Proceedings Article10.1109/ITSC.2013.6728538
Multi-stage dynamic programming algorithm for eco-speed control at traffic signalized intersections
Raj Kishore Kamalanathsharma,Hesham A. Rakha +1 more
- 01 Oct 2013
- pp 2094-2099
112
TL;DR: A multi-stage dynamic programming tool that uses a recursive trajectory generation that is similar to least-cost path-finding algorithms that optimizes the upstream profile while comparing discretized downstream cases is suggested.
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Abstract: Researchers have attempted to compute a fuel-optimal vehicle trajectory by receiving traffic signal phasing and timing information. This problem, however, is complex when microscopic models are used to compute the objective function. This paper suggests use of a multi-stage dynamic programming tool that not only provides outputs that are closer to optimum, but are also computationally much faster. It uses a recursive trajectory generation that is similar to least-cost path-finding algorithms that optimizes the upstream profile while comparing discretized downstream cases. Since dynamic programming is faster than traditional computational methods, the algorithm can afford to use microscopic models and thereby be sensitive to a multitude of inputs such as grade, weather etc. Agent-based simulations suggest fuel savings in the range of 19 percent and travel-time savings of 32 percent in the vicinity of intersections. This research also showed potential benefits to vehicles following a vehicle that uses the proposed logic.
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Citations
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References
A note on two problems in connexion with graphs
TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Generalized best-first search strategies and the optimality of A*
Rina Dechter,Judea Pearl +1 more
TL;DR: It is shown that several known properties of A* retain their form and it is also shown that no optimal algorithm exists, but if the performance tests are confirmed to cases in which the estimates are also consistent, then A* is indeed optimal.
Transportation energy data book
Stacy Cagle Davis,Susan W Diegel,Robert Gary Boundy +2 more
- 01 Jan 2008
TL;DR: The Transportation Energy Data Book: Edition 11 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the Office of Transportation Technologies in the Department of Energy (DOE) as discussed by the authors.
1K
Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time
B Asadi,Ardalan Vahidi +1 more
TL;DR: An optimization-based control algorithm is formulated that uses short range radar and traffic signal information predictively to schedule an optimum velocity trajectory for the vehicle to reduce idle time at stop lights and fuel consumption.
793
Energy and emissions impacts of a freeway-based dynamic eco-driving system
TL;DR: This study investigated the concept of dynamic eco-driving, where advice is given in real-time to drivers changing traffic conditions in the vehicle's vicinity, and found that in general, higher percentage reductions in fuel consumption and CO2 emission occur during severe compared to less congested scenarios.
607