Adaptability analysis methods of demand responsive transit: a review and future directions

ABSTRACT

Demand responsive transit (DRT) echoes the new requirements of modern travel on flexibility and carbon reduction, as well as achieving a better match between demand and supply. However, many DRTs still failed. An important step named adaptability analysis helps to understand the context, desirability, and feasibility of introducing DRT. An adaptability analysis includes three sub-questions. Question 1 focuses on policy, regulation, funding, and technologies. Question 2 looks at the interactions of travel demand with operation parameters such as fare and fleet size. Question 3 tries to figure out the impacts of DRT on mobility, society, and the environment. To answer Question 1, macro-level methods collect information and generalise from empirical knowledge, including experience and barriers from real-world operation cases. To answer Question 2, meso-level methods determine the operation mode of DRT by quantifying related factors and establishing evaluation models or boundary condition decision models. To answer Question 3, micro-level methods use microscopic models for simulating the interaction between passengers and vehicles under different scenarios. This paper further discusses the advantages, disadvantages, and future directions of adaptability analysis methods of DRT. Overall, DRT presents great potential and future adaptability analysis should be developed by considering new trends in DRT and more complex and practical-oriented scenarios.

KEYWORDS:

• Demand-responsive transit
• adaptability analysis
• case studies
• evaluation models
• boundary condition decision models
• agent-based models

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Ministry of Transport of the People’s Republic of China Science and Technology Research Foundation for Transportation (no. 2015318221020).