Smart Transportation & Cities

Don’t just see the traffic. Investigate it.

CityForensics connects traffic signals, movement patterns and incident data to reconstruct how disruptions begin and spread across a city.

Prototype demonstration using simulated conditions on Madhya Marg, Chandigarh.

5
Propagation stages
3
Intersections traced
5
Evidence signals
Chandigarh Network — Sector Grid Madhya Marg
Sector 17 Sector 18 Sector 19 Sector 22 Sector 21 Sector 20 Madhya Marg Incident
Normal flow Affected Incident Madhya Marg

Investigation Module

Incident Investigation

Follow the chain, not just the congestion. The system traces how one disrupted segment of Madhya Marg propagates into the surrounding sector grid.

Case 04–MG Madhya Marg · Chandigarh · 20 Sep · 10:42 AM
Idle Simulated Incident
Sector 17 Sector 18 Sector 19 Sector 22 Sector 21 Sector 20 Sector 23 Sector 34 Madhya Marg Sector Road 19 Sector Road 21 Incident Origin Intersection B Sector 19 Junction Sector 21 Crossing Sector 18 Signal
Network: Madhya Marg — Sector 17 / 18 / 19 grid
Simulated Demo • Not Live Traffic Data
CityForensics Investigation
Reference · CF-2026-0917-MG
IncidentRoad incident
LocationMadhya Marg, Chandigarh
Time10:42 AM
ClassSimulated incident
Investigation Process 0 / 7
  1. 01Detecting anomaly…
  2. 02Comparing traffic conditions…
  3. 03Correlating nearby intersections…
  4. 04Tracing movement patterns…
  5. 05Testing possible causes…
  6. 06Reconstructing incident…
  7. 07Generating explanation…
Possible Causes
Traffic surge Unevaluated
Signal failure Unevaluated
Road incident Unevaluated
Evidence Correlated
  • Speed reduction detected at 10:42
  • Vehicle density increased on Madhya Marg
  • Movement shifted toward nearby sector roads
  • Intersection overload followed the speed drop
  • Secondary congestion appeared afterward
Awaiting investigation. Evidence will be correlated from simulated signals.
Root Cause
Road incident on Madhya Marg

The observed traffic cascade is consistent with an incident originating on Madhya Marg, followed by speed reduction, intersection overload, rerouting and secondary congestion.

Based on simulated demonstration data.

Simulated Traffic Snapshot Madhya Marg · 10:42–10:45 AM
Average Speed
68km/h
Baseline recorded
Vehicle Density
0%
At normal pattern
Travel Delay
0min
No added delay
Affected Intersections
0
None detected
Secondary Roads
0
None detected
Reconstructed Sequence

Incident Timeline

Reconstructed from the simulated sequence of signal and movement observations between 10:42 and 10:45 AM.

10:42
Road incident detected
Origin
10:42
Average speed drops on Madhya Marg
Impact
10:43
Intersection overload detected
Affected
10:44
Vehicles reroute to sector roads
Rerouting
10:45
Secondary congestion detected
Downstream
Causal Reconstruction

Propagation Chain

The sequence the investigation reconstructs — from the initiating event to the downstream congestion it produced.

01
Incident
Origin detected on Madhya Marg at 10:42 AM.
02
Speed Drop
Average speed decreases across the affected segment.
03
Intersection Overload
Density exceeds the normal pattern at nearby signals.
04
Rerouting
Traffic shifts onto nearby sector roads.
05
Secondary Congestion
Impact spreads downstream to adjoining roads.

Positioning

From Monitoring to Investigation

Monitoring and investigation answer different questions. CityForensics is designed to work alongside established traffic operations, focused on the second question.

Traditional Traffic Monitoring
  • Shows where traffic currently is
  • Reports current speeds
  • Describes current congestion levels
  • Raises current alerts
CityForensics
  • Explains where the disruption started
  • Reconstructs how it propagated
  • Identifies which areas were affected
  • Presents the evidence supporting the cause

We don’t just predict where traffic will be. We investigate why it happened.

See the traffic.Understand the cause.

Respond with context.

CityForensics identifies the initiating event, not just the most visible symptom.