Human Mobility and Location-Based Analysis

Derniers papiers

• Travel Mode- and Purpose-Specific Origin-Destination Matrices for England and Wales from Fused Travel Survey and Mobile Network Data

  Bowen Zhang, Chen Zhong, Mingfei Ma, James Golding-Graham · 30 septembre 2026

  Origin-destination (OD) matrices sit behind much of quantitative transport planning, from model calibration and accessibility analysis to the appraisal of new services and development. The increasing emphasis on place-based solutions requires mobility data that can support decision-making not only a…

• Editable Map-Conditioned Trajectory Generation for Human Mobility Simulation

  Takayuki Mizuno, Shouji Fujimoto, Mikito Hiruki, Atushi Ishikawa · 29 septembre 2026

  Geospatial simulation of infrastructure interventions requires mobility generators that respond directly to edited maps, yet many data-driven generators do not expose the map as an editable condition. We formulate this task as map-conditioned autoregressive generation of human mobility: a road raste…

• A Vision-Language Framework for Measuring Social Life on Sidewalks

  Liu Liu, Andres Sevtsuk · 25 septembre 2026

  While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A street traversed by a high volume of pedestrians has the same headcount as a street where people linger, sit, and socialize. This paper presents a visi…

• CALM: A Calibrated LLM Choice Network Framework for Activity-Based Traveler Simulation

  Yezhou Cheng · 22 septembre 2026

  We present CALM, a reproducible hybrid framework that integrates an optional large language model (LLM) activity planner with calibrated stochastic choice, shared network feedback, memory and habit, typed feasibility checks, and deterministic offline replay. Unlike trip-mode classifiers or diary-onl…

• Industrial Kinematic Trajectory Model (IKTM): Coordinate-Free Autoregressive Generator

  Max Amiri, David Eyers · 22 septembre 2026

  Mobility simulation supports logistics, safety, and communications planning in industrial environments such as ports, mines, and airports. Existing trajectory models, however, rely on absolute coordinates, road-network tokens, or semantic zones: representations that are site-specific and not well su…

• Modelling daily activity patterns from mobile phone location data via deep representation learning

  Xinglei Wang, Junyuan Liu, Guangsheng Dong, Zichao Zeng, Stephen Law, James Haworth, Tao Cheng · 22 septembre 2026

  Passively collected mobile phone location data provide large-scale, longitudinal observations of human mobility but do not directly reveal activity purposes. The functional characteristics of visited locations offer useful contextual information, yet their relationship with activity purpose remains …

• LE4Mob: Towards Inductive, Distance-Aware and General-Purpose Location Embedding for Human Mobility Modelling

  Xinglei Wang, Stephen Law, Zichao Zeng, Junyuan Liu, Guangsheng Dong, Tao Cheng · 22 septembre 2026

  Location representations provide mobility models with fundamental information about the spatial position, functional characteristics, and relationships of places. However, existing embeddings are often dependent on mobility observations, unable to represent unseen locations, and weakly constrained t…

• ZeroHAT: Behavior-Conditioned Zero-Shot Human Activity Trace Generation

  Rongchao Xu, Dahai Yu, Lin Jiang, Guang Wang · 18 septembre 2026

  Human activity traces record individuals' timestamped visits to points of interest and are essential for applications such as mobility prediction and urban simulation. However, accessing large-scale HATs is challenging due to high collection costs and privacy concerns. Synthetic HAT generation offer…

• Physics-Constrained Digital Twins for Sensor Integrity in Urban Pedestrian Flow: Detecting Stealthy False Data Injection with Conformal Guarantees

  Oscar Mogollon Gutierrez, Fatemeh Ghasemi, Mohammadhossein Homaei, Andres Caro, Mar Avila · 17 septembre 2026

  City pedestrian counting systems now feed economic indicators, planning decisions and safety operations, yet the twins built on top of them treat the incoming stream as ground truth. We study what happens when it is not. We formalise stealthy false data injection for city-scale pedestrian sensing, w…

• Generating Individual Travel Diaries Using Large Language Models Informed by Census and Land-Use Data

  Sepehr Golrokh Amin, Devin Rhoads, Fatemeh Fakhrmoosavi, Nicholas E. Lownes, John N. Ivan · 16 septembre 2026

  This study introduces a Large Language Model (LLM) scheme for generating key attributes of travel diaries in agent-based transportation models, including purpose, mode and distance, to assess the underlying viability of LLMs for activity generation tasks. While traditional approaches rely on large q…

• GEAR: From Dynamic Encoding to Dynamic Activation in Social Trajectory Prediction

  Jiaheng Chen, Jiaxing Li, Leixia Wang, Jianan Ju, Tinghe Zhang · 15 septembre 2026

  Human trajectory prediction requires modeling both individual motion patterns and social interactions among agents. Existing methods have made substantial progress by using attention mechanisms, graph structures, and temporal encoders to capture dynamic social context. However, most of them primaril…

• Enhancing Human Mobility Prediction with Spatially Aware LLM-based Multi-Agent Systems

  Shangyu Lou, Ziqi Cui · 15 septembre 2026

  Predicting a user's next POI is a task in human mobility modeling, yet LLM-based approaches focus on semantic reasoning from previous mobility records, while neglecting real-world spatial context. However, human mobility is inherently shaped by spatial cognition, including geographic distance and ne…

• A global mobile network coverage raster product at 1km resolution, 1999--2030

  Till Koebe, Theophilus Aidoo, Ali El Chami, Ali Kanso, Akansh Maurya, Purushottam Sharma, Ingmar Weber, Ridhi Kashyap · 11 septembre 2026

  Where a mobile signal is available shapes who can work, learn, bank, seek health care and respond to crises in the digital age, yet no globally consistent, sub-national record of mobile network coverage exists. We present such a record: annual 1km maps of the probability of 2G, 3G and 4G coverage fo…

• Who You Are Adds Nothing Detectable to Where You Go Next: Sociodemographic Conditioning in LLM Next-Location Prediction

  Xin Wang, Paraic Carroll, Kerry Nice, Sachith Seneviratne, Li Zhang · 10 septembre 2026

  Large language models (LLMs) are increasingly used for individual next-location prediction, while sociodemographic conditioning is common in LLM-based travel simulation. Yet the incremental predictive value of sociodemographic attributes remains unclear. To directly test this contribution, sociodemo…

• Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding

  Namwoo Kim, Jeeyun Chang, Kanghoon Lee, Yoonjin Yoon · 9 septembre 2026

  Urban region embeddings have shown promising results in diverse urban sensing tasks such as crime, income, and service-call prediction. Recent methods improve representation quality by integrating mobility data with auxiliary modalities, using cross-view attention or contrastive objectives to align …

• LEBGen: An LLM-Enhanced Bayesian Network Framework for Few-Shot Travel Survey Data Generation

  Zijian Shen, Bin Zhou, Jiguang Wang, Ya Zhao, Jintao Ke · 9 septembre 2026

  Travel survey data are essential for transportation planning and travel behavior analysis, yet collecting large-scale representative samples is costly and time-consuming. A practical alternative is to generate synthetic survey records from a few-shot sample. However, such samples provide incomplete …

• BER-PEF: Unified Human Mobility Predictability Evaluation via Bayes Error Rate Estimation

  En Xu, Jingtao Ding, Zhiwen Yu, Yong Li · 7 septembre 2026

  Human mobility predictability concerns the best prediction performance attainable from a given target and input information, but its ground truth is not directly observable on real mobility data. We present BER-PEF, a Bayes-error-rate-based framework that converts BER estimation into mobility predic…

• UTP-Bench: Uncertainty-aware Travel Planning Benchmark

  Etcharla Revanth Rao, Priyanshu Karmakar, Shubhojit Mallick, Manish Gupta, Shreya Ghosh, Abhik Jana · 3 septembre 2026

  Large Language Models (LLMs) have recently demonstrated strong capabilities in automated travel itinerary generation. However, real- world travel planning is inherently uncertain: transportation delays, crowd fluctuations, and unexpected stochastic delays frequently inval- idate otherwise feasible s…

• Behavioral calibration of mobile-phone GPS data for population-representative analyses

  Nicol\`o Alessandro Girardini, Unchitta Kan, Eduardo L\'opez, Bruno Lepri, Lorenzo Lucchini, Simone Centellegher · 2 septembre 2026

  Mobile phone mobility data have transformed the study of human behavior, but demographic and behavioral biases can compromise their representativeness and distort population-level inference. Existing calibration approaches primarily address demographic and geographic representativeness, leaving beha…

• Do LLMs Know Your Neighborhood? Auditing LLM Priors for Neighborhood-Level Mobility Prediction and Structural Alignment

  Saad Mohammad Abrar, Eesha Kurella, Arnav Dadarya, Naman Awasthi, Kazi Tasnim Zinat, Vanessa Frias-Martinez · 2 septembre 2026

  Human mobility is central to urban planning, transportation, public health, and emergency response, yet fine-grained trajectory data are often proprietary, restricted, and privacy-sensitive. Large language models (LLMs) offer a potential alternative by generating plausible mobility traces and predic…

• Off the Normal Path: Learning Spatial Density Models of Node Mobility

  Wanxin Gao, Ioanis Nikolaidis, Janelle Harms · 31 août 2026

  We consider the problem of learning models of spatial density functions, representing the steady-state density of mobile nodes moving on a two-dimensional terrain. Deriving such models can assist in network design and optimization problems, e.g., by accelerating the computation of the density functi…

• Learning to Transfer Across Modes: Towards Unified Urban Mobility Forecasting

  Yixuan Zhao, Man Luo · 31 août 2026

  Urban transportation systems consist of multiple mobility modes that coexist within the same city and exhibit complex interdependencies, leading to correlated demand dynamics across modes. However, forecasting demand jointly across different modes remains challenging due to substantial heterogeneity…

• An Empirical Evaluation of Cross-City POI Recommendation on a Large-Scale Benchmark

  Peibo Li, Yang Song, Hao Xue, Maarten de Rijke, Flora D. Salim · 31 août 2026

  Cross-city point-of-interest (POI) recommendation is crucial for navigating unfamiliar urban environments, yet its progress has historically been constrained by data limitations. Using the recently proposed large-scale benchmark Trip World, we empirically re-examine whether conclusions drawn on smal…

• DeMMO: Longitudinal and Cross-Disease Modelling of Digital Mobility Outcomes via Multi-Task Learning

  Menghui Zhou, Zhipeng Yuan, Vitaveska Lanfranchi, Po Yang · 27 août 2026

  Digital mobility outcomes (DMOs) derived from wearable sensors characterise mobility in daily life and offer a promising means of monitoring disease progression. Yet most DMO studies examine one disease at one visit; they do not model how multivariate DMO relationships with multiple clinical outcome…

• Quantifying geographic domain shift to decouple the geospatial transferability of human mobility flow generation models

  Zhiyong Zhou, Song Gao, Qianheng Zhang, Feng Zhang, Zhenhong Du · 25 août 2026

  Human mobility serves as an essential proxy for understanding social, economic, and environmental dynamics in urban systems. Geospatial transferability, which measures a model's capability in a new location or unseen region, is a critical dimension for comparing different human mobility generation m…