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Real-time Route Planner Design

Summary

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  • Up-to-date information enables travelers to make improved route choice decisons.

  • Significant traveler response to up-to-date information affects network traffic conditions.

  • Reduction of individual drivers’ travel times as well as total travel time.

  • Distribution of travel time savings among guided and unguided travelers.

  • Better utilization of existing infrastructure.

Motivation

  • Travelers unfamiliar with an area are frequently unaware of route options available.

  • Familiar travelers possess only limited route options knowledge.

  • Congestion occurence can be unpredictable.

  • Recurrent congestion also contains randomness due to variability in travel demand levels and network performance

Contributions

Dynamic Shortest Path Calculation based on Link Speed Profile Functions

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Real-time Route Planner

  • Algorithms for estimating speeds, turning ratios and link densities via RSUs and OBUs.

  • Feedback traffic schedules and predicted link speed profiles to vehicle onboard route planner Apps via RSUs.

Route Guidance and Advanced Traveler Information Systems (ATIS)

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Poster for NTU-NXP Workshop in Aug 2017

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Reference

  1. A. F. Lentzakis, S. I. Ware, and R. Su. Region-based dynamic forecast routing for autonomous vehicles. In Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International Conference, pp. 1464-1469. 2016.

  2. A. F. Lentzakis, R. Su, C. Wen. Strategic learning approach to region-based dynamic route guidance. 12th IEEE International Conference on Control & Automation, Kathmandu, 2016.