Intelligent Transportation System (ITS) and Collaborative Intelligent Transport System (C-ITS) for Smart City and Autonomous Vehicles
The cost involved with traffic congestion is continuously rising and has exceeded US$ 26 billion solely in South Korea. With growing concerns for pollution and strains from the growing population, different technologies and transport systems are being explored to optimize the traffic control for less traffic congestion, less travel time on the road and less pollution.
Intelligent Transport System (ITS) aims to provide innovative services relating to different modes of transport and traffic management and enable users to be better informed and make safer, more coordinated, and smarter use of transport networks.
ITS has recently evolved to Collaborative Intelligent Transport System (C-ITS). C-ITS will allow road users and traffic managers to share information and use it to coordinate their actions enabled by digital connectivity between vehicles and between vehicles and transport infrastructure. Vehicles, infrastructure, and other road users will be able to communicate not only to increase the safety but for future fully autonomous vehicles.
For example, vehicles will be able to analyze the data received and warn the driver against dangers, e.g. congestion in tunnel, approaching to a construction site, a car ahead pulls over suddenly etc. This way, cooperative systems can support foresighted driving, display dangers that are not even visible to the driver and help avoiding accidents.
C-ITS will play a vital role for self-driving vehicles. To enable fully automated driving,(1) Self-driving cars should be able to sense, decide and control the vehicle reliably in any conditions. Also (2) Infrastructure, such as road facilities, roadside sensors or transportation centers or communication systems should be highly advanced too to be able to accommodate and support self-driving cars.
The current sensors that are being utilized for Advanced Driver Assistant System (ADAS) have limitations. For example (a) if the lanes are not visible, (b) the vehicle approaches the unexpected construction site, (c) there is heavy rain or fog, or (d) there is severe traffic jams, the functions of ADAS are highly likely to be compromised. In this case of scenario, the role of sensors within infrastructure become more important. And C-ITS will play more important roles once the self-driving cars are introduced to the market.
Problem - limitation of the current sensors
Loop coils are the most used to detect passing vehicles and they are relatively cheap. However, because they should be installed underneath the concrete, it is invasive and needs unnecessary road works. Accuracy is also an issue as the speed is defined based on the point of contact with the loop coil.
Camera sensors can capture license plate and model of the vehicles and it can even detect the possibilities of drowsy driving. However, it cannot detect well under harsh weather condition and/or at night in the dark.
Radar sensors are often used to collect traffic information by individual lanes. It could be utilized for the collection of nos. of vehicles, individual vehicle speed and accident situations regardless of the weather conditions. But because of its’ low resolution radar cannot distinguish different types of vehicles.
Camera Integrated ITS Traffic Radar – AIR Traffic
Bitsensing proposes a Camera Integrated ITS Traffic Radar, AIR Traffic, a 2020 CES innovation award winner, capable of monitoring various traffic information such as speed, counting, occupancy rate or incident detection on road in real-time. It can read up to 128 vehicles simultaneously, detects 300 meters in range, classifies different types of vehicles and is able to monitor 4 different individual lanes at the same time. Also, its auto-calibration function allows the AIR Traffic to return to the default position to maintain with the optimal detection results regardless of the environmental conditions.
The RADAR based data size is very small yet critical to be passed smoothly to the clients’ server in real-time for data processing for the real-time navigation and/or map. These data can be not only used to optimize traffic control and provide real-time navigation service but also be used as a fundamental foundation for true V2X communication to acquire safety level required for the era of autonomous driving.
Bitsensing is Radar Technology Company to shape and redefine road infrastructure in the era of autonomous vehicle. Our goal is to deliver a high resolution 4D Imaging Radar that is unaffected by any weather conditions such as heavy fog that is cost-effective enough to be commercially viable. Our 4D Imaging Radar sensor will enable autonomous driving by fulfilling all the necessary criteria required by AV sensors and will significantly improve the safety level for self-driving cars, bringing Level 4 self-driving closer.
Before introducing out 4D Imaging Radar to the market, we are adopting our Radar solution to establish infrastructure on the road to enhance safety starting with 24GHz AIR Traffic. AIR Traffic collects and provides real-time traffic data for navigation/map and it will be used to build V2X infrastructure for Smart City and Self-driving Cars.