Row = affected
“Palayam · primary · R12” means we are asking about that road’s predicted speed.
Compiling the hour
Compiling the hour
Influence
Pick a place in Thiruvananthapuram. The heat map shows which nearby roads are strongly linked in the speed model. Deeper orange = stronger link — not more jam.
Thiruvananthapuram · simple guide
This page shows which roads near your place are linked in the traffic model. Search a place, load the heat map, then read the colors.
How to read one box
Row name = road being affected · Column name = road that affects it
Higher number + deeper orange = stronger link. Lower number + pale box = weaker link. Not traffic jam.
What this page does
Finds 30 roads near your place and shows how strongly they connect to each other.
How to read the table
Each row and column is a road. One colored box = one pair of roads.
Not the Map page
Map page colors = speed. This page colors = connection strength only.
Place in Thiruvananthapuram
Not selected yet
Type a place name. Results come from OpenStreetMap (Nominatim + Overpass), debounced while you type.
Search a place in Thiruvananthapuram (example: Palayam), then click Load heat map.
In plain words
You choose a place — Palayam, Technopark, Kowdiar, Medical College. The page finds about 30 roads closest to that place, then draws a color table of how strongly those roads are linked when predicting speed.
A heat map here is a grid. Each row is a road being affected. Each column is a road that may affect it. One colored box = one pair.
Deeper orange + higher number = stronger link. If road B’s predicted speed changes, road A’s prediction is expected to move with it more. Pale box + lower number = weaker link.
This is not more cars or more jam. Jam and speed colors live on the Map page (green / orange / red). Here color only means “how connected in the model.”
Example: row “Palayam · primary” and column “Connemara · …” with value 0.09 means Connemara affects Palayam’s predicted speed more than a pale 0.03 cell nearby. Top-left after the labels is often a road affecting itself (self link).
1. Search a place (dropdown appears after you type). 2. Click Load heat map. 3. Read the guide box. 4. Scan for deep orange cells. 5. Use the road list under the grid for place name, road type, distance, and predicted km/h.
Same demo forecasts as Predict and Map: date, time, and scenario — not live sensors. If you already ran Predict, Influence reuses that window; otherwise it generates a default demo set.
A jam near East Fort does not stay on East Fort. It can rewrite speeds toward Overbridge and Palayam. Influence makes that rumor visible for one neighborhood at a time, so operators and students can see who is coupled to whom before they look at a route.
Worked example
Suppose you loaded Influence near Palayam. Rows and columns are nearby roads labeled with place and road type.
“Palayam · primary · R12” means we are asking about that road’s predicted speed.
“Connemara · primary · R45” means we measure how much that road pulls on the row.
Strong link: if the column road’s forecast moves, the row road is expected to move with it more.
Weak link: mostly independent in this local matrix.
A deep cell is not “more traffic.” Map page green/orange/red is for speed. Influence is for connection.
Shows place, highway type, distance from focus, and predicted km/h for each road in the matrix.
Common questions
After the color fix: pale = weaker, deep orange = stronger. Also trust the number in the cell — higher means stronger link.
Several OSM edges can sit near the same place name. The R-index suffix keeps each column unique.
The API defaults around city center so you still get a matrix. Prefer searching a place for a meaningful focus.
Yes when you share the last prediction window. Otherwise Influence builds a default demo forecast first.