Behavioral Design Case Study

Reducing Railway Fatalities in India: A Human-Centered Approach to Track Safety

Applying behavioral science and data analysis to understand why nearly 500 people died on railway tracks in one division—and how to prevent future deaths through systemic, equitable interventions.

Overview

Indian Railways carries over 23 million passengers daily, making it one of the world's largest transportation networks. But alongside this scale comes a devastating human cost: in 2023 alone, over 21,800 railway-related deaths occurred nationally, with 72.8% classified as human-run-over (HRO) incidents.

As part of the Behavioral Design Fellowship at First Principles Lab, we partnered with Southern Railways to examine the crisis in Trivandrum Division, Kerala—a 625-kilometer network serving over 7 crore passengers annually. Our research aimed to move beyond simplistic "trespassing" narratives to understand the behavioral, systemic, and infrastructural factors driving these preventable deaths.

Research Team

Kamakshi Arora Service Designer — Data analysis, behavioral frameworks, systems mapping
Kashish Clinical Psychologist — Stakeholder research, psychological barriers, persona development

This case study documents our research phase: problem definition, quantitative analysis, stakeholder interviews, and the behavioral insights that will inform future intervention design.

The Challenge

When we began this project, the problem was framed as "trespassing"—implying individual carelessness or rule-breaking. But our research revealed something more complex: a system where unsafe choices have become the rational ones.

1,855 Deaths from HRO incidents (2020–2024)
86% Incidents classified as "trespassing"
614% Increase: 69 deaths (2020) to 493 (2024)

The data showed a crisis accelerating, not stabilizing. But the "trespassing" label obscured what was actually happening: people making decisions shaped by infrastructure gaps, time pressure, normalized risk, and detection failures.

Our reframe: These aren't reckless individuals breaking rules—they're people navigating a system that often leaves unsafe behavior as the only practical choice.

Approach

Data Analysis

We analyzed five years of incident data from Trivandrum Division, mapping patterns across time, location, and circumstance. Key findings included:

Temporal patterns: 50% of incidents occur during two windows—morning rush (6–9 AM, 25%) and late night (12–3 AM, 25%). January and December showed peak incidents, correlating with post-monsoon tourism and pleasant weather.

Geographic concentration: Six sections accounted for 45% of all incidents. The Ernakulam Junction to Shoranur Junction corridor alone saw 297 incidents—more than double any other section.

Demographic profile: 89% of 2024 victims were male, predominantly working-age men and migrant workers—people whose livelihoods depend on consistent, timely travel.

[ Incident hotspot map visualization ]

Stakeholder Research

Our research combined quantitative analysis with qualitative fieldwork. We conducted interviews with Railway Protection Force (RPF) officials at multiple levels—from control room operators to a Commissioner and DIG—and gathered insights from passengers, trackside community members, and railway workers.

These conversations surfaced the systemic pressures invisible in incident reports: the RPF officer managing 1,134 commuters alone, the track worker relying on sound cues that electric trains no longer provide, the commuter who boards a moving train because missing it means losing a day's wages.

Understanding the People

To move from statistics to actionable insights, we developed four personas representing distinct risk profiles. Each emerged from our research and embodies different behavioral drivers.

[ Rajan illustration ]

Rajan

The Calculated Risk-Taker

Daily commuter from Ernakulam to Chalakkudy. Boards moving trains because missing the 6:15 AM means lost wages. Overcrowding creates competitive boarding; repeated safe crossings normalize the risk.

[ Shri illustration ]

Shri

The Trackside Resident

Has lived near the tracks since childhood. What once felt risky is now routine—crossing is simply part of his daily landscape. The familiarity heuristic has made the danger invisible.

[ Shyam illustration ]

Shyam

The Track Worker

Maintains tracks while trains run—his job requires proximity to danger. Works in extreme heat, relies on vision and sound to detect trains, but curves and silent electric trains make detection nearly impossible.

[ Sayil illustration ]

Sayil

The Stretched RPF Officer

Sub-inspector assigned to a station where passenger traffic increased 12x in one year. Manages 22 different operations with jurisdictional constraints. One officer per 1,134 commuters.

Behavioral Insights

Our analysis revealed several interconnected behavioral and systemic factors:

Normalized Risk

When people cross tracks daily without incident, the perceived danger fades. Social proof reinforces this—if everyone around you crosses, it feels safe. Each successful crossing strengthens the belief that risk can be managed through personal vigilance.

Detection Failures

People crossing tracks rely on sight and sound. But the division has 27 curves sharper than 3 degrees (35% of the network), dense vegetation that limits sightlines, and increasingly silent electric trains. The traditional warning cues—loud engines, strong vibrations—no longer exist.

They get run over because often they don't hear or see the train coming. Sometimes, they move to the adjacent track to avoid a train but end up getting hit by a train coming from the opposite direction.

Infrastructure-Forced Behavior

In many locations, crossing the tracks is the only practical option. The absence of safe crossing infrastructure doesn't eliminate the need to cross—it just makes crossing unsafe. When the alternative to trespassing is a 2-kilometer detour, the "unsafe" choice becomes the rational one.

Occupational Exposure

Track workers face compounding risks: extreme heat affecting cognition, reliance on contract workers unfamiliar with local geography, no train-tracking mechanism beyond sensory cues, and proposed speed increases that will further reduce reaction time.

What gets measured gets managed. The data gaps around worker fatalities mean this population's risks remain invisible to policy.

Synthesis: A Systems View

What appeared to be individual carelessness revealed itself as a confluence of reinforcing factors:

Infrastructure & Access

Physical infrastructure forces unsafe behaviors or excludes users entirely

Detection & Capability

People cannot reliably detect trains in time to make safe decisions

Behavioral & Cultural

Repeated exposure adapts human behavior in ways that increase risk

Occupational Safety

Railway work inherently requires track proximity, creating unavoidable exposure

Technology Gaps

Modern improvements (electrification, speed increases) create new safety gaps

Equity

Safety solutions often work only for privileged or able-bodied users

The curb-cut principle applies: designing for the most vulnerable (track workers in low-visibility zones) will create safety benefits for everyone.

Our Guiding Question

How might we create equitable railway safety that serves all users and nearby communities, while addressing track misuse and improving risk awareness in low-detectability zones?

What Comes Next

This research phase established the problem space and identified the behavioral dynamics driving incidents. The next phase will move from understanding to intervention:

  • Field visits to hotspot locations — Each section has unique characteristics. On-the-ground observation during peak risk windows (6–9 AM, 12–3 AM) will surface context invisible in data.
  • Behavioral observation at transition points — Platform edges, track crossings, decision moments where people choose to cross.
  • Worker shadowing — Accompanying track maintainers during shifts to understand occupational risk in context.
  • Learning from success — Some sections showed dramatic decreases in incidents. Understanding what changed could be as valuable as understanding what's failing.

Our goal: interventions grounded in behavioral science that acknowledge systemic constraints—solutions that work for Rajan rushing to work, Shri crossing to get home, Shyam maintaining tracks, and Sayil managing impossible ratios.

Reflection

This project challenged us to hold complexity without simplifying toward blame. The instinct to frame railway deaths as "trespassing" or "carelessness" obscures the systemic factors that make unsafe behavior rational.

Indian Railways serves as the primary means of travel for millions and employs millions more. In a country striving to be inclusive and equitable, the ability to travel and work safely shouldn't be a privilege. Every citizen deserves the dignity of safety, irrespective of their circumstances.

Research conducted as part of the Behavioral Design Fellowship at First Principles Lab, in partnership with Southern Railways India.

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