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Intelligent Transportation System: Route Guidance, Driving Behavior, and Eco-driving

Title
Intelligent Transportation System: Route Guidance, Driving Behavior, and Eco-driving
Translated Title
지능형 교통 시스템: 길 찾기, 운전 행태, 친환경적 교통 시스템
Authors
Son, Jeong Il
DGIST Authors
Son, Jeong Il; Son, Sang Hyuk; Park, Tae Joon; Son, Joon Woo
Advisor(s)
Son, Sang Hyuk; Park, Tae Joon
Co-Advisor(s)
Son, Joon Woo
Issue Date
2014
Available Date
2016-05-18
Degree Date
2014. 2
Type
Thesis
Keywords
route guidancedriving behavioreco driving
Abstract
There have been numerous modern technological advances that have changed life for many people. Transportation fields are evolving, too. This thesis suggests intelligent transportation systems (focused on general vehicles) using smart sensors, high-powered computers, and advanced communication technologies. This thesis divided into three parts. The first part is the study on route guidance systems. Existing general route guidance systems focused on shorter travel time and distance. However, it is not the most important element in deciding a route. Thus, this study aimed to quantify the quality of alternative routes by explicitly considering route travel time variability. The second part is the study on driving behaviors. This study aimed to propose a new index to capture drivers’ aggressiveness by analyzing inter-vehicular dynamics data and to demonstrate how the proposed index would work using real world driving behavior data obtained from four distinctive groups. The final part is the study on eco-driving. The proposed system in this study can offer a recommended speed to drivers and volume of traffic to traffic light control system. This can make an improved traffic environment. This system can reduce fuel consumption and CO2 emissions. ⓒ 2014 DGIST
Table Of Contents
Chapter1. Introduction 1 -- Chapter2. Quantifying Route Quality through Viability Indices using Actual Travel Time Data 5 -- 2.1 Introduction 5 -- 2.2 Travel Time Data in Daegu City 6 -- 2.3 Methodology 9 -- 2.4 Implementation and Results 11 -- 2.4.1 OP Pair 1 11 -- 2.4.1.1 Dominancy Index 11 -- 2.4.1.2 Beat the Average Index 12 -- 2.4.2 OP Pair 2 14 -- 2.4.2.1 Dominancy Index 15 -- 2.4.2.2 Beat the Average Index 15 -- 2.4.3 OP Pair 3 16 – 19 -- 2.4.3.1 Dominancy Index 17 -- 2.4.3.2 Beat the Average Index 17 -- 2.5 Summary 19 -- Chapter3. Capturing Drivers’ Aggressiveness from Inter-Vehicular Dynamics Data 20 -- 3.1 Introduction 20 -- 3.2 Data 21 -- 3.2.1 Subject 21 -- 3.2.2 Instrumented Vehicle 22 -- 3.2.3 Data Collection Procedure 22 -- 3.2.4 Driving Behavior Data 22 -- 3.2.5 Questionnaire Data 23 -- 3.3 Procedure for Quantifying Aggressiveness 23 -- 3.3.1 Proposed Aggressiveness Index 24 -- 3.3.1.1 Time to Collision Measure 24 -- 3.3.1.2 Deceleration Rate Difference Measure 24 -- 3.3.1.3 Proposed Aggressiveness Index 25 -- 3.3.2 Drivers’ Aggressiveness from Driving Behavior Questionnaire 26 -- 3.3.2.1 Radar Chart based Aggressiveness Analysis 26 -- 3.3.2.2 Quantifying Aggressiveness based on Intentional and Unintentional Violations 26 -- 3.4 Results and Discussion 27 -- 3.4.1 Proposed Driver’s Aggressiveness Index 27 -- 3.4.2 Aggressiveness Obtained from Radar Charts 29 -- 3.4.3 Aggressiveness using Intentional and Unintentional Violations, and Safe Driving Speed 30 -- 3.5 Summary 31 -- Chapter4. Vehicles’ Speed and Traffic Light Control to Reduce Fuel Consumption and CO2 Emissions 33 -- 4.1 Introduction 33 -- 4.2 Background 36 -- 4.2.1 Elements increasing Fuel Consumption and Emissions of Vehicles -- 4.2.2 Car-Following Model 36 -- 4.2.3 VISSIM 37 -- 4.2.4 VT-Micro Model 37 -- 4.2.5 Related Works 37 -- 4.3 Methodology 38 -- 4.3.1 Speed Control 39 -- 4.3.1.1 Current Traffic Light is Green 41 -- 4.3.1.2 Current Traffic Light is Red 43 -- 4.3.2 Traffic Light Cycle Control 44 -- 4.4 Simulation 45 -- 4.4.1 Simulation Environment 46 -- 4.4.2 Simulation Result 47 -- 4.4.2.1 Average Travel Time 47 -- 4.4.2.2 Non-stop Pass Rate 48 -- 4.4.2.3 Fuel Consumption and CO2 Emissions 49 -- 4.5 Summary 52 -- Chapter5. Conclusions 53 -- REFERENCES 55 -- 요약문 58 -- Acknowledgement 59
URI
http://dgist.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002262546
http://hdl.handle.net/20.500.11750/1354
DOI
10.22677/thesis.2262546
Degree
Master
Department
Information and Communication Engineering
University
DGIST
Files:
Collection:
Information and Communication EngineeringThesesMaster


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