The Impact of Traffic Incident Locations on a Metropolitan Evacuation

Bahaaldin, Karzan; Fries, Ryan; Chowdhury, Mashrur

doi:10.14257/ijt.2016.4.2.06

Cited by 4 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results were satisfactory and queue lengths visually matched in all locations without the need for further calibration. Details can be found in the author's previous work [56]. These results showed that the process of calibration and validation was satisfactory as described in previously established methods [66,68].…”

Section: Model Calibration and Validationsupporting

confidence: 64%

“…It was found from previous literature that some of these parameters such as CC0 (standstill distance), CC1 (headway time), and CC2 ("following" variation) had higher impacts on the results while other parameters such as CC3 (threshold for entering "following") had less influence [64,65]. Further information about the calibration of this model can be found in Bahaaldin et al [56].…”

Section: Model Calibration and Validationmentioning

confidence: 97%

See 1 more Smart Citation

A Case Study on the Impacts of Connected Vehicle Technology on No-Notice Evacuation Clearance Time

Bahaaldin

Fries

Bhavsar

et al. 2017

Journal of Advanced Transportation

Self Cite

View full text Add to dashboard Cite

No-notice evacuations of metropolitan areas can place significant demands on transportation infrastructure. Connected vehicle (CV) technology, with real-time vehicle to vehicle and vehicle to infrastructure communications, can help emergency managers to develop efficient and cost-effective traffic management plans for such events. The objectives of this research were to evaluate the impacts of CVs on no-notice evacuations using a case study of a downtown metropolitan area. The microsimulation software VISSIM was used to model the roadway network and the evacuation traffic. The model was built, calibrated, and validated for studying the performance of traffic during the evacuation. The researchers evaluated system performance with different CV penetration rates (from 0 to 30 percent CVs) and measured average speed, average delays, and total delays. The findings suggest significant reductions in total delays when CVs reached a penetration rate of 30 percent, albeit increases in delays during the beginning of the evacuation. Additionally, the benefits could be greater for evacuations that last longer and with higher proportions of CVs in the vehicle stream.

show abstract

Section: Model Calibration and Validationsupporting

confidence: 64%

Section: Model Calibration and Validationmentioning

confidence: 97%

A Case Study on the Impacts of Connected Vehicle Technology on No-Notice Evacuation Clearance Time

Bahaaldin

Fries

Bhavsar

et al. 2017

Journal of Advanced Transportation

Self Cite

View full text Add to dashboard Cite

show abstract

“…The total network delay for each scenario was compared by using VISSIM simulator. Bahaaldin [33] used traffic micro-simulation software VISSIM to identify the locations where traffic incidents can significantly increase durations during a no-notice evacuation, so as to guide the operation engineers to focus on traffic incident management resources during evacuations. Liang [34] used VISSIM to simulate hurricane evacuation traffic in New Orleans, as to better understand evacuation behavior of mass evacuation in urban areas.…”

Section: Literature Reviewmentioning

confidence: 99%

Traffic Flow Catastrophe Border Identification for Urban High-Density Area Based on Cusp Catastrophe Theory: A Case Study under Sudden Fire Disaster

Lin

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

For traffic management under sudden disasters in high-density areas, the first and foremost step is to prevent traffic congestion in the disaster-affected area by traffic flow management and control, so as to provide enough and flexible traffic capacity for emergency evacuation and emergency rescue. Catastrophe border identification is the foundation and the key to traffic congestion prediction under sudden disaster. This paper uses a mathematical model to study the regional traffic flow in the high-density area under sudden fire disaster based on the Cusp Catastrophe Theory (CCT). The catastrophe border is identified by fitting the CCT-based regional traffic flow model to explore the stable traffic flow changing to the instable state, as to provide a theoretical basis for traffic flow management and control in disaster-affected areas, and to prevent the traffic flow being caught into disorder and congestion. Based on VISSIM simulator data by building simulation scenarios with and without sudden fire disaster in a Sudoku traffic network, the catastrophe border is identified as 439 pcu/lane/h, 529 pcu/lane/h, 377 pcu/lane/h at 5 s, 10 s, 15 s data collection interval in a Sudoku traffic network respectively. The corresponding relative precision, which compares to the method of Capacity Assessment Approach (CAA), is 89.1%, 92.7% and 76.5% respectively. It means that 10 s data collection interval would be the suitable data collection interval in catastrophe border identification and regional traffic flow control in high-density area under sudden fire disaster.

show abstract