CityDrive.AICEI
Commuter Efficiency Intelligence — A CityDrive.AI Platform

Every signal.
Every corridor.
Finally measurable.

CEI gives a metropolitan authority the one thing it has never had: a continuous, commuter-weighted view of how its city actually moves — by hour, by corridor, by signal. Delivered through a proprietary intelligence layer built specifically for municipal command.

120
Corridors monitored
Continuous
Intelligence cadence
24mo
To full embed
01 — The problem

The most data-rich
moment in transport.
The least informed decisions.

Cities generate more data about how they move than ever before. The data exists. The intelligence does not.

15–20km/h

Average peak-hour speed on major metropolitan arterials, against 50 km/h design capacity.

Source — TomTom Traffic Index
150hrs

Productive hours lost per commuter, per year, to congestion alone. Nearly four working weeks.

Source — BCG Mobility Index
5–10yrs

Age of the traffic studies behind today's signal timings in most metropolitan corridors.

Source — Transport authority audits
02 — How it works

Independent benchmark.
Direct measurement.
Their disagreement is your signal.

CEI is built on a single conviction: real urban intelligence emerges only when an independent reference meets a direct observation — and the two are forced to reconcile.

Conventional traffic management asks two questions and answers neither cleanly. Public mapping services tell you what the aggregate fleet experiences, but they are opaque, third-party, and not subject to municipal verification. Existing infrastructure tells you what was observed locally, but without an external reference it cannot tell you whether what was observed was good, bad, or expected.

CEI resolves both, simultaneously. A proprietary intelligence layer reconciles an external benchmark against direct on-the-ground observation, segment by segment, signal by signal, across every monitored corridor — every fifteen minutes during peak hours, around the clock.

The intelligence appears where the two disagree. Agreement confirms congestion observed two ways. Disagreement — when the benchmark says moving but the observation says queued, or vice versa — is an anomaly. Anomalies are where bottlenecks live, where signal timing has decayed, where infrastructure damage is suppressing throughput, where the operational story differs from the public story. This is the layer no incumbent system gives you.

Layer 01 — Reference

Independent benchmark

A vendor-neutral external reference for aggregate fleet behaviour, sampled continuously across every monitored corridor and time window.

Reference Observation Anomaly
Layer 02 — Observation

Direct measurement

Ground-truth measurement of actual segment-by-segment journey performance, derived from existing municipal infrastructure without parallel build-out.

03 — In operation

What your traffic branch
sees, every Monday at 0700.

Five operational artefacts, delivered on a weekly cadence, designed for the rhythms of a metropolitan command structure.

/ 01
Live Map

Real-time congestion map

Every monitored corridor colour-coded by current congestion ratio. Refreshed every five minutes. Click any corridor for its 24-hour trend, the bottleneck location, and the recommended action.

Delivers — Live ops view
/ 02
Weekly Brief

Hotspot Report

Ranked list of the week's twenty worst corridors with quantified commuter impact, root cause, and intervention recommendation.

Delivers — JCP (Traffic) inbox
/ 03
Signal Scorecard

Per-signal ranking

Green-wave efficiency score, delay attribution, and specific timing recommendation per signal.

Delivers — Signal operations team
/ 04
Intervention Tracker

Closed-loop measurement

Every signal change and deployment decision logged with its measured impact on commuter journey times.

Delivers — Learning organisation
/ 05
Executive View

Single-page dashboard

City-wide index, week-on-week trend, top three concerns, top three improvements. Designed for the City Governments.

Delivers — Weekly leadership review
04 — Evidence

Documented
elsewhere.
Available here.

Four reference deployments across two continents and three decades. The pattern is not theoretical.

Pittsburgh
USA · Carnegie Mellon
System — SURTRAC
25%
Travel-time reduction; 40% wait-time reduction across deployed corridors. Adaptive signal control with decentralised coordination.
Sydney
Australia · TfNSW
System — SCATS
$3.6bn/yr
Sustained annual economic benefit, continuously, for over four decades. Software now deployed in 216 cities across 33 countries.
Stockholm
Sweden
System — Congestion-charge cordon
30–50%
Congestion reduction on inner-city arterials. 20% traffic reduction. 10–14% emissions reduction. Referendum-validated outcome.
Singapore
LTA · IBM partnership
System — TrEPS
85–90%
Prediction accuracy for congestion one hour ahead. Validated combination of historical pattern data and real-time feeds.
Engagement

A six-week scoping engagement, structured for mutual evaluation.

The CEI team works with your traffic operations to select a representative set of corridors, audit the existing infrastructure, complete the data-protection review, and produce a final commercial proposal your office can consider with full information. Defined scope, defined duration, defined deliverables — designed for both teams to establish operational fit before any wider commitment is contemplated.

The case

For an investment of less than one-thousandth of the annual cost of congestion to a major metropolitan area, that city can operate traffic on evidence rather than intuition.