No Transfers Required: Integrating Last Mile with Public Transit Using Opti-Mile

TL;DR

Op ti-mile addresses the transfer-heavy nature of public transit in developing regions by integrating last-mile services with main transit to achieve direct connections. The approach builds a dynamic LMPTN and a bipartite PTN framework, optimizing the path by a convex combination of first/last mile and public transit times under a fare constraint. Experiments in Delhi show opti-mile can reduce travel distance by about $10\%$ with an $18\%$ fare increase and can improve city coverage, particularly when LM ranges are expanded, suggesting practical benefits for broader transit adoption. The work demonstrates a concrete, end-to-end planning methodology that aligns user preferences with network design, potentially informing policy and platform-level decisions for multi-modal urban mobility.

Abstract

Public transit is a popular mode of transit due to its affordability, despite the inconveniences due to the necessity of transfers required to reach most areas. For example, in the bus and metro network of New Delhi, only 30% of stops can be directly accessed from any starting point, thus requiring transfers for most commutes. Additionally, last-mile services like rickshaws, tuk-tuks or shuttles are commonly used as feeders to the nearest public transit access points, which further adds to the complexity and inefficiency of a journey. Ultimately, users often face a tradeoff between coverage and transfers to reach their destination, regardless of the mode of transit or the use of last-mile services. To address the problem of limited accessibility and inefficiency due to transfers in public transit systems, we propose ``opti-mile," a novel trip planning approach that combines last-mile services with public transit such that no transfers are required. Opti-mile allows users to customise trip parameters such as maximum walking distance, and acceptable fare range. We analyse the transit network of New Delhi, evaluating the efficiency, feasibility and advantages of opti-mile for optimal multi-modal trips between randomly selected source-destination pairs. We demonstrate that opti-mile trips lead to a 10% reduction in distance travelled for 18% increase in price compared to traditional shortest paths. We also show that opti-mile trips provide better coverage of the city than public transit, without a significant fare increase.

Figures (4)

• Figure 1: An Opti-Mile trip ensures a direct public transit connection with the help of first/last mile services
• Figure 2: Public Transit Network Model: (a) Remodeled PTN Graph -- $V^s = V^d = V$. Directed edges $e_{ij} \in E_b$ are drawn from $V^s$ to $V^d$ iff a route exists between $v_i^s \in V^s$ and $v_j^d \in V^d$. (b) LMPTN Graph -- first/last mile edges $e_{si}, e_{di} \in E_{LM}$ are added to the graph in Fig. \ref{['fig:rmptn']}.
• Figure 3: Coverage map showing the 90% population density bounding box. Blue represents the transit network, while red represents the coverage area
• Figure 4: Factors Affecting Path Efficiency