DFD: Data-privacy-regulation Food Delivery

Article: Zijian Zhao, Sen Li*, "The Impacts of Data Privacy Regulations on Food-Delivery Platforms", Transportation Research Part C: Emerging Technologies, 2025

Proposal: Zijian Zhao, "Towards Fairness in Transportation Gig Markets: Identifying, Imitating, and Mitigating Algorithm Discrimination via Deep Reinforcement Learning", 2026 Annual AAAI Conference on Artificial Intelligence (AAAI) / Special Interest Group on Artificial Intelligence (SIGAI) Doctoral Consortium, supervised by Prof. Sen Li

Acknowledgement: The code is based on our previous work Discriminatory-Food-Delivery and the work of ‪Yulong Hu‬. Special thanks to Yitong Shang for providing the synthetic food delivery data.

Notice: A new version of this work will be provided at AV-Food-Delivery.

1. Workflow

2. Dataset & Simulator

Please refer to our previous work Discriminatory-Food-Delivery.

Notice: Due to copyright, we only provide the synthetic food delivery data generated by a GAN. Please notice it would be different from the real-world data used in the paper.

3. How to Run

3.1 Platform Training

3.1.1 Pre-training

python pretrain_platform.py --probability_worker --rand_sample_rate

3.1.2 Fine-tuning

python finetune_platform.py --probability_worker --demand_sample_rate <order sampling rate> --worker_mode <gdpr/benchmark/mask>

3.2 Courier Training

python train_courier.py --probability_worker --model_path <platform_strategy_model_path> --worker_mode <gdpr/benchmark/mask> --lowest_utility <minimum_wage_for_exit_couriers> --demand_sample_rate <order sampling rate>

3.3 Comparative Evaluation

python eval.py --probability_worker --gdpr_path <gdpr_model_path> --benchmark_path <benchmark_model_path> --mask_path <mask_model_path> --lowest_utility <minimum_wage_for_exit_couriers> --demand_sample_rate <order sampling rate>

4. Reference

@article{ZHAO2025105364,
title = {The impacts of data privacy regulations on food-delivery platforms},
journal = {Transportation Research Part C: Emerging Technologies},
volume = {181},
pages = {105364},
year = {2025},
issn = {0968-090X},
doi = {https://doi.org/10.1016/j.trc.2025.105364},
url = {https://www.sciencedirect.com/science/article/pii/S0968090X25003687},
author = {Zijian Zhao and Sen Li},
keywords = {Transportation network companies, Food-delivery market, General data protection regulation (GDPR), Multi-agent reinforcement learning}
}