Understanding Mode Choice Behavior of People with Disabilities: A Case Study in Utah
- URL: http://arxiv.org/abs/2511.11748v1
- Date: Thu, 13 Nov 2025 16:28:58 GMT
- Title: Understanding Mode Choice Behavior of People with Disabilities: A Case Study in Utah
- Authors: Megh Bahadur KC, Ziqi Song, Keunhyun Park, Keith Christensen,
- Abstract summary: The study identified key factors influencing mode preferences for both groups by utilizing Utah's household travel survey.<n>The analysis revealed intriguing trends, including a shift towards carpooling among disabled individuals.<n>People with disabilities placed less emphasis on travel time saving.<n>Despite a 50% fare reduction for the disabled group, transit accessibility remains a significant barrier in their choice of Transit mode.
- Score: 0.5155906628389595
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Despite the growing recognition of the importance of inclusive transportation policies nationwide, there is still a gap, as the existing transportation models often fail to capture the unique travel behavior of people with disabilities. This research study focuses on understanding the mode choice behavior of individuals with travel-limited disabilities and comparing the group with no such disability. The study identified key factors influencing mode preferences for both groups by utilizing Utah's household travel survey, simulation algorithm and Multinomial Logit model. Explanatory variables include household and socio-demographic attributes, personal, trip characteristics, and built environment variables. The analysis revealed intriguing trends, including a shift towards carpooling among disabled individuals. People with disabilities placed less emphasis on travel time saving. A lower value of travel time for people with disabilities is potentially due to factors like part-time work, reduced transit fare, and no or shared cost for carpooling. Despite a 50% fare reduction for the disabled group, transit accessibility remains a significant barrier in their choice of Transit mode. In downtown areas, people with no disability were found to choose transit compared to driving, whereas disabled people preferred carpooling. Travelers with no driving licenses and disabled people who use transit daily showed complex travel patterns among multiple modes. The study emphasizes the need for accessible and inclusive transportation options, such as improved public transit services, shorter first and last miles in transit, and better connectivity for non-motorized modes, to cater to the unique needs of disabled travelers. The findings of this study have significant policy implications such as an inclusive mode choice modeling framework for creating a more sustainable and inclusive transportation system.
Related papers
- Inequality in Congestion Games with Learning Agents [49.16654883862325]
We show that disparities arise not only from the structure of the network but also from differences in how commuters adapt to it.<n>To capture potential efficiency-fairness tradeoffs, we introduce the Price of Learning (PoL), a measure of inefficiency during learning.<n>Our simulations show that network expansions can simultaneously increase efficiency and amplify inequality.
arXiv Detail & Related papers (2026-01-28T13:16:25Z) - Exploring Dissatisfaction in Bus Route Reduction through LLM-Calibrated Agent-Based Modeling [0.0]
This study employs an agent-based modelling (ABM) approach calibrated through a large language model (LLM)<n>Using IC-card data from Beijing's Huairou District, the LLM-calibrated ABM estimated passenger sensitivity parameters related to travel time, waiting, transfers, and crowding.<n>Results show that the structural configuration of the bus network exerts a stronger influence on system stability than capacity or operational factors.
arXiv Detail & Related papers (2025-10-30T05:59:48Z) - Scalable Ride-Sourcing Vehicle Rebalancing with Service Accessibility Guarantee: A Constrained Mean-Field Reinforcement Learning Approach [42.070187224580344]
We introduce continuous-state mean-field control (MFC) and mean-field reinforcement learning (MFRL) models that employ continuous vehicle repositioning actions.<n>MFC and MFRL offer scalable solutions by modeling each vehicle's behavior through interaction with the vehicle distribution, rather than with individual vehicles.<n>Our approach scales to tens of thousands of vehicles, with training times comparable to the decision time of a single linear programming rebalancing.
arXiv Detail & Related papers (2025-03-31T15:00:11Z) - GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching [81.82487256783674]
GARLIC: a framework of GPT-Augmented Reinforcement Learning with Intelligent Control for vehicle dispatching.<n>This paper introduces GARLIC: a framework of GPT-Augmented Reinforcement Learning with Intelligent Control for vehicle dispatching.
arXiv Detail & Related papers (2024-08-19T08:23:38Z) - Studying the Impact of Semi-Cooperative Drivers on Overall Highway Flow [76.38515853201116]
Semi-cooperative behaviors are intrinsic properties of human drivers and should be considered for autonomous driving.
New autonomous planners can consider the social value orientation (SVO) of human drivers to generate socially-compliant trajectories.
We present study of implicit semi-cooperative driving where agents deploy a game-theoretic version of iterative best response.
arXiv Detail & Related papers (2023-04-23T16:01:36Z) - A Bibliometric Analysis and Review on Reinforcement Learning for
Transportation Applications [43.356096302298056]
Transportation is the backbone of the economy and urban development.
Reinforcement Learning (RL) that enables autonomous decision-makers to interact with the complex environment.
This paper conducts a bibliometric analysis to identify the development of RL-based methods for transportation applications.
arXiv Detail & Related papers (2022-10-26T07:34:51Z) - Shifting Mobility Behaviors in Unprecedented Times: Intentions to Use
On-demand Ride Services During the COVID-19 Pandemic [0.0]
COVID-19 has been a major disruptive force in people's everyday lives and mobility behavior.
The demand for on-demand ride services, such as taxis and ridehailing, has been specifically impacted.
This study examines intentions to use on-demand ride services in a period of drastic changes in lifestyles and daily routines.
arXiv Detail & Related papers (2021-08-05T00:41:59Z) - Incentivizing Routing Choices for Safe and Efficient Transportation in
the Face of the COVID-19 Pandemic [14.943238230772264]
We propose to use financial incentives to set the tradeoff between risk of infection and congestion to achieve safe and efficient transportation networks.
For our framework to be useful in various cities and times of the day without much designer effort, we also propose a data-driven approach to learn human preferences about transport options.
arXiv Detail & Related papers (2020-12-28T13:52:06Z) - Studying Person-Specific Pointing and Gaze Behavior for Multimodal
Referencing of Outside Objects from a Moving Vehicle [58.720142291102135]
Hand pointing and eye gaze have been extensively investigated in automotive applications for object selection and referencing.
Existing outside-the-vehicle referencing methods focus on a static situation, whereas the situation in a moving vehicle is highly dynamic and subject to safety-critical constraints.
We investigate the specific characteristics of each modality and the interaction between them when used in the task of referencing outside objects.
arXiv Detail & Related papers (2020-09-23T14:56:19Z) - Modeling and Analysis of Excess Commuting with Trip Chains [3.728629802579785]
This research finds that traditional excess commuting studies underestimate both actual and optimal commute, while overestimate excess commuting.
Based on a case study of the Tampa Bay region of Florida, this research finds that traditional excess commuting studies underestimate both actual and optimal commute, while overestimate excess commuting.
arXiv Detail & Related papers (2020-08-25T14:54:04Z) - Interdependence in active mobility adoption: Joint modelling and
motivational spill-over in walking, cycling and bike-sharing [0.0]
The purpose of this study is to investigate the adoption of three active travel modes; namely walking, cycling and bikesharing.
The analysis is based on an adaptation of the stages of change framework, which originates from the health behavior sciences.
arXiv Detail & Related papers (2020-06-24T17:37:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.