The effects of autonomous buses to vehicle scheduling system

Viktor, Nagy; Horváth, Balázs

doi:10.1016/j.procs.2020.03.035

Cited by 15 publications

(5 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The advent of self-driving vehicles promises to revolutionize sustainable urban transportation systems [10][11][12], yet it also carries the risk of undermining the efficacy and utilization of public transit networks [11,12]. The conversion to autonomous buses is expected to result in cost savings for fixed bus routes [13][14][15][16], with higher investment costs offset by savings in operating costs for drivers [13,14,17]. A combination of buses and smaller autonomous vehicles also appears to be economically attractive [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Fleet Structure for Autonomous Electric Buses: A Route-Based Analysis in Aachen, Germany

Sistig,

Sinhuber,

Rogge

et al. 2024

Sustainability

View full text Add to dashboard Cite

Intelligent transportation systems enhance the potential for sustainable, user-friendly, and efficient transport. By eliminating driver costs, autonomous buses facilitate the redesign of networks, timetables, and fleet structure in a cost-effective manner. The electrification of bus fleets offers the opportunity to further improve the environmental sustainability of transportation networks, but requires adjustments to vehicle schedules due to the limited range and charging requirements. This paper examines the intricate relationship between electrification and autonomous buses. To this end, timetables for autonomous electric buses of different sizes were developed for a real bus route in Aachen, Germany. The resulting electric vehicle scheduling problem was then solved using an adaptive large neighborhood search to determine the number of vehicles needed and the total cost of ownership. By eliminating driver costs, vehicles with lower passenger capacity become much more attractive, albeit at a slightly higher cost. In comparison, the incremental costs of electrification are low if the right approach is taken. Fluctuations in typical passenger numbers can be used to modify timetables and vehicle schedules to accommodate the charging needs of autonomous electric buses. In particular, electric bus concepts with fewer charging stations and lower charging power benefit from adapting the timetable to passenger numbers. The results demonstrate that the specific requirements of electric buses should be considered when adapting networks and timetables in order to design a sustainable transport network.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Fleet Structure for Autonomous Electric Buses: A Route-Based Analysis in Aachen, Germany

Sistig,

Sinhuber,

Rogge

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Thus, the efficiency of the current system is usually between 60 to 70% which means that the vehicle does not generate income for almost one third of the working time because of the rest time. For example, Nagy Horváth [9] studied the implications of adaption of autonomous buses for the city of Eger, Hungry which is a medium sized city with about 50.000 inhabitants based on the following assumptions: a.…”

Section: Dmentioning

confidence: 99%

Public Transportation on the Era of Autonomous Vehicles: Exploring Different Scenarios

Othman

2020

CERJ

View full text Add to dashboard Cite

Research on vehicle automation has launched many years ago. Over the last decade, autonomous vehicles (AVs) have witnessed tremendous improvement because of the significant effort dedicated to AVs from both research and industry. Despite the enthusiastic speculation of AVs, little is known about the influence of vehicle automation on the public transit service. Thus, the main goal of this paper is to investigate and explore the implications of vehicle automation on the shape of public transit. In this paper three scenarios of AVs adoption are explored: autonomous vehicles are used for the entire trip (AV as a competitor to the public transportation), integrated AVs with the current public transit system (AVs are used to solve the first mile last mile problem to increase the attractive ness of the transit service), and fully autonomous buses. Finally, results show that a combination between scenario two and three is the recommended scenario in order to derive the optimal benefits of the automation technology.

show abstract

“…To generate a set of non-dominated solutions, a non-dominated sorting genetic algorithm is adopted in this paper. Also, the effects of autonomous buses to vehicle scheduling system are studied in [24]. Multi-depot vehicle scheduling problem is also raised as a subproblem in many important problems [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

State-of-the-Art Auction Algorithms for Multi-depot Bus Scheduling Problem Considering Depot Workload Balancing Constraints

Niksirat

2020

Fuzzy Information and Engineering

View full text Add to dashboard Cite

This paper deals with multi-depot bus scheduling (MDBS) problem. Depot workload balancing constraints are introduced. In this case, the problem can be stated as a two-objective multi-commodity flow problem with soft constraints. Two state-of-the-art heuristics are developed including schedule-based and cluster-based heuristics, both of them extend auction algorithm. Also three different approaches are proposed to satisfy depot workload balancing constraints. The convergence of each algorithm is investigated and its complexity obtained. To illustrate the main concepts and results, a small example is solved. Also, to demonstrate the performance of the proposed algorithms, some benchmark examples are considered and CPU-time and optimality gap are compared. The results show a great improvement in the CPU time and quality of the solution of the proposed algorithms. Also the extension of the proposed algorithms under -scaling approach is analysed.

show abstract

The effects of autonomous buses to vehicle scheduling system

Cited by 15 publications

References 1 publication

Optimizing Fleet Structure for Autonomous Electric Buses: A Route-Based Analysis in Aachen, Germany

Optimizing Fleet Structure for Autonomous Electric Buses: A Route-Based Analysis in Aachen, Germany

Public Transportation on the Era of Autonomous Vehicles: Exploring Different Scenarios

State-of-the-Art Auction Algorithms for Multi-depot Bus Scheduling Problem Considering Depot Workload Balancing Constraints

Contact Info

Product

Resources

About