Autonomous Vehicle Curbside Mapping for Passenger Walking Distance
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently determining convenient pickup and drop-off locations for passengers, leading to potential inconvenience due to the distance traveled to reach or exit the vehicle, especially for individuals with disabilities or in crowded environments.
Innovation Solution
A method to assess the inconvenience of pickup and drop-off locations by analyzing data from a vehicle's perception system, calculating observed distances and road edge distances, and generating map data to optimize these locations for autonomous vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles use automated dispatch instructions to pickup and drop off passengers, then operational efficiency is improved, but passenger convenience deteriorates due to increased walking distance to reach the vehicle
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal pickup locations that minimize passenger walking distance before the vehicle arrives. The server computing device determines convenient pickup locations based on map data and passenger destination, and notifies passengers in advance, allowing them to prepare for the most convenient pickup point.
Solution Approach 2:
The patent introduces an intermediary communication system between the autonomous vehicle and passenger. The server computing device acts as a mediator that receives passenger destination information, calculates optimal pickup locations, and communicates both to the vehicle's server and to the passenger's client device, coordinating the pickup process to minimize inconvenience.
2Object-affected harmful factors
If autonomous vehicles stop at locations far from road edges to improve passenger safety, then safety is improved, but accessibility deteriorates as passengers must walk longer distances to reach the vehicle
Solution Approach 1:
The system dynamically changes the parameter of pickup location based on multiple factors including passenger destination, road geometry, and safety considerations. The server computing device calculates inconvenience values that balance safety requirements with walking distance, selecting optimal locations that satisfy both constraints rather than using a fixed safety margin.
Solution Approach 2:
The patent applies local quality by determining pickup locations with specific characteristics suitable for each particular situation. Instead of a uniform approach, the system evaluates local conditions such as proximity to road edges, passenger destination, and map data to determine the most appropriate pickup point for each specific case.
3Device complexity
If the vehicle determines pickup location without considering passenger destination, then decision-making simplicity is improved, but passenger satisfaction deteriorates due to inconvenient pickup locations
Solution Approach 1:
The system performs preliminary calculation of optimal pickup locations based on passenger destination before the vehicle arrives. The server computing device receives destination information from the passenger's client device and pre-determines the most convenient pickup location, notifying the passenger in advance, which simplifies the on-site decision-making process.
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.