In the context of the accelerated implementation of intelligent transportation in 2025, LiDAR, with its unique technological advantages, is becoming a core sensor in building future transportation systems. As a high-precision environmental perception device that integrates opto-mechatronics and computing, LiDAR can generate three-dimensional point cloud data with centimeter-level accuracy in real-time by scanning millions of laser pulses per second. This ability makes it irreplaceable in fields such as autonomous driving, traffic management, and road safety.

Currently, the main wavelengths of mainstream LiDARs are 905nm and 1550nm. The 905nm LiDAR is the most common because its receiver can be made of silicon material, which is affordable and gives it a cost advantage. In terms of measurement methods, they are mainly divided into ToF (Time of Flight) LiDAR and FMCW (Frequency Modulated Continuous Wave) LiDAR. The ToF LiDAR directly measures the time difference between the transmitted laser and the echo signal, and calculates the distance to the target object based on the speed of light in the air. This measurement method has a fast response speed, high detection accuracy, high technical maturity, and relatively low cost, making it the most widely used solution at present. The FMCW LiDAR linearly modulates the optical frequency of the transmitted laser, and obtains the frequency difference by coherently beating the echo signal with the reference light, thereby indirectly obtaining the flight time and calculating the target distance. Its advantage is that it can directly measure speed information and has strong anti-interference ability. However, its current technical maturity is low, and it has not been commercially mass-produced yet. According to the scanning method, LiDARs are divided into mechanical, semi-solid-state, and solid-state LiDARs. Mechanical LiDARs appeared early and have mature technology. They perform 360° horizontal scanning and directional vertical scanning by rotation. They have a stable rotation speed, but they have high costs, large sizes, are difficult to meet automotive specifications, are prone to damage, and have poor mass production capabilities. Semi-solid-state LiDARs have fixed transmitters and receivers and scan with a small number of components. They are further divided into rotating mirror types, MEMS types, and prism types. The rotating mirror type relies on a rotating mirror, and its moving parts are motors and mirrors; the MEMS type scans by vibrating a galvanometer and can dynamically adjust the scanning mode, but it has a low signal-to-noise ratio, short detection range, and narrow field of view; the prism type uses non-repetitive scanning technology and can obtain detailed three-dimensional information, but it has a small field of view and motion distortion at high speeds. Solid-state LiDARs have no moving parts and use semiconductor technology. They are divided into Flash and OPA solid-state LiDARs.

Traffic Flow Monitoring

In the field of traffic flow monitoring, LiDAR plays a crucial role. For LiDARs installed above the road, they continuously emit laser beams and scan the road below. When the laser beams encounter moving vehicles, reflections occur. LiDAR can accurately calculate the distance between the vehicle and itself based on the time difference between the emission and reception of the laser beams. At the same time, by combining the scanning angle of the LiDAR, the specific position of the vehicle on the road can be determined. With high-frequency scanning, LiDAR can obtain the distance information of vehicles at various positions on the road in real-time and further convert it into key data such as the number of vehicles, speed, and spacing. On major roads with heavy traffic, LiDAR can perform thousands of scans per minute, precisely capturing the dynamics of every vehicle. Through the analysis of this data, traffic management departments can clearly understand the changing trends of traffic flow on different road sections and at different times. During the morning and evening rush hours on weekdays, the traffic flow on some road sections increases significantly, the vehicle spacing decreases, and the speed drops. All this information can be accurately monitored by LiDAR and fed back to the management department. This data provides solid support for traffic planning, helping to rationally plan road construction, optimize bus routes, and improve the utilization efficiency of traffic resources.

Intelligent Traffic Signal Control

The application of LiDAR in the field of intelligent traffic signal control provides a practical solution to alleviate traffic congestion. At traffic intersections, LiDAR continuously collects traffic flow data. Its working principle is similar to that of traffic flow monitoring, but it focuses more on the vehicle information in each direction of the intersection. It can not only detect the number of vehicles but also accurately track the driving trajectories and speed changes of vehicles. When the traffic flow in a certain direction increases, LiDAR will quickly transmit this information to the traffic signal control system. Based on the data provided by LiDAR and combined with preset algorithms, this system intelligently adjusts the time of traffic lights. At some busy intersections, traditional fixed-time traffic lights are difficult to adapt to the dynamic changes of traffic flow, resulting in long waiting times for vehicles in some directions while the road resources in other directions are left idle. After the introduction of LiDAR, the system can perceive the traffic conditions in each direction in real-time. When the queue of vehicles in a certain direction is long, it will automatically extend the green light time of that direction, shorten the waiting time of vehicles, achieve dynamic optimization control of traffic lights, improve the traffic efficiency of intersections, and effectively relieve traffic congestion.

Pedestrian Detection and Obstacle Avoidance

In urban traffic safety management, pedestrian detection and obstacle avoidance are crucial tasks. LiDAR technology can accurately identify and track the positions and movement trajectories of pedestrians, providing obstacle avoidance prompts for vehicles and preventing collisions with pedestrians. Its high-precision perception ability makes pedestrian detection more accurate and reliable, helping to ensure the traffic safety of pedestrians.

In a smart neighborhood project in Busan Smart City, Seoul, South Korea, a LiDAR – based solution provided municipal officials with the data they needed to understand and reduce the influencing factors of accidents in school areas. The sensors collected a large amount of data about each school intersection area, including vehicle traffic patterns, vehicle speeds, and pedestrian behaviors. This solution can accurately detect people standing in blind spots (such as behind cars), a situation that often leads to pedestrian accidents. The data collected by LiDAR forms the basis for new and more effective traffic policies and helps municipal officials use the best technology to make decisions to ensure the safety of pedestrians and drivers.