TIDS · TRAIN INTELLIGENT DETECTION SYSTEM

Intelligent Train Obstacle Detection Solution

Give Trains Independent Forward-environment Perception

LiDAR, industrial cameras, optional millimeter-wave radar and intelligent algorithms actively perceive trains, people, intruding objects and signal states during normal operation, degraded modes, line inspection, commissioning and depot shunting.

Explore the Complete SolutionConsult a Solution Specialist
01 Autonomous Positioning02 Obstacle Detection03 Signal Recognition04 Risk Output
CUSTOMER VALUE

Customer Value Summary

Give train crews continuous forward risk alerts to support anomaly detection and response.

Support risk detection

Detect people, vehicles and obstacles ahead to supplement the driver's lookout and identify potential hazards.

Support varied operating scenarios

Configure alerts for service operation, degraded operation, testing and shunting to support crews across operating conditions.

Support event review

Link targets, positions and alert records so operators can review events and inform operational improvements.

INDEPENDENT ONBOARD PERCEPTION

Add a Continuously Forward-looking Pair of Eyes beyond Existing Systems

Centered on onboard perception, TIDS does not rely on a single vehicle sensor or signaling position. It combines active and passive sensing to identify objects along the train's potential path and assess risk.

Complete DeliveryComplete TIDS Intelligent Train Obstacle Detection System
OPERATIONAL GAPS

Four Protection Gaps in Complex Rail Operations

01

Intruding Objects Are Hard to Detect in Time

When drill rods, blast doors, trees, cables or other objects enter the safety clearance, conventional systems lack direct perception of non-vehicle obstacles.

02

Degraded Operation Relies on Human Lookout

When signaling or vehicle systems degrade, safety depends more heavily on drivers and dispatchers, affecting response time and consistency.

03

Incomplete Protection during Commissioning and Shunting

During line inspection, trial runs, cross-line operation and depot shunting, existing systems may not fully protect against trains ahead, buffer stops and personnel.

04

Complex Environments Challenge Perception Stability

Tunnel lighting transitions, curves, gradients, turnouts, rain, snow and fog continually change visibility and target appearance.

OPERATING SCENARIOS

Cover Normal Operation, Degraded Modes, Commissioning and Shunting

Configure target recognition, alerts and vehicle-interface strategies according to operating rules and the protection boundaries of existing systems.

01

Normal Operation

Continuously perceive intruding objects, people in platform track areas, and buffer stops on sidings or terminal tracks.

02

Degraded Operation

Provide independent perception of trains ahead, signals, buffer stops and track objects when signaling or vehicle systems are degraded.

03

Line Inspection & Commissioning

Support train-ahead protection and detection of people and small objects during commissioning, reducing the burden of manual lookout.

04

Depot Shunting

Cover depot doors, buffer stops, vehicles ahead, trackside personnel and abnormal obstacles along shunting paths.

INTEGRATED ARCHITECTURE

Coordination across Perception, Computing and Vehicle Interfaces

Multiple sensors collect environmental data on a shared time base. The main computer performs fused perception and risk assessment, then outputs results to the driver or vehicle system.

PERCEPTION
Industrial CamerasLiDARMillimeter-wave Radar Optional
↓
EDGE INTELLIGENCE
Synchronization & FusionAutonomous PositioningTarget RecognitionRisk Calculation
TIDS Main Computer
↓
VEHICLE INTERACTION
DMI DisplayAudible & Visual AlertsVehicle BusBraking Interface
TIDS autonomous train perception technologies and system components
Documented Key Technologies and Architecture for Autonomous Train Perception
CORE CAPABILITIES

From Seeing a Target to Producing Actionable Information

01

Perception-based Autonomous Positioning

Match point clouds to a high-definition map for real-time autonomous train positioning and a spatial reference for filtering targets along the route.

02

Forward Obstacle Detection

Identify trains, people, buffer stops and foreign objects entering the safety clearance along the train's potential path.

03

Signal Aspect Recognition

Recognize red, yellow, green and other signal aspects during mainline operation or shunting to support driving and protection logic.

04

Risk Calculation & Interface Output

Calculate risk from vehicle speed, braking performance and obstacle distance, then output warnings and intervention information through the DMI, vehicle bus or braking interface.

<1sResponse to Sudden Events
≥300mTrain-ahead Warning Distance
≥120mPersonnel Detection Distance
≥50m30×30 cm Object Detection Distance

These are representative values under the documented test conditions; distance values correspond to straight track. Actual performance depends on vehicle type, line, weather, installation and system configuration. Project specifications and acceptance results prevail.

REAL-TIME DETECTION

Detect Targets and Determine Whether They Affect the Train's Path

Using train position, track geometry and safety clearance, the system filters targets relevant to the train from complex point clouds and images, reducing interference from adjacent-line vehicles and objects outside the clearance.

  • Dynamic tracking and distance calculation for trains ahead
  • Detection of people, buffer stops and small objects
  • Path assessment on straight track, curves, gradients and turnouts
  • Continuous perception by day, night, rain and snow
TIDS forward train recognition interfaceTIDS train detection at nightTIDS track detection in rain
FLEXIBLE OPERATING MODES

Map-based and Map-free Operating Modes

01

Map-based Mode

Use a 3D high-definition map for autonomous positioning, obstacle detection and signal recognition on mapped lines.

Line position reference · Path-associated detection
02

Map-free Mode

Provide forward obstacle detection before an HD map is available, supporting rapid deployment for commissioning, temporary operation and cross-line running.

Reduced mapping prerequisites · Temporary scenario configuration
STANDARD WORKFLOW

Six Steps Form a Complete Perception Loop

01

Synchronized Multi-source Capture

Cameras, LiDAR and optional millimeter-wave radar capture the forward environment synchronously.

02

Autonomous Positioning

Determine the train's real-time position, direction and target trajectories on the line.

03

Target Recognition

Distinguish trains, people, buffer stops, signals and other foreign objects.

04

Clearance Assessment

Determine whether a target enters the protected area based on the line and travel path.

05

Risk Calculation

Combine speed, distance and vehicle performance to define warning or braking-intervention conditions.

06

Output & Recording

Output results to the driver or vehicle interface and retain operational data for review.

SYSTEM DELIVERY

Configure the Complete System to Vehicle Type and Project Scope

Equipment quantity, installation positions, interfaces and braking coordination must be determined from vehicle space, line conditions and safety requirements.

Onboard Sensor Unit
01

Onboard Sensor Unit

Industrial cameras, LiDAR and optional millimeter-wave radar configured to the vehicle and available installation space.

View Product Details ↗
TIDS Main Computer
02

TIDS Main Computer

Performs sensor synchronization, fused perception, autonomous positioning, target recognition and risk calculation.

View Product Details ↗
DMI Driver Display
03

DMI Driver Display

Presents target type, distance, speed, line status and graded warnings to the driver.

View Product Details ↗
Vehicle & Signaling Interfaces
04

Vehicle & Signaling Interfaces

MVB/TRDP bus, signaling network, audible/visual alerts and braking interfaces can be configured to vehicle conditions.

TIDS detection in tunnels, curves, turnouts and elevated sections
ENVIRONMENT ADAPTABILITY

Designed for Real Lines, Not a Single Laboratory Environment

Documentation shows continued data accumulation in tunnels, viaducts, surface sections, curves, gradients and turnouts, with validation under lighting transitions, backlight, rain and snow.

Track Geometry
Straight / Curve / Gradient / Turnout / Viaduct
Lighting Conditions
Unlit / Light transitions / Front light / Backlight / Night
Weather Conditions
Rain / Snow / Fog and other project-defined conditions
FIELD FINDINGS

Make Potential Risks Visible before a Collision

TIDS detects tree intrusion during commissioning
Tree IntrusionDetect trees intruding into the operating clearance during commissioning
TIDS detects a train ahead inside a tunnel
Train in TunnelDetect a vehicle target ahead in an operating environment
TIDS detects a buffer stop and issues an overspeed alert
Buffer-stop ProtectionRecognize the buffer stop and issue a risk prompt during depot return
APPLICATION EXPERIENCE

Multi-line Experience and Engineering Practice

The following are representative line applications from the available materials. Actual project scope is subject to authorized releases and contract terms.

Train on the Tsuen Wan Line in Hong Kong, China
01

Hong Kong, China — Tsuen Wan Line

Perception-assisted driving and long-term line validation

Train on Beijing Metro Line 11
02

Beijing Line 11

Exploration of autonomous perception and backup operation

Train on Beijing Metro Line 12
03

Beijing Line 12

Autonomous train perception and operational safety protection

Train on Beijing Metro Line 13
04

Beijing Line 13

Autonomous positioning, clearance detection and signal recognition

Train on Beijing Metro Line 15
05

Beijing Line 15

Perception assistance for cross-line operation

Train on Beijing Metro Line 17
06

Beijing Line 17

Forward-environment perception and safety protection

Train on Beijing Metro Line 3
07

Beijing Line 3

Line-environment perception and safety protection

Train on the Beijing Airport Express
08

Beijing Airport Line

Airport-line environmental perception

Train on Chengdu Metro Line 13
09

Chengdu Line 13

Clearance protection and backup perception for signaling

Train on Chengdu Metro Line 27
10

Chengdu Line 27

Clearance protection and backup perception for signaling

Train on Chengdu Metro Line 30
11

Chengdu Line 30

Clearance protection and backup perception for signaling

Train on the Chengdu Ziyang Line
12

Chengdu Ziyang Line

Autonomous perception and safety protection for suburban rail

Train on Chongqing Rail Transit Line 24
13

Chongqing Line 24

Line-environment perception and safety protection

Train on Taiyuan Metro Line 1
14

Taiyuan Line 1

Autonomous train perception and line-scenario validation

CONFIGURE FOR YOUR ROLLING STOCK

Configure TIDS for the Vehicle, Line and Protection Objectives

From sensor layout and onboard computing to the DMI and vehicle interfaces, deliver a complete solution aligned with the project's safety boundaries.

Contact a Solution Specialist ↗

Last updated