Geospatial Analytics to Improve the Safety of Autonomous Vehicles

Geospatial Analytics to Improve the Safety of Autonomous Vehicles

Robert Hipps (Saint Peter's University, Jersey City, NJ, USA), Tushar Chopra (Saint Peter's University, USA), Peng Zhao (Saint Peter's University, USA), Edward Kwartler (Liberty Mutual Inc., Boston, MA, USA) and Sylvain Jaume (Saint Peter's University, USA)
Copyright: © 2017 |Pages: 12
DOI: 10.4018/IJKBO.2017070104

Abstract

Finding the costs and risks associated with highway traffic routes would allow companies and people alike to find routes that offer a comfortable amount of risk. With the amount of traffic data being collected at a more granular level the ability to find costs and risks associated with traffic routes given real time circumstances is plausible. Weighing these data and finding the areas that are most accident-prone allows for an assessment of the probability that an accident happens and what the cost of that accident would be for any given route. This information is very valuable for both safety and cost saving for drivers and insurance companies.
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Introduction

“Road accidents are one of the most important problems being faced by modern societies. Apart from the humanitarian aspect of reducing road deaths and injuries in developing countries, a strong case can be made for reducing road crash deaths on economic grounds alone, as they consume massive financial resources that the countries can ill afford to lose” (Partheeban et al., 2008). Urban traffic is notorious for routine stoppages, delays and other forms of congestion. The urbanization and globalization of the world economies brings highly significant economic and societal impacts. These include significant monetary losses to the economy.

There are two general reasons for economic and societal costs to an economy. One is the monetary cost of accidents (safety) and the other is economic cost (lost revenue). “Compared to the economical and societal cost of traffic congestion, the last of traffic safety has a very high cost. As an illustration, in 1997 the cost for society of traffic congestion in the Netherlands was 0.8 billion Euros; the costs due to accidents was much higher, namely 8 billion Euros” (Louwerse et al., 2004).

The costs in the United States are much greater. “In 2010, there were 32,999 people killed, 3.9 million were injured, and 24 million vehicles were damaged in motor vehicle crashes in the United States. The economic costs of these crashes totaled $242 billion. Included in these losses are lost productivity, medical costs, legal and court costs, emergency service costs (EMS), insurance administration costs, congestion costs, property damage, and workplace losses. The $242 billion cost of motor vehicle crashes represents the equivalent of nearly $784 for each of the 308.7 million people living in the United States, and 1.6 percent of the $14.96 trillion real U.S. Gross Domestic Product for 2010.” (Allahyar et al., 2006). These costs do not include estimates of the reductions in quality of life costs, when they are included, the total cost of societal harm increased to $836 billion in 2010.

Naturally, the greatest concern is for those who lose their lives in traffic accidents. Although traffic fatalities in the United States declined by nearly 25% during the period of 2003 to 2013, we lost 32,719 people in crashes on roadways during 2013. The number of people injured was 2.3 million (Gerdes et al., 2016).

Researchers in the Netherlands found that the greatest cost of vehicle accidents occurs on the rural and urban roads, not on the “motorways” (divided, limited access highways like a US Interstate). The secondary, underlying traffic network was found to be far less safe than the motorways. They found that more research should be focused on approaches to improve the traffic safety on urban and rural roads (Louwerse et al., 2004).

Much has been done to combat the economic and societal losses of vehicle accidents. During the past 25 years, a great amount of research and product development has gone toward the avoidance of accidents when they are about to occur. “Since the early nineties, there has been an increasing interest in the application of Advanced Driver Assistance (ADA) functions in cars and roads in order to make traffic safer and more efficient. ADA systems support or take over a drivers' task, e.g. to maintain a safe speed or distance, to maintain the right heading and to avoid collisions” (Van Arem et al., 2003). Such measures include, Adaptive Cruise Control, proximity sensors (to warn of another vehicle when backing up or changing lanes), automated lighting and automated braking. The market for these systems seems to be strong because many cars now arrive with some of these items as standard equipment.

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