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M.TechInterior & ergonomicsAdvanced About 8 weeksSolidWorks & Alias

HMI Control Placement and Reach Zones in an EV Cockpit

Study where to place touchscreen and physical controls in an EV cockpit using reach envelopes, glance zones and a physical buck, modelled in SOLIDWORKS and surfaced in Autodesk Alias, with measured reach times from user trials.

Tools: SOLIDWORKS · Autodesk Alias

HMI Control Placement and Reach Zones in an EV Cockpit: Electric scooter in the DIYguru EV lab during a training session
Representative photo from DIYguru's EV lab, not of this specific project.

The problem

EV cockpits increasingly move controls onto touchscreens, which can increase the time a driver looks away from the road. Where controls sit, how big they are and whether they are physical or on-screen all affect reach and glance time. A measured placement study gives evidence instead of opinion.

Objectives

  • Build reach envelopes and glance zones for a driver package from published data.
  • Define candidate layouts that mix touchscreen and physical controls.
  • Build a physical buck from the CAD layout and measure reach and task times with volunteers.
  • Recommend a layout with evidence and surface it in Alias.

What you need

Tools and toolboxes

  • SOLIDWORKS Part, Assembly and Configurations — Driver package, reach envelope surfaces and candidate layout configurations.
  • SOLIDWORKS Surfacing — Building reach envelope surfaces from tabulated reach data with Boundary Surface or Lofted Surface.
  • Autodesk Alias — Surfacing the instrument panel and control clusters for the chosen layout, with Zebra and Continuity checks.
  • SOLIDWORKS Drawings — Buck build drawings and control position tables.
  • Excel or a statistics package — Analysing reach times, errors and glance counts from the trials.

Software

  • SOLIDWORKS 2023 or later
  • Autodesk Alias 2024 or later
  • Excel or a statistics package

Extra parts and data

  • A simple driver buck (seat, steering wheel, frame) — Real reach and task times can only come from people in a physical setup.
  • A tablet or touchscreen and 3D-printed control mock-ups — Needed to run the touch and physical control tasks.
  • A camera for glance recording — Glance count and duration are measured from video of the participant's eyes or head.

Key concepts

Reach envelope
The surface in space that a driver can reach with a hand while belted and seated. Practices such as SAE J287 describe how to build it; check the current edition.
Eyellipse
A statistical ellipse of driver eye positions used to judge vision, described in practices such as SAE J941.
Glance time
Time the driver's eyes are off the road during a task. Shorter, fewer glances are safer.
Fitts' law
Movement time to a target grows with distance and falls with target size, which helps explain why small, far controls are slow to use.

Step-by-step guide

  1. 1

    Set the scope and package

    Choose an example compact EV cockpit and list the controls to study: climate temperature, fan, demist, drive mode, volume and hazard lights. Build a SOLIDWORKS driver package with H-point, seat back angle, steering wheel and eye point region from stated data. Note which practices you follow for reach and vision, such as SAE J287 and SAE J941, and that you should check the current editions.

    Checkpoint: A list of controls and tasks and a package assembly with named reference points.

  2. 2

    Build reach envelopes

    Tabulate reach distances from your chosen source for a small driver at several heights and lateral positions. Create 3D sketch points from the table and loft or boundary-surface them into an envelope surface. Add a reduced envelope for the reach with the shoulder held back by the belt. Colour the envelopes and check that the steering wheel rim sits inside the comfortable zone.

    Checkpoint: Envelope surfaces built from tabulated values with the source cited, and the steering rim inside the envelope.

  3. 3

    Define glance zones

    From the eye point region, draw sight cones to the road ahead, the instrument cluster and the centre screen. Measure the angle between the road line and each control location. Define zones, for example within about 30 degrees of the road line, as preferred for frequently used controls, and state where the threshold comes from or that it is a study assumption.

    Checkpoint: A table of downward and lateral angles from the road line to each candidate control location.

  4. 4

    Create candidate layouts

    Create three configurations: all controls on the centre touchscreen, a split layout with climate and hazards as physical controls below the screen, and a layout with steering-wheel buttons for the most frequent controls. Model controls as simple bodies with sizes you state. Measure each control's distance outside or inside the reach envelope and its glance angle. Keep the same control sizes across layouts so that only position and type change between them.

    Checkpoint: Three configurations, each with a table of control positions, reach margins and glance angles.

  5. 5

    Build the physical buck

    Make drawings of a simple adjustable buck from the CAD layout: seat at the H-point, steering wheel at the package position and a panel that holds the screen and control mock-ups at each layout's positions. Build it from timber or aluminium profiles and 3D-printed controls. Measure the built positions and compare them with CAD so errors are known. Make the panel fixings adjustable so all three layouts can be set up on the same buck during one session.

    Checkpoint: A built buck whose control positions match CAD within a stated tolerance, for example 10 mm.

  6. 6

    Plan the user trial

    Write a protocol: participant sizes, the task list, the order of layouts randomised between participants, a simple primary task such as following a moving dot on a screen to load attention, and measures such as task time, errors and glances. Get approval from your institute's ethics committee before recruiting. Run a pilot with two people to fix the protocol. Decide the sample size before you start, with a short justification, and plan how you will store data anonymously.

    Checkpoint: An approved protocol and pilot results showing the measures can be recorded reliably.

  7. 7

    Run trials and analyse

    Run each participant through all layouts, recording task time with a timer or video, errors and glance count and duration from a camera. Enter data into a spreadsheet and compare layouts with paired tests or a repeated-measures analysis suited to your sample size. Report means with spread, not just averages, and check whether driver size changes the result. Code glances from video with two people independently for a subset and compare their counts to check reliability. Note any participant who could not complete a task and why.

    Checkpoint: A results table and plots of task time and glance time per layout, with a stated statistical test and its outcome.

  8. 8

    Surface the chosen layout

    Import the package and chosen control positions into Alias. Build the instrument-panel and control-cluster surfaces with Skin and Square, blend them with Surface Fillet and check continuity and reflections with Zebra. Keep the controls at the tested positions so the styling does not undo the ergonomic result. Export a STEP file for engineering. Run Diagnostic Shading for draft on the moulded faces and check that the screen bezel does not block the road view. Note any position changes the styling forced and retest them if they are large.

    Checkpoint: Alias surfaces that hold the tested control positions and pass the continuity checks on visible boundaries.

  9. 9

    Report and recommend

    Report the package, envelopes, glance zones, candidate layouts, trial protocol, results and the recommended layout, with renders of the final surfaces. Be clear about limits: a static buck, a simple primary task and a small sample. Recommend what a driving simulator study would add. Avoid presenting the result as proof of road safety. Include the protocol, an anonymised data summary and the statistical outputs in appendices so the analysis can be checked. Say which results designers can use now and which need more evidence.

    Checkpoint: A report with evidence-based recommendations and clearly stated limits.

Testing & validation

  • Reach envelopes built from a cited source.
  • Buck positions measured against CAD.
  • Ethics approval and a piloted protocol before trials.
  • Statistical comparison of task and glance times between layouts.

Expected results

A measured comparison of three EV cockpit control layouts, with reach and glance geometry from CAD, task and glance times from a physical buck, and a recommended layout surfaced in Alias.

Research angle for your M.Tech thesis

The research question is how control placement and control type affect task time, errors and glance behaviour, and whether CAD measures such as reach margin and glance angle predict the trial results. A correlation between CAD geometry and measured performance would give designers an early screening method. Metrics: task time, glance count, total eyes-off-road time, errors and subjective workload.

Take it further

  • Repeat the study in a driving simulator with a real driving task.
  • Add haptic feedback to the touchscreen and compare.
  • Study left-hand and right-hand drive mirror layouts.

Viva and review questions

Why did you build a physical buck instead of only using CAD?

CAD can show whether a control is reachable, but not how long a task takes or how often the driver looks away. Those need real people.

Why randomise the order of layouts?

Participants get faster with practice, so a fixed order would favour later layouts. Randomising spreads the learning effect.

What does Fitts' law tell you about the touchscreen?

Small targets far from the hand take longer to hit, so small on-screen buttons at the edge of reach are slow, which matches what we measured.

Learn it at DIYguru

These DIYguru courses and programmes teach what this project needs.

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