A simulation-based approach to provide insights on Hyperloop network operations

Rajendran, Suchithra; Harper, Aidan

doi:10.1016/j.trip.2020.100092

Cited by 23 publications

(15 citation statements)

References 31 publications

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“…In terms of operation, Hyperloops are comparable to a subway system but have lesser stops within a city. A typical Hyperloop system would have passenger capsules going in either direction inside two tubes of diameter 2.23 m. A pod would travel at a maximum speed of 750 mph and accommodate 28 passengers (Dudnikov, 2017;Rajendran and Harper, 2020). In contrast, a subway car has a capacity of approximately 54 seated commuters (Rajendran and Harper, 2020).…”

Section: Hyperloop Systemmentioning

confidence: 99%

“…A typical Hyperloop system would have passenger capsules going in either direction inside two tubes of diameter 2.23 m. A pod would travel at a maximum speed of 750 mph and accommodate 28 passengers (Dudnikov, 2017;Rajendran and Harper, 2020). In contrast, a subway car has a capacity of approximately 54 seated commuters (Rajendran and Harper, 2020). Irrespective of capacity constraints, Hyperloop would drastically reduce the travel time between two cities.…”

Section: Hyperloop Systemmentioning

confidence: 99%

“…Several recent studies have focussed on the operational side of the hyperloop network. For instance, Rajendran and Harper (2020) developed a simulation model to analyze the impact of parameters, such as the total number of pods, pod capacity and demand variability, between San Francisco (SF) and Los Angeles (LA). Voltes-Dorta and Becker (2018) investigated the effect of establishing this service on airports in SF and LA using an exploratory analysis.…”

Section: Hyperloop Systemmentioning

confidence: 99%

“…However, not every flight would be expected to function at 100% capacity. Therefore, the estimated upper limit was then multiplied by a parameter defined in the literature as the commuter variability (CVV <1) to generate an hourly rate table (Rajendran and Harper, 2020).…”

Section: Data Descriptionmentioning

confidence: 99%

“…For the baseline setting, we set the seating capacity of Hyperloop to be 28 passengers in a single ride, whereas a single HSR vehicle can carry a maximum of 480 commuters, based on prior research. The commuter volume variability (CV) was assumed to be 0.8 from a previous literature (Rajendran and Harper, 2020). Based on the grid search method, the number of Hyperloop pods in the system is set at 30.…”

Section: Baseline Casementioning

confidence: 99%

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A study on emerging transportation services based on efficient network design and operation

Sinha¹

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Rapid growth in modern technologies has provided new tools for flexible and convenient transportation to the public. These new avenues for commuting would enable promoting non-driving modes of conveyance while shifting the economics of movement via traditional methods such as cars, subways, buses, etc. These innovative services would be advantageous in reducing dependability on privately-owned vehicles, thereby reducing the impact on the environment while providing a faster mode of travel. They would also play a crucial role in decreasing bottleneck due to heavy traffic, which has a detrimental impact on people's health, lifestyle and productivity. Thus, logistic companies are aiming towards making use of emerging technologies, such as air taxis and hyperloop, for facilitating efficient transportation in the near future. In this dissertation, a unique two-phase procedure integrating a multi-criteria warm start technique with an iterative k-means clustering algorithm is developed for optimal air taxi infrastructure location decisions. The proposed methodology was improved by utilizing a different clustering technique called clustering large applications (CLARA) which suggests developing 14 unique sites in New York City (NYC). However, establishing all the stations simultaneously might be challenging for any business, and therefore, a mathematical model is created to recommend these centers in multiple phases while maximizing the demand satisfaction in each scenario. Based on the available transportation literature, constraints such as rental cost, number of trips per day per 1000 customers, road facilities, and the employee salary are considered to be a part of the linear model. Next, a multiple-criteria simulation optimization model is developed to determine the ideal station size, location and size of charging facilities, minimum threshold charge, number of vehicles required and, allocating customers to air taxis for a network of five skyports. The model proposes having 50 air taxis in the system for the base case. The commuter average time in system and wait time to be approximately 36 and 14 minutes respectively, with average vehicle utilization of nearly 76 percent. While air taxis are expected to be utilized for intra-city commute, Hyperloop and High-Speed Rail (HSR) services would enable passengers for inter-city transport . A brief investigation is performed to examine the substitutability of HSR with Hyperloop services based on vehicle and passenger characteristics. A simulation model is developed to compare the performance of both these alternate transportation modes for a network of three major cities in Europe (Amsterdam, Paris, and Frankfurt). Our results indicate that with a significantly lower pod capacity, the Hyperloop system will still be able to serve more customers compared to the HSR services, while the vehicle utilization is observed to be higher in the latter alternative for a given period of time. We further compare the two transportation modes with respect to their estimated infrastructure and operational costs as well as CO2 emission. Finally, a cost-benefit analysis is conducted to estimate the passenger ticket price for Hyperloop services.

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Section: Hyperloop Systemmentioning

confidence: 99%