Preface

The transportation system plays a significant role in making cities sustainable, inclusive, and safe.

Innovative and smart mobility systems are expected to change the way transportation systems work and move traditional mobility paradigms towards a more self-conscious and sustainable behavior. In this context, a great research effort is necessary to cover those issues related to transportation planning, management and design.

Indeed, it is fundamental to understand and model much more complex travel paradigms, to identify robust and effective strategies for traffic control, and to design transit services or personal mobility services. Furthermore, it is crucial to identify real opportunities that the current technological revolution may present for making transportation systems smarter, safer, and more sustainable.

This book proposes a methodological and technological approach to the aforementioned issues. It proposes a comprehensive framework that may support researchers, analysts/practitioners, decision-makers, industries, and investors.

The first section of the book examines travel and driving behavior, investigating the necessity of more realistic and flexible paradigms for mode choice and modeling complex travel patterns. It also focuses on two very timely issues: attitudes and behavior of old travelers towards new technologies and the role of cognitive profile of offender drivers.

The second section addresses the crucial challenges regarding the management and optimization of the multiple components of a transportation system. It investigates route guidance in connected/autonomous environments, management of electric and cooperative buses, traffic control in hybrid traffic flow conditions, and optimization of transit or shared services.

The third section is an overview of three of the most promising technological advances of transportation systems: advanced vehicles, driving technologies, and the Building Information Modeling revolution.

The book includes the following twelve chapters.

**II**

**Chapter 7 145**

**Chapter 8 163**

**Chapter 9 183**

Technological and Digital Advances **199**

**Chapter 10 201**

**Chapter 11 215**

**Chapter 12 237** BIM Approach for Smart Infrastructure Design and Maintenance Operations

Advanced Vehicles: Challenges for Transportation Systems Engineering

*by Salvatore Antonio Biancardo, Nunzio Viscione, Cristina Oreto* 

Centralised Traffic Control and Green Light Optimal Speed Advisory Procedure in Mixed Traffic Flow: An Integrated Modelling Framework *by Roberta Di Pace, Chiara Fiori, Luigi Pariota and Facundo Storani*

Towards Shared Mobility Services in Ring Shape

*by Orlando Giannattasio and Giulio E. Cantarella*

Transit Signal Priority in Smart Cities *by Bahman Moghimi and Camille Kamga*

Driver Assistance Technologies *by Pradip Kumar Sarkar*

*and Francesca Russo*

*by Fabien Leurent*

**Section 3**

Chapter 1 is a brief introduction to the Mobility as a Service (MaaS) paradigm and the main modeling issues that researchers should address in the near future. Then, it provides an extensive review of the state of the art of mode choice approaches and introduces a bi-level mode choice behavior paradigm that explicitly accounts for real-time events and travelers' adaptive behavior.

Chapter 2 describes the state of art and practice of activity-based modeling approaches, including the ongoing research covering both demand and supply considerations. It proposes possible solutions to improve the modeling approach, as well as existing opportunities for effective spatial transferability to new geographical contexts along with expanding the applicability of ABMs in transportation policy-making.

Chapter 3 considers the needs of older travelers and how new technology can meet some of those needs and what is necessary for it to be appropriate to and usable by older travelers. It covers what happens as travelers get older and how changes in transport systems can be made much more useful and usable for older people. In addition, the chapter considers MaaS in the United Kingdom, especially for older and infirm people.

Chapter 4 investigates the cognitive profile of optimistic offender drivers and proposes possible interventions for sustainable and safer driving behavior. In particular, it highlights the lack of understanding of the true impact that external factors can have on driving and how offender drivers overestimate their abilities in avoiding accidents.

Chapter 5 investigates an integrated management approach exploiting the potentials of the new Cooperative Intelligent Transportation Systems (C-ITS) to meet the requirements of the next generation of Public Transport (PT) for electrified and cooperative bus systems, thus taking into account the additional complexity of periodically recharging electric buses during operation using the dedicated infrastructure. Specifically, the proposed system is tested and evaluated in simulation showing the benefits of electrified and cooperative bus systems.

Chapter 6 explores the integration of two traffic management strategies: ramp metering (RM) and route guidance (RG). It focuses on the interaction between automated vehicles (AVs) and human-driven vehicles (HDVs). Indeed, it seems unrealistic that all HDVs will suddenly be replaced by AVs in the near future. Rather, AVs will be introduced in the presence of HDVs. Therefore, there is a need to consider cases where it becomes necessary to model the interactions between AVs and HDVs. The key areas of interest involve traffic routing and management, optimal highway merging, and intelligent overtaking behaviors.

Chapter 7 investigates the integration of traffic management strategies in the era of Cooperative and Connected Intelligent Transportation Systems. The focus is on strategies to optimize vehicle behavior at junctions. In accordance with the literature, one of the proposed approaches is that of the Green Light Optimal Speed Advisory (GLOSA), which provides a warning to the driver regarding the best speed to maintain when approaching the junction by avoiding stops at junctions. The chapter proposes a whole modeling framework based on the integration of GLOSA and traffic control strategy. The framework is also applied considering a real case study.

Chapter 8 focuses on the "systemic qualities" of shared mobility services adopting a ring format, as well as explores the conditions required to establish a ring system in urban settlements. It evaluates whether a ring system makes it possible to cover a relatively large geographical area while also establishing service cycles for shared vehicles. The modal models share a four-tier architecture that involves: (1) the physical operations of the service and the laws governing its vehicle flow, (2) the balance between supply and demand, (3) the optimized service management, and (4) the strategic positioning of the service in terms of technologies. The chapter applies the model to analyze some scenarios.

**V**

Chapter 9 provides a comprehensive review of transit signal priority models. Generally, giving priority to public transport vehicles at traffic signals is one of the traffic management strategies deployed at emerging smart cities to increase the quality of service for public transit users. This is key to breaking the vicious cycle of congestion that threatens to bring cities into gridlock. The chapter presents studies in the following categories: signal priority and different control systems, passive versus active priority, predictive transit signal priority, the priority with connected vehicles, multi-modal signal priority models, and other practical considerations.

Chapter 10 addresses the challenges that AVs introduce for transportation systems engineering. It discusses the most likely positive and negative effects of mixed flow expected in the near future, the main classifying criteria such as ownership, on-board technologies (sensors), and the most effective tools already available for macroscopic analysis of multi-vehicle-type transportation systems to highlight the

Chapter 11 describes Driver Assistance Technology, which is emerging as a new driving technology popularly known as Advanced Driver Assistance Systems (ADAS). The chapter provides a complete overview on this topic explaining the functioning of Driver Assistance Technology with the help of its architecture and

Chapter 12 provides an overview of a creative process for the digitalization of existing roads. It depicts the approach, known as the reverse engineering method, by (1) modeling the 3D digital terrain model; (2) creating the horizontal alignment, vertical profiles, and editing cross-sections; and (3) modeling the 3D corridor. As a response to long-term development between Big Data, Building Information Modeling (BIM), and road engineering, this chapter offers innovative and practical solutions for integrating road design and pavement analysis for better management

**Stefano de Luca, Roberta Di Pace and Chiara Fiori**

Department of Civil Engineering,

University of Salerno,

Italy

need to update and/or develop new mathematical models.

and optimization of road pavement maintenance.

various types of sensors.

Chapter 9 provides a comprehensive review of transit signal priority models. Generally, giving priority to public transport vehicles at traffic signals is one of the traffic management strategies deployed at emerging smart cities to increase the quality of service for public transit users. This is key to breaking the vicious cycle of congestion that threatens to bring cities into gridlock. The chapter presents studies in the following categories: signal priority and different control systems, passive versus active priority, predictive transit signal priority, the priority with connected vehicles, multi-modal signal priority models, and other practical considerations.

Chapter 10 addresses the challenges that AVs introduce for transportation systems engineering. It discusses the most likely positive and negative effects of mixed flow expected in the near future, the main classifying criteria such as ownership, on-board technologies (sensors), and the most effective tools already available for macroscopic analysis of multi-vehicle-type transportation systems to highlight the need to update and/or develop new mathematical models.

Chapter 11 describes Driver Assistance Technology, which is emerging as a new driving technology popularly known as Advanced Driver Assistance Systems (ADAS). The chapter provides a complete overview on this topic explaining the functioning of Driver Assistance Technology with the help of its architecture and various types of sensors.

Chapter 12 provides an overview of a creative process for the digitalization of existing roads. It depicts the approach, known as the reverse engineering method, by (1) modeling the 3D digital terrain model; (2) creating the horizontal alignment, vertical profiles, and editing cross-sections; and (3) modeling the 3D corridor. As a response to long-term development between Big Data, Building Information Modeling (BIM), and road engineering, this chapter offers innovative and practical solutions for integrating road design and pavement analysis for better management and optimization of road pavement maintenance.

> **Stefano de Luca, Roberta Di Pace and Chiara Fiori** Department of Civil Engineering, University of Salerno,

Italy

**IV**

study.

as well as existing opportunities for effective spatial transferability to new geographical contexts along with expanding the applicability of ABMs in

Chapter 3 considers the needs of older travelers and how new technology can meet some of those needs and what is necessary for it to be appropriate to and usable by older travelers. It covers what happens as travelers get older and how changes in transport systems can be made much more useful and usable for older people. In addition, the chapter considers MaaS in the United Kingdom, especially for older

Chapter 4 investigates the cognitive profile of optimistic offender drivers and proposes possible interventions for sustainable and safer driving behavior. In particular, it highlights the lack of understanding of the true impact that external factors can have on driving and how offender drivers overestimate their abilities in

Chapter 5 investigates an integrated management approach exploiting the potentials of the new Cooperative Intelligent Transportation Systems (C-ITS) to meet the requirements of the next generation of Public Transport (PT) for electrified and cooperative bus systems, thus taking into account the additional complexity of periodically recharging electric buses during operation using the dedicated infrastructure. Specifically, the proposed system is tested and evaluated in simulation showing the benefits of electrified and cooperative bus systems.

Chapter 6 explores the integration of two traffic management strategies: ramp metering (RM) and route guidance (RG). It focuses on the interaction between automated vehicles (AVs) and human-driven vehicles (HDVs). Indeed, it seems unrealistic that all HDVs will suddenly be replaced by AVs in the near future. Rather, AVs will be introduced in the presence of HDVs. Therefore, there is a need to consider cases where it becomes necessary to model the interactions between AVs and HDVs. The key areas of interest involve traffic routing and management,

Chapter 7 investigates the integration of traffic management strategies in the era of Cooperative and Connected Intelligent Transportation Systems. The focus is on strategies to optimize vehicle behavior at junctions. In accordance with the literature, one of the proposed approaches is that of the Green Light Optimal Speed Advisory (GLOSA), which provides a warning to the driver regarding the best speed to maintain when approaching the junction by avoiding stops at junctions. The chapter proposes a whole modeling framework based on the integration of GLOSA and traffic control strategy. The framework is also applied considering a real case

Chapter 8 focuses on the "systemic qualities" of shared mobility services adopting a ring format, as well as explores the conditions required to establish a ring system in urban settlements. It evaluates whether a ring system makes it possible to cover a relatively large geographical area while also establishing service cycles for shared vehicles. The modal models share a four-tier architecture that involves: (1) the physical operations of the service and the laws governing its vehicle flow, (2) the balance between supply and demand, (3) the optimized service management, and (4) the strategic positioning of the service in terms of technologies. The chapter

optimal highway merging, and intelligent overtaking behaviors.

applies the model to analyze some scenarios.

transportation policy-making.

and infirm people.

avoiding accidents.

**1**

Section 1

Travel and Driving Behavior

Section 1
