TrajRoute: Rethinking Routing with a Simple Trajectory-Based Approach – Forget the Maps and Traffic!

The abundance of vehicle trajectory data offers a new opportunity to compute driving routes between origins and destinations. Current graph-based routing pipelines, while effective, involve substantial costs in constructing, maintaining, and updating road network graphs to reflect real-time conditions. In this study, we propose a new trajectory-based routing paradigm that bypasses current workflows by directly utilizing raw trajectory data to compute efficient routes. Our method, named TrajRoute, uniquely “follows” historical trajectories from a source to a destination, constructing paths that reflect actual driver behavior and implicit preferences. To supplement areas with sparse trajectory data, the road network is also incorporated into TrajRoute's index, and tunable parameters are introduced to control the balance between road segments and trajectories, ensuring a unified and adaptable routing approach. We experimentally verify our approach by comparing it to an existing online routing service. Our results demonstrate that as the number of trajectories covering the road network increases, TrajRoute produces increasingly accurate travel time and route length estimates while gradually eliminating the need to downgrade to the road network. This highlights the potential of simpler, data-driven pipelines for routing, offering lowermaintenance alternatives to conventional systems.

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Publication Details

Published
2025-06-02
DOI
https://doi.org/10.1109/mdm65600.2025.00040
Citations
1
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
1.49
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article

TrajRoute: Rethinking Routing with a Simple Trajectory-Based Approach – Forget the Maps and Traffic!

Cyrus Shahabi, John Krumm, Maria Despoina Siampou, Chrysovalantis Anastasiou
1 citations
Data Management and Algorithms
1.49
article

TrajRoute: Rethinking Routing with a Simple Trajectory-Based Approach – Forget the Maps and Traffic!

Cyrus Shahabi, John Krumm, Maria Despoina Siampou, Chrysovalantis Anastasiou
article en
1 citations

Abstract

The abundance of vehicle trajectory data offers a new opportunity to compute driving routes between origins and destinations. Current graph-based routing pipelines, while effective, involve substantial costs in constructing, maintaining, and updating road network graphs to reflect real-time conditions. In this study, we propose a new trajectory-based routing paradigm that bypasses current workflows by directly utilizing raw trajectory data to compute efficient routes. Our method, named TrajRoute, uniquely “follows” historical trajectories from a source to a destination, constructing paths that reflect actual driver behavior and implicit preferences. To supplement areas with sparse trajectory data, the road network is also incorporated into TrajRoute's index, and tunable parameters are introduced to control the balance between road segments and trajectories, ensuring a unified and adaptable routing approach. We experimentally verify our approach by comparing it to an existing online routing service. Our results demonstrate that as the number of trajectories covering the road network increases, TrajRoute produces increasingly accurate travel time and route length estimates while gradually eliminating the need to downgrade to the road network. This highlights the potential of simpler, data-driven pipelines for routing, offering lowermaintenance alternatives to conventional systems.

University of Southern California (US)
Openalex Percentile: Top 17%
Data Management and Algorithms
1.49
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TrajRoute: Rethinking Routing with a Simple Trajectory-Based Approach – Forget the Maps and Traffic! — Cyrus Shahabi, John Krumm, et al. · (2025) | TGRS Research Map | TGRS