Eco-Approach Propulsion Control at Signalized Intersections
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Solution Overview
Problem
Current vehicle energy optimization systems face challenges in accurately predicting and managing energy consumption at signalized intersections due to adaptive signal phase and timing, leading to reduced energy efficiency and increased travel times.
Innovation Solution
The implementation of a method and system that utilizes vehicle-to-infrastructure communication to determine an intersection propulsion profile based on current vehicle speed and signal data, allowing for selective control of vehicle propulsion to deviate from or adjust energy consumption profiles, optimizing eco-approach and departure strategies through multi-horizon optimization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If adaptive signal phase and timing are used at intersections, then traffic flow flexibility is improved, but vehicle energy efficiency deteriorates due to unpredictable stop times
Solution Approach 1:
The system receives advance signal data about upcoming intersections and their phase/timing information before the vehicle reaches them. This preliminary information allows the propulsion control system to plan energy-efficient approaches in advance, adjusting speed and propulsion settings proactively rather than reactively when approaching intersections with adaptive signals.
2Use of energy by moving object
If vehicle speed is adjusted to pass through intersections in green phase, then energy consumption is reduced, but travel time increases due to speed modifications
Solution Approach 1:
The system implements dynamic speed adjustment strategies that continuously adapt to real-time conditions including signal phase, vehicle speed, and distance to intersection. Rather than using fixed speed profiles, the propulsion control dynamically optimizes the balance between maintaining green-phase passage and minimizing travel time, allowing flexible trade-offs based on current operational context.
Solution Approach 2:
The system changes key propulsion parameters including target speed, acceleration rates, and power delivery timing to optimize the approach to intersections. By adjusting these parameters based on signal data and vehicle state, the system achieves energy-efficient passage through intersections while minimizing deviations from optimal travel timelines.
3Use of energy by moving object
If eco-approach strategies are implemented at intersections, then energy efficiency is improved, but system complexity increases due to multiple horizon optimization
Solution Approach 1:
The optimization problem is segmented into multiple time horizons or stages, allowing the complex eco-approach control to be broken down into manageable computational steps. This segmentation enables the system to handle the complexity of multiple horizon optimization by processing decisions in sequential phases rather than requiring simultaneous optimization of all future states.
Data Source
AI summary
A method for controlling vehicle propulsion includes receiving signal data corresponding to a signaled intersection of a route being traversed by a vehicle. The method further includes determining an intersection propulsion profile for the signaled intersection based on at least a current vehicle speed and the signal data. The method further includes determining, based on the intersection propulsion profile, whether to deviate from a vehicle energy consumption profile corresponding to the route being traversed by the vehicle. The method further includes, in response to a determination to deviate from the vehicle energy consumption profile, selectively controlling vehicle propulsion of the vehicle according to the intersection propulsion profile. The method further includes, in response to traversing the intersection, selectively controlling vehicle propulsion according to the vehicle energy consumption profile.