Autonomous Vehicle Pickup Mapping from Passenger Walking Distance
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Solution Overview
Problem
Autonomous vehicles face challenges in coordinating pickup and drop-off locations with passengers, leading to inconvenience due to difficulties in determining optimal stopping points, especially for passengers with disabilities or in crowded areas.
Innovation Solution
A method that assesses the inconvenience of pickup and drop-off locations by calculating the observed distance a passenger travels from the road edge to the vehicle using data from the vehicle's perception system, generating an inconvenience value, and incorporating this data into maps to guide autonomous vehicles in selecting more convenient locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles use automated dispatch instructions for pickup locations, then operational efficiency is improved, but coordination difficulty with passengers worsens leading to increased inconvenience
Solution Approach 1:
The system implements feedback by using the perception system to observe passenger positions and movements, then using this information to determine whether the passenger has successfully reached the vehicle. This closed-loop feedback mechanism allows the autonomous vehicle to adapt its pickup process based on real-time passenger behavior, resolving the coordination difficulty while maintaining automated operation.
Solution Approach 2:
The perception system automatically detects and tracks passenger movement toward the vehicle without requiring manual intervention or communication. The system serves itself by autonomously determining pickup success based on observed passenger position data, eliminating the need for human-to-human coordination while maintaining ease of operation for passengers.
2Object-affected harmful factors
If autonomous vehicles stop further from road edges to improve safety, then safety is improved, but passenger access difficulty increases
Solution Approach 1:
The system dynamically adjusts the pickup location selection by considering both safety requirements (distance from road edge) and passenger access convenience. The computing device evaluates multiple potential pickup locations and selects optimal points that balance safety constraints with minimal passenger walking distance, allowing the vehicle to adapt its stopping position based on real-time conditions.
Solution Approach 2:
The system changes the parameter of pickup location position by selecting different stopping points along the road. By optimizing the distance from the road edge while minimizing passenger travel distance, the system adjusts this critical parameter to simultaneously improve safety and maintain ease of access, rather than using a fixed stopping distance.
3Adaptability or versatility
If traditional taxi services use physical signals or phone calls for location coordination, then communication flexibility is improved, but determination difficulty of optimal pickup locations worsens
Solution Approach 1:
The system replaces mechanical communication methods (physical signals, phone calls) with an automated perception and computing system. The perception system uses sensors to detect passenger positions and the computing device processes this data to automatically determine optimal pickup locations, substituting human communication with automated detection and measurement systems that objectively identify best stopping points.
Solution Approach 2:
The perception system and computing device act as an intermediary between the autonomous vehicle and the passenger. Instead of direct human-to-human coordination, this intermediate system translates passenger location data into optimized pickup point selections, mediating the interaction and objectively determining optimal locations based on measured data rather than subjective communication.
Data Source
AI summary
Aspects of the disclosure relate to generating map data. For instance, data generated by a perception system of a vehicle may be received. This data corresponds to a plurality of observations including observed positions of a passenger of the vehicle as the passenger approached the vehicle at a first location. The data may be used to determine an observed distance traveled by a passenger to reach a vehicle. A road edge distance between an observed position of an observation of the plurality of observations and a nearest road edge to the observed position may be determined. An inconvenience value for the first location may be determined using the observed distance and the road edge distance. The map data is then generated using the inconvenience value.