Smart cars
Smart cars are vehicles equipped with advanced technologies that enhance safety, navigation, and mechanical efficiency. Often referred to as "biometric cars," they can respond to various driving conditions, such as alerting drivers who may be drowsy or distracted. These cars utilize a combination of mathematical modeling, artificial intelligence, and real-time data to monitor both their internal systems and external environments, aiming to prevent accidents and improve overall driving performance.
Key features may include advanced driver assistance systems that detect and respond to dangerous driving behaviors, as well as systems that can predict potential hazards based on road and weather conditions. Smart cars have evolved significantly since their early models, which often catered to urban environments, such as the Smart Fortwo. Today, the development of fully autonomous vehicles is a focal point in the automotive industry, with varying levels of automation defined by the Society of Automotive Engineers (SAE). This includes levels where human intervention is required to fully autonomous operation, allowing for a range of functionalities that aim to enhance driver safety and efficiency on the road. The future of smart cars may incorporate even more innovative features, such as dynamic surface adjustments for improved aerodynamics and interconnectivity with smart infrastructure.
Smart cars
- SUMMARY: A smart car is able to respond to the conditions it detects, such as sounding an alarm if it detects that a driver is becoming drowsy.
A smart car is also sometimes referred to as a “biometric car.” The overall design and technology of such vehicles should incorporate many functions: protection of the driver and passengers, reliable and easy navigation, and better mechanical and fuel efficiency. Mathematicians, engineers, and many others are involved in the development of improved vehicle technology. This includes aerodynamics and computerized systems that use mathematical techniques from geometry, mathematical and computer modeling, and statistical analyses of data regarding safety, ergonomics, and consumer preferences. Methods from artificial intelligence, such as cellular automata, are also very useful. According to mathematician John von Neumann, cellular automata can be thought of as “cells” or agents that behave according to relatively simple sets of mathematical rules or algorithms. These rules include responses to neighboring cells’ behaviors, making them useful in modeling many biological processes, like flocking birds or traffic.
Ideal Functions
In many peoples’ minds, the primary purpose of a smart car should be to help a driver in ways that prevent accidents and encourage safe driving. For example, many car accidents occur because drivers do not realize that they are drowsy, so they consequently fall asleep at the wheel. A biometric smart car could alert drivers to such conditions by measuring eye movements relative to typical alert driver behavior to detect inattention and lack of scanning of the instruments and the road. Drivers that deviated too far from established safety norms would then be alerted. Other systems may involve a steering detector that responds to angular movements of the steering wheel that exceed a specified degree or a system that measures the angles of a driver’s head and sound an alert if the head nods too far forward. In 2010, a Japanese company launched a system designed for commercial truck drivers that analyzes a driver’s unique patterns and variability taking into account variables such as time. It then uses mathematical algorithms to proactively recommend rest breaks and measures to increase alertness and safety.
But What Actually Makes a Car Smart?
In addition to reactive systems like driver alertness warnings, some feel that a truly smart car should anticipate conditions to be avoided. Speeding when road conditions are poor or attempting to pass another car in low visibility could be predicted and avoided. Smart car systems would not only anticipate but also correct any anomaly so that a driver has time to recover. Further, they might suggest actions to a driver in advance of adverse conditions by monitoring the road and weather. Aspects of these features are present in many models of cars at the start of the twenty-first century facilitated by the introduction of real-time technology, such as interactive maps and global positioning systems (GPS), which depend on external communication with the environment to provide data beyond the drivers’ senses. For example, many agencies provide data on road grade and surface, work zones, hazards, or speed restrictions. A smart car also monitors its internal state, taking measures of aspects like tire pressure and fluid levels using electronic sensors—functions that used to have to be performed by hand.
Advanced instrumentation, once found mostly in luxury cars, is becoming commonplace in vehicles. These systems may include smart starting that relies on electronics embedded in the car’s keysbiometric features, like fingerprint scans or keyless entry that may also require a computer chip, code, or fingerprint to activate. Many hybrid gas–electric vehicles balance energy usage to obtain maximum performance in mileage. Future smart cars may automatically sense variables like weight distribution and suggest load adjustments for better balance and braking. There are even notions that future smart cars will be able to dynamically reshape their surfaces for maximum aerodynamic efficiency. There is work being done on systems such as neural networks that may monitor and analyze all driver decisions in order to better provide feedback for safety and performance for particular geographic regions. Networks within smart cars may also interact with other cars and “smart roads,” which could use computer technologies and mathematical modeling or algorithms, coupled with control and communications features, to improve issues like road safety and traffic capacity by directing traffic and helping drivers make better and safer decisions.
Smart Cars in the Twenty-First Century
Smart cars are typically associated with mini-sized cars or self-driving vehicles. An example of the former is the Smart Fortwo“for two” peoplefirst manufactured by Daimler in 1998, and then by Daimler’s Mercedes division in subsequent decades. This car was designed for fuel efficiency, affordability, and ease of operation in dense urban areas. The vehicle, however, subjected passengers to bumpy, noisy rides. While smaller vehicles were a staple in Europe, these seemed more out of place in the United States where consumers favored bigger cars. After 2017, only electric models were available in the US. Because of lagging sales, the model was discontinued in North America after 2019.
Efforts to manufacture self-driving vehicles received much notoriety in the 2010s and 2020s. According to the Society of Automotive Engineers (SAE), there are six characteristics that define automated driving. These range from full control by a driver, to vehicles that can operate without any input from a human. The upper-most level is considered a fully autonomous vehicle. SAE Levels 0-3 characterize human drivers with increasing higher levels of automated support features such as breaking, steering, and lane centering. SAE Levels 3-5 are used to describe where a human is not driving. The different levels are distinguished by hand-free driving where the human passenger has varying levels of interventions. For example, in SAE Level 3, a human driver must take control in specific situations such as a traffic jam. In SAE Level 5, the vehicle drives under all conditions.
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