimization without having to run expensive simulation work. Finally, in this dissertation, a user-friendly decision-support tool was developed to assist in the pavement treatment and project selection planning process. We use machine learning models to encapsulate the simulation optimization process.