DSRC Pedestrian Density Estimation for ADAS Adaptability
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Solution Overview
Problem
Current vehicle control systems, particularly Advanced Driver Assistance Systems (ADAS), lack the ability to adapt their behavior in response to varying pedestrian densities near businesses, which can impact safety and efficiency, especially during peak hours.
Innovation Solution
Implementing a pedestrian density system using Dedicated Short Range Communication (DSRC) technology, where DSRC-enabled devices broadcast Pedestrian Safety Messages (PSM) that are aggregated to estimate pedestrian density data, allowing ADAS systems to modify their motion profiles based on real-time pedestrian presence and distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If ADAS systems use fixed motion profiles, then system complexity is reduced, but adaptability to varying pedestrian density conditions deteriorates
Solution Approach 1:
The system pre-establishes multiple motion profiles corresponding to different pedestrian density conditions (low, medium, high) before actual operation. When pedestrian density is detected, the appropriate pre-defined profile is selected and applied, avoiding the need for complex real-time calculations while maintaining adaptability to varying conditions.
Solution Approach 2:
The system dynamically switches between different motion profiles based on real-time pedestrian density detection. The motion profile is not fixed but adapts to current conditions by selecting from pre-defined options, enabling the ADAS system to respond flexibly to changing environmental conditions without increasing fundamental system complexity.
2Reliability
If real-time pedestrian density monitoring is implemented, then safety is improved, but use of energy increases due to continuous DSRC communication and data processing
Solution Approach 1:
Instead of continuous monitoring, the system periodically updates pedestrian density information at predetermined time intervals (e.g., every few seconds). This periodic update mechanism maintains safety by providing timely information while significantly reducing energy consumption compared to continuous DSRC communication and processing.
Solution Approach 2:
The system implements monitoring at a frequency sufficient to ensure safety (partial action) rather than maximum possible frequency. By updating pedestrian density information at intervals that are adequate for safety decisions rather than continuously, the system achieves the necessary safety level while minimizing energy consumption.
3Adaptability or versatility
If multiple motion profiles are maintained for different pedestrian densities, then adaptability is improved, but device complexity increases
Solution Approach 1:
Multiple motion profiles are pre-configured and stored in the system before operation begins. Each profile corresponds to a specific pedestrian density condition and is ready for immediate selection. This preliminary preparation eliminates the need for complex real-time generation and management of motion profiles, reducing operational complexity while maintaining adaptability.
Data Source
AI summary
The disclosure includes embodiments for estimating pedestrian density data based on one or more Personal Safety Messages (PSM message). A method includes, according to some embodiments, receiving, by a first dedicated short range communication (DSRC) chip of a DSRC-enabled vehicle, a PSM message including an instance of pedestrian safety message data (PSM data) describing a geographic location of a pedestrian. The method includes executing an analysis of the instance of PSM data to determine that the pedestrian is present at a business based on the geographic location being within a known geographic area for the business. In some embodiments, this analysis is executed for a plurality of instances of PSM data. The method includes generating pedestrian density data for the business that describes how many pedestrians are present at the business based on executing the analysis for the plurality of instances of PSM data.