Pricing Innovation: State of the Art and Automotive Applications

The paper aims at elaborating on pricing and business models for forthcoming innovative ITS devices, limiting its scope in particular to in-vehicle driving assistance systems and suggesting the various possible innovation and pricing strategies with theoretical discussions. The methodology is based on a comprehensive literature review of the major contributions made by the fields of managerial economics and management sciences to the study of pricing strategies and practices and, in particular, the pricing of innovative goods or services, in order to identify the strengths and weaknesses of the various schools of thought. The paper also gathers and analyzes the available data on two innovative navigation and safety devices for cars, namely ABS (Anti-Lock Braking System) and navigation systems, in order to put forward an initial interpretation.It concludes that there is no formula or even a vague method for determining "acceptable" price levels or "trigger points". There are two options, i.e. disruptive innovation which is by essence very risky and incremental innovation with each major model renewal.Innovation; pricing; automobile; intelligent transportation system

Conceptual Model for an Intelligent Persuasive Driver Assistant

Traffic congestion is a serious issue for large cities.  This is especially critical for cities that has insufficient mass transit system like Bangkok.  Although transportation infrastructure projects and rail mass transit lines are being implemented, these efforts require major financial investment and take a long time to complete.  This work proposes to help reduce traffic problems through influencing a change in driver behavior.  In this initial stage, a model for an intelligent persuasive driver assistant is conceptualized as a voice-interactive smart assistant on a smartphone.  The system uses information about the driver, his physical state, vehicle performance information, and geolocation information to form persuasive strategies to influence driver behavior and to adapt user interfaces and interactions to reduce driver distraction.  Integrating these components together is expected to provide improved assistance in driving tasks and affect driving behavior changes. Keywords: intelligent driver assistant, navigation, smart assistant, persuasive technolog

Driver-passenger collaboration as a basis for human-machine interface design for vehicle navigation systems

Human Factors concerns exist with vehicle navigation systems, particularly relating to the effects of current Human-Machine Interfaces (HMIs) on driver disengagement from the environment. A road study was conducted aiming to provide initial input for the development of intelligent HMIs for in-vehicle systems, using the traditional collaborative navigation relationship between the driver and passenger to inform future design. Sixteen drivers navigated a predefined route in the city of Coventry, UK with the assistance of an existing vehicle navigation system (SatNav), whereas a further 16 followed the navigational prompts of a passenger who had been trained along the same route. Results found that there were no significant differences in the number of navigational errors made on route for the two different methods. However, drivers utilising a collaborative navigation approach had significantly better landmark and route knowledge than their SatNav counterparts. Analysis of individual collaborative transcripts revealed the large individual differences in descriptor use by passengers and reference to environmental landmarks, illustrating the potential for the replacement of distance descriptors in vehicle navigation systems. Results are discussed in the context of future HMIs modelled on a collaborative navigation relationship

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Work domain analysis and intelligent transport systems: Implications for vehicle design

This article presents a Work Domain Analysis (WDA) of the road transport system in Victoria, Australia. A series of driver information requirements and tasks that could potentially be supported through the use of Intelligent Transport Systems (ITS) are then extracted from the WDA. The potential use of ITS technologies to circumvent these information gaps and provide additional support to drivers is discussed. It is concluded that driver information requirements are currently not entirely satisfied by contemporary vehicle design and also that there are a number of driving tasks that could be further supported through the provision of supplementary systems within vehicles

Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving

Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving

Leveraging Personal Navigation Assistant Systems Using Automated Social Media Traffic Reporting

Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amount of vehicular traffic congestion and incidents. Existing incident detection techniques are limited to the use of sensors in the transportation network and hang on human-inputs. Despite of its data abundance, social media is not well-exploited in such context. In this paper, we develop an automated traffic alert system based on Natural Language Processing (NLP) that filters this flood of information and extract important traffic-related bullets. To this end, we employ the fine-tuning Bidirectional Encoder Representations from Transformers (BERT) language embedding model to filter the related traffic information from social media. Then, we apply a question-answering model to extract necessary information characterizing the report event such as its exact location, occurrence time, and nature of the events. We demonstrate the adopted NLP approaches outperform other existing approach and, after effectively training them, we focus on real-world situation and show how the developed approach can, in real-time, extract traffic-related information and automatically convert them into alerts for navigation assistance applications such as navigation apps.Comment: This paper is accepted for publication in IEEE Technology Engineering Management Society International Conference (TEMSCON'20), Metro Detroit, Michigan (USA