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Shortest-Path Diversification through Network Penalization: A Washington DC Area Case Study

Published: 05 November 2019 Publication History

Abstract

Traditional navigation systems compute the quantitatively shortest or fastest route between two locations in a spatial network. In practice, a problem resulting from all drivers using the shortest path is the congregation of individuals on routes having a high in-betweenness. To this end, several works have proposed methods for proposing alternative routes. In this work, we test solutions for traffic load-balancing by computing diversified routes proposing variants of the penalty method using the road network of the Washington DC metropolitan area as a case study. Our experimental evaluation shows that the tested Penalty-based approaches allow to significantly balance the load of a spatial network, compared to existing k-shortest path algorithms, and compared to a naive baseline that randomly changes the weights of the network at each shortest-path computation.

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  1. Shortest-Path Diversification through Network Penalization: A Washington DC Area Case Study

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      cover image ACM Conferences
      IWCTS'19: Proceedings of the 12th ACM SIGSPATIAL International Workshop on Computational Transportation Science
      November 2019
      89 pages
      ISBN:9781450369671
      DOI:10.1145/3357000
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      Published: 05 November 2019

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      Author Tags

      1. Diversification
      2. Load balancing
      3. Penalization
      4. Road Network
      5. Traffic
      6. k-Shortest Paths

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      Cited By

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      • (2024)Impact of Static Urban Traffic Flow-Based Traffic Weighted Multi-Maps Routing Strategies on Pollutant EmissionsSystems10.3390/systems1203008912:3(89)Online publication date: 12-Mar-2024
      • (2024)Generating Trajectories from Implicit Neural Models2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00036(129-138)Online publication date: 24-Jun-2024
      • (2024)Congestion-Mitigating Spatiotemporal Routing in Road Networks2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00349(4586-4599)Online publication date: 13-May-2024
      • (2023)Effects of Route Randomization on Urban EmissionsSUMO Conference Proceedings10.52825/scp.v4i.2174(75-87)Online publication date: 29-Jun-2023
      • (2023)Application of Traffic Weighted Multi-Maps Based on Disjoint Routing Areas for Static Traffic AssignmentApplied Sciences10.3390/app13181007113:18(10071)Online publication date: 6-Sep-2023
      • (2023)k-Fewest Turn and Shortest Path Algorithm based on Stroke GraphProceedings of the 16th ACM SIGSPATIAL International Workshop on Computational Transportation Science10.1145/3615895.3628170(32-41)Online publication date: 13-Nov-2023
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      • (2022)History oblivious route recovery on road networksProceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3560979(1-10)Online publication date: 1-Nov-2022
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