Abstract

A key challenge facing cities of today is the persistent and growing urban congestion that has significant adverse effects on economic productivity, emissions, driver frustration, and quality of life. The concept of smart cities, which can revolutionize the management of metropolitan transportation operations and infrastructure, shows great promise in mitigating this problem. Specifically, the automation and connectedness (A&C) of smart city entities such as its infrastructure, services, and vehicles, can be helpful. In this regard, this paper focuses on the potential of autonomous vehicles (AVs) and AV infrastructure, particularly during prospective transition era where there will be mixed streams of AVs and human driven vehicles (HDVs). The paper considers two aspects of this potential: connectivity-enabled travel demand management and travel infrastructure supply through lane management. To demonstrate the opportunity associated with this potential, this paper first presents an AV-enabled tradable credit scheme (TCS) to manage travel demand. Here, the transportation authority distributes travel credits to travelers directly and instantaneously using the AV’s A&C features. Then, travelers use their A&C features to pay these credits for travel at specific locations or times-of-day according to their choices of lane types and links. With regard to supply, the paper considers that the road network consists of two lane types: AV-dedicated, and mixed traffic lanes, and develops a scheme for Travel Demand and Lane Management Strategies in AV transition era (TLMAV). First, the paper models the expected travel choices based on the user equilibrium concepts, at different levels of AV market penetration. Then, the existence of the optimal solution in terms of link flows and the prevailing travel credit price is demonstrated. Then, the paper establishes the optimal TLMAV that minimize total travel time subject to user equity constraints. The results demonstrate the extent to which HDV users suffer increase in travel cost if equity is not considered in the model. The results also show how the transportation agency can use TLMAV to keep HDV travel costs to acceptable levels, particularly during early periods of the AV transition period.

Highlights

  • Urban Congestion and the Promise of Smart Cities ConceptsThe smart cities concept has received increasing interest during the last decade

  • This decision is subject to constraints that include: (i) a Pareto optimal stipulation, which ensures that everyone ends up better off, and (ii) equity constraints, which ensure that human driven vehicles (HDVs) travelers are reimbursed for their higher travel times due to lane allocation to autonomous vehicles (AVs), during the early periods of the transition era

  • AV dedicated lanes on the road network can help reduce traffic congestion as AVs require a relatively smaller headway compared to HDVs

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Summary

Introduction

Urban Congestion and the Promise of Smart Cities ConceptsThe smart cities concept has received increasing interest during the last decade. The need for smart cities is accentuated by ever-increasing population growth and urbanization. The transportation, water and waste water, and energy infrastructure systems were designed decades ago to serve far smaller demand, and increasing populations have caused excess demand, and subsequently, poor levels of service (Word Bank, 2018). This is unfolding at a time when urban areas are already grappling with providing the infrastructure needed to support their populations (Birkmann et al, 2016) due to funding inadequacy or lack of skilled managers. According to Grimm et al (2008) and Alberti (2017), the confluence of structural, functional, and social evolutions have resulted in daunting challenges to city authorities as they struggle to provide critical infrastructure services for their residents

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