Target Speed Band Planning Around Time-Dependent Vehicle Obstacles
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Solution Overview
Problem
Current vehicle control systems lack an effective method to generate a target operational speed band that optimizes energy efficiency by anticipating and adapting to time-dependent obstacles, such as traffic signals and other vehicles, along a route, which limits the potential benefits of V2I and V2V communication for predictive energy management.
Innovation Solution
A method and controller that identify time-dependent obstacles on a vehicle's route, define these obstacles in a two-dimensional speed against distance map, and determine a target operational speed band that includes speed trajectories to optimize energy efficiency, considering acceleration limits and cost penalties for deviations, thereby improving operating efficiency and reducing journey time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the vehicle maintains a constant speed to simplify control, then the control system is easier to operate, but energy efficiency cannot be optimized by anticipating future obstacles
Solution Approach 1:
The system performs preliminary identification of time-dependent obstacles and pre-calculates optimal speed trajectories before the vehicle reaches critical points. By anticipating traffic signals, congestion, and other obstacles in advance, the control system can smoothly adjust speed to optimize energy consumption without reactive braking or acceleration, thereby resolving the contradiction between energy efficiency and control complexity.
Solution Approach 2:
The control system dynamically adjusts the speed trajectory based on real-time identification of time-dependent obstacles. Instead of maintaining a fixed speed profile, the system continuously adapts the operational speed band to match predicted obstacle locations and characteristics, enabling energy optimization while maintaining manageable control complexity through adaptive rather than static control.
2Productivity
If the vehicle accelerates quickly to reduce journey time, then productivity increases, but energy consumption and friction braking increase
Solution Approach 1:
The system pre-identifies time-dependent obstacles and calculates optimal acceleration profiles that balance journey time reduction with energy conservation. By knowing obstacle locations in advance, the vehicle can accelerate efficiently toward optimal points then coast or decelerate smoothly rather than braking abruptly, thereby reducing both journey time and energy consumption simultaneously.
Solution Approach 2:
The system converts the potential harm of friction braking into beneficial coasting behavior. By anticipating obstacles and planning speed trajectories in advance, the vehicle naturally decelerates through coasting rather than friction braking, transforming what would be energy-wasting braking events into energy-saving opportunities while maintaining productive journey times.
3Use of energy by moving object
If the vehicle coasts more to save energy, then energy efficiency improves, but journey time increases
Solution Approach 1:
The system dynamically balances coasting duration and acceleration timing based on predicted obstacle locations. Instead of prolonged coasting that would extend journey time, the system performs targeted coasting maneuvers only where and when they provide energy benefits without significantly impacting arrival time, thereby optimizing the trade-off between energy efficiency and productivity.
Solution Approach 2:
The system changes the operational parameters (speed, acceleration, coasting duration) based on the identified time-dependent obstacles and their temporal characteristics. By adjusting these parameters dynamically rather than using fixed coasting strategies, the system achieves energy efficiency improvements while minimizing the impact on journey time through optimized parameter selection.
Data Source
AI summary
The present disclosure relates to a method of generating a target operational speed band (53; 63; 67) for a host vehicle (1) travelling along a route. A first time-dependent obstacle (15-n, 18-n) is identified at a first location on the route. The first time-dependent obstacle (15-n, 18-n) is identified as hindering progress of the host vehicle (1) during a first time period (11). The first time-lin dependent obstacle (15-n, 18-n) is defined in a two-dimensional speed against distance map (50, 60). A first speed trajectory (51, 52; 61; 65, 66) is determined from a first point to a second point within the two-dimensional speed against distance map (50, 60). The second point represents the first location on the route and the determined first speed trajectory (51, 52; 61; 65, 66) represents the host vehicle (1) arriving at the first location at a first arrival time. The target operational speed band (53; 63; 67) is determined such that the first speed trajectory (51, 52; 61; 65, 66) forms one of an upper limit and a lower limit of the target operational speed band (53; 63; 67). The first arrival time is outside said first time period (11). The present disclosure also relates to a controller (2) for generating a target operational speed band (53; 63; 67); and to a vehicle (1).