Conceptual Design Optimization of Autonomous Electric Buses in Public Transportation

Abstract

Autonomous electric buses (AEB) have widely been envisioned in future public transportation systems due to their large potential to improve service quality while reducing operational costs. The requirements and specifications for AEBs, however, remain uncertain and strongly depend on the use case. To enable the identification of the optimal vehicle specifications, this paper presents a holistic design optimization framework that explores the impacts of implementing different AEB concepts in a given set of routes/network. To develop the design optimization framework, first, a multi-objective, multi-criteria objective function is formulated by identifying the attributes of bus journeys that represent overall value to the stakeholders. Simulation models are then developed and implemented to evaluate the overall performance of the vehicle concepts. A genetic algorithm is used to find the concepts with the optimal trade-off between the overall value to the stakeholders and the total cost of ownership. A case study is presented of a single bus line in Singapore. The results show an improvement in the waiting time with the use of a smaller sized AEB with a capacity of 20 passengers. However, the costs and emissions increase due to the requirement of a larger fleet and the increase in daily distance traveled compared to a 94-passenger capacity AEB.

Method for the Conceptual Design of a New Mode of Urban Delivery Vehicle

“…This was derived from the current state of vehicle development, based on a structured comparative literature review, and can be used as a guide to define battery/electric vehicle architectures at an early stage of development. Pathak et al 2021 [28] introduced a framework for optimizing the design of autonomous electric buses in public transport into the problem of vehicle concept design. In the paper, the authors consider quality of service, operating costs, and stakeholder value.…”

“…TCO annual packge weight available and km € year kg km (1) This methodology is closely based on the work of Pathak et al [28] and Stocker et al [20], resulting in findings that allow the vehicle operator to measure the technoeconomic factors governing the efficiency of delivery vehicles. Both these studies start by defining vehicle parameters and drive cycles (representing use cases), then run a simulation to predict the energy consumption and lifecycle costing.…”

The Role of Attitude, Travel-Related, and Socioeconomic Characteristics in Modal Shift to Shared Autonomous Vehicles with Ride Sharing

“…The use of private cars in developing countries is much higher than the use of public transit, which leads to a variety of adverse effects in many aspects [1][2][3]. According to some forecasts, autonomous vehicles (AVs) will significantly reduce the private car market share and increase the share of transit, cycling, and walking, as well as facilitating car sharing and ridesharing services, which shows how automation contributes to creating sustainable and efficient transportation systems [4][5][6]. Nevertheless, one of the major barriers is the high cost of AVs for personal use [7,8], particularly within large urban networks where travel demand is high and space is limited [9,10].…”

Integration of a Chassis Servo-Dynamometer and Simulation to Increase Energy Consumption Accuracy in Vehicles Emulating Road Routes

“…The need for an even quicker means of testing is one of the reasons why numerical simulation becomes relevant to rapidly evaluate solutions; these studies usually fulfill the function of evaluating many components and route conditions at a much lower cost and time than route or dynamometer tests through the use of iterative or analytic methods performed in virtual environments [49][50][51]. Studies in this area are varied, for example, Bottiglione et al simulate and compare electrical buses with different types of transmissions [52]; Xu et al propose methodologies for simulating traffic and driving styles [53]; while Fiori et al, propose an instant speed and acceleration analysis in order to estimate electric vehicle energy requirements [54]; however, authors of these different studies, and many others focused on mathematical simulation, comment on the limitations of using theoretical models for precise component interaction analysis.…”