Table of Contents

• 1. General
• 2. Competitors
• 3. Target groups
• 4. Persona
• 5. Features that Users Need

1. General

This section is about the result of researching internet articles, scientific papers, and surveys about optimizing automotive fleets. Here a short overview:

1.1. Online research

Key findings

• reduce costs (decrease in fuel consumption, reduce idle time of automotives, improved routing)
• vehicle maintenance (tires, fuel and oil, and brakes; alerts)
• keeping drivers safe (reduce accidents)
• reduction in labor costs (reduce idle time)
• lower greenhouse emissions (monitoring speed, acceleration, breaking, and idle time)
• enhanced customer service (product tracking, delivery alerts)
• fleet managers have different roles, which need different functionalities (purchasing agents, sales personnel, and supply chain managers)

Resources

• 2015 Fleet and Vehicle Management Survey Findings
• Fleet Management & Asset Tracking Survey
• Fleet Managers and Their Environment: A Survey

Closer examination of sustainability

The dashboard could improve the sustainability of companies Corporate social responsibility

• Reward system
• Social responsibility
• we care for our employees > show best truck drivers
• break times needs to be monitored
• promote communication
• carbon footprint/ ecological footprint
• long term
• green IT
• resource efficient driving
• travel management

2. Competitors

2.1. Intelligent fleet management from Bosch

Features

• Fuel consumption analyses
• Electronic logbook with theft warning capability
• Vehicle localization via gps
• On Board Diagnosis (OBD)
• Meaningful controlling instruments for fleet management
• Maximum data security through modern encryption techniques

2.2. The Uber for logistics

Features

• On-demand availability of carriers: locate the driver that suits you best acording to his location
• Trip Management: Organizing and aligning new carriers acording to their current location
• Keeping a record of all the trips (with details)
• Enabling cost efficency with routes and fuel optimization: design most efficient trips

2.3. Akveo Fleet Management

Features

• Vehicle Meta Data (type / year / licence / plate)
• Key indicators (Battery / Engine / Oil / Gas)
• Vehicle position (current position/checkpoints/ in time?)
• Event notifications (success / errors /warnings / side route / being late / driving / parked)
• Trips overviews ( vehicle / driver / delivery time / products shipped / scheduled / history)
• Real Time Telemetrics (Fuel consumption / Average Speed)
• Vehicle details (driver/type)
• Active and finished trips (status/duration/distance covered/date)
• Maintenance Handling (Planning/History)
• Analytics ( Revenue / Profit / expenses / labor hours / trips performance / co2 emissions / idle time costs / driving distance )

Resource: Akveo Demo

2.4. Transportation & Logistics – Fleet Management Dashboard

Features

• overall (on the way / available / out for maintenance)
• costs (maintenance / fuel / breakdown)
• insurance costs
• oldest vehicles
• type of vehicles (trucks / cars -> filter drill down)

Resource: Transportation & Logistics – Fleet Management Dashboard

2.5. Dashboard—A digital UI Kit - Eugen Design

Resource: https://eugen.store/smart-home-a-digital-ui-kit/

2.6. Analytics Dashboard - Eugen Design

Resource: https://no.pinterest.com/pin/150237337558024631/

2.7. Severny - Bootstrap 4 Admin Template

Resource: https://www.wrappixel.com/demos/admin-templates/severny/src/html/menu-sidebar/index.html

2.8. Severny - Dashboard

Resource: https://www.wrappixel.com/demos/admin-templates/severny/src/html/menu-sidebar/index.html

3. Target groups

These are the identified target groups whose needs would be satisfied with our dashboard. We chose fleet managers as our main target group:

1. Fleet managers (purchasing, optimizing and maintaining automotive fleets)
2. Decision makers (controlling, finance, logistics)

Motto

• Sustainable performance optimization of vehicle fleet
• building solution for a better future

4. Persona

Background:

• Klaus is a trained merchant for forwarding and logistics services
• 30 years of work experience
• Employee of a large Europe-wide forwarding agency
• Head of fleet management
• Responsibilities: planning and reporting

Demography:

• 50 years old
• Male
• Married
• 3 children

Identifiers:

• Part of the business for many years, he´s more like an “old school” guy
• Klaus developed his own way of handling the fleet management
• Fleet management is his “baby”, he uses Excel for everything
• When it gets stressful, it’s sometimes hard for him to keep an overview

Challenges:

• The boss of Klaus wants him to be more efficient, but right now he really doesn’t know how. He has access to a lot of data, but he doesn’t know how to handle it and get the most out of it. Expectations, goals & emotions:
• Klaus hopes for a system that let him keep control of the situation even if it gets very stressful.
• Klaus wants to live up to the expectations of his bosses
• Klaus hopes to save time in evaluating his daily key figures

Ideal solution:

• An evaluation and clear presentation of the given data that represent meaningful information for Klaus and can be used to increase efficiency
• Thanks to automated evaluation and clear presentation of the most important key figures, the tours can be made more efficient and the saved time can be used differently and therefore has a positive effect on the productivity of the fleet management.
• Increase in efficiency by monitoring the telematics data and deriving strategies and measures

Frequent objections:

• Klaus has a smartphone and also spends a lot of time on the computer, but new programs are a big challenge for him
• Klaus has always managed things the way he does and that went well
• For Klaus, visualizations are "schnickschnack" and superfluous
• Klaus doubts that visualizations of his key figures can add value, or even replace his own system
• Klaus is afraid that additional tools mean additional effort

5. Features that Users Need

The collected results from the research were gathered and categorized using models from Decision Science and information technology acceptance (Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology). Due to the limited extent of our university project, the first 3 categories were focused:

1. Usefulness & Ease of use

• decrease fuel consumption (efficient routes, reduce unnecessary braking, effective driving, avoid hard braking, avoid steep acceleration, avoid exceeding speed limit, avoid, carbon emissions)
• reduce truck down time (reduce idle time, optimize maintenance = repair frequency, vehicle life span, efficient breaks, reduce unnecessary braking, truck checks after hard braking, comply with break times, maintenance planning and history, material efficient driving style (Download Paper))
• choose most efficient routes (traffic jam prediction, reduce delivery time, reduce fuel consumption)
• optimize maintenance (tires, fuel and oil, and brakes)
• keeping drivers safe (reduce accidents, alerts for possible issues concerning tires, breaks, ...)
• reducing labor costs (reduce idle time, optimize routes)
• lower greenhouse emissions (monitoring speed, acceleration, breaking, and idle time)
• enhanced customer service (product tracking, delivery alerts)
• monitor fleet performance (revenue / profit / cost / labor hours / trips performance / co2 emissions / idle time costs / driving distance, truck routes, average consumption, average speed, distance covered, date)
  • show vehicle status (on the way / available / out for maintenance)
  • costs (maintenance / fuel / breakdown / insurance)
  • oldest vehicles
  • type of vehicles (trucks / cars -> filter drill down)
  • Event notifications (success / errors /warnings / side route / being late / driving / parked)
• show vehicle data (type / year / licence / plate)
• show position (current, goal, checkpoints)
• trips overview ( vehicle / driver / delivery time / products shipped / scheduled)
• PDF export function (daily view)

2. Sustainability

• economical driving (l/100 km, braking and accelerating forces as indicators for inefficient driving style)
• Adopt an anticipatory driving style avoiding unnecessary accelerations and braking. These situations are the ones, into a driving cycle, consuming more fuel (note that in this paper the expression “driving cycle” always refers to a wider concept than usual, containing all possible factors influencing vehicle emissions16). Driving style influence on car CO2 emissions
• Use the engine as efficiently as possible. As the engine efficiency increases with the engine load and the internal friction loss decreases with decreasing the engine speed, the combina-tion of high loads and low engine speeds allows to spend less fuel for the same power sup-plied by the engine. Driving style influence on car CO2 emissions

3. Customization

• fleet managers have different roles, which need different functionalities (purchasing agents, sales personnel, and supply chain managers)
• Dropdown with different views (for each role / strategical vs realtime)
• Modular personalization (views are adaptable by giving the option to delete, search, or add visualizations)

Other unconsidered factors:

4. Security: theft alert (If a vehicle involuntarily leaves a marked geo-zone, e.g. in the case of a night-time theft, you will be informed directly); Check points reached (if you dont reach it for a long time, an alarm will be given)
5. Hedonic motivation (fun to do)
6. Self-actualization (have a deeper sense of purpose)
7. Learnability (easy to learn, tooltips)
8. Autonomy
9. Facilitating Conditions