An Online Mechanism for Ridesharing in Autonomous Mobility-on-Demand Systems
Authors: Wen Shen, Cristina V. Lopes, Jacob W. Crandall
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Numerical results indicate the competitiveness of IORS compared with two benchmarks, namely the optimal assignment and an offline, auction-based mechanism. |
| Researcher Affiliation | Academia | Wen Shen and Cristina V. Lopes University of California, Irvine Irvine, CA 92697, USA {wen.shen, lopes}@uci.edu Jacob W. Crandall Masdar Institute of Science and Technology Abu Dhabi, PO Box 54224, UAE jcrandall@masdar.ac.ae |
| Pseudocode | Yes | Algorithm 1: The Fare Estimation Algorithm |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. No explicit statements about code release or links to repositories were found. |
| Open Datasets | No | The paper describes generating synthetic data within a simulator ('we generated a random number of requests Rt 2 R... initialized R with a set of N = 500 integers randomly drawn from a normal distribution...'). It does not provide access information (link, DOI, formal citation) for a publicly available or open dataset. |
| Dataset Splits | No | The paper describes simulation settings and data generation parameters but does not specify explicit training/validation/test dataset splits as would be typical for model training and evaluation. |
| Hardware Specification | Yes | We ran all the simulations on a 2.9GHz quad-core machine with a 32GB RAM. |
| Software Dependencies | No | The paper mentions using 'Lp Solve solver' but does not provide specific version numbers for this or any other software dependencies. |
| Experiment Setup | Yes | In the experiment, we assumed that the number of AVs in the system is fixed. We set the number N = 1000. For each simulation, the system ran for 500 rounds unless specified otherwise. For each round, we generated a random number of requests Rt 2 R. We initialized R with a set of N = 500 integers randomly drawn from a normal distribution with mean µ = 1000 and standard deviation 100 (see Figure 3a). We assumed that each AV can transport up to four passengers at the same time. The request time is the current round number; the waiting time is randomly drawn from the range 10 to 100; both the origins and destinations are randomly selected within a radius of 50 blocks in the grid. The operational cost per unit distance (block) is 1. The speeds for all vehicles are the same: 0.5 block per unit time (round). Initially, all the AVs depot at the center of the grid city. At time t = 0, the AVs become available for servicing passengers. |