The integration of Industry 4.0 and automated vehicles into the smart cities concept is a topical issue in the urbanization of cities and technological innovation within cities. As it is a relatively modern issue, many aspects of this field have not yet been explored; as a consequence, this paper is concerned with the search for synergies between Industry 4.0 and automated vehicles in smart city infrastructures. There is a lack of contributions in this field that summarize these synergies in a single article and address a wide range of aspects, including transport, energy, communication, and citizen participation. As the field lacks a complete and clear summary of what is already known, which would help multiple stakeholders, the authors decided to conduct this review. The article elucidates the above-stated aspects through a clear and in-depth literature review, which is complemented by specific examples from practice. Of course, the article also includes a description of the synergy potential and the impact on the inhabitants, the environment, and, last but not least, on the overall city life. The main hypothesis of this article is that the integration of Industry 4.0 technologies and automated vehicles within smart city infrastructure will result in significant improvements in transportation efficiency, resource utilization, and overall urban sustainability. The article discusses the positives and negatives of such integration, highlighting, on the one hand, the benefits in terms of reducing environmental impact and improving citizens’ quality of life, but on the other hand, also highlighting the various ethical, legal, and social issues that such integrations may bring. Several methods have been used within the article, namely analysis, synthesis, comparison, and historical interpretation. The final discussion highlights the benefits, as well as the challenges, that such integration faces and must deal with if it is to be successful. It can be concluded that the synergistic potential of automated vehicles and Industry 4.0 in smart city infrastructure is enormous and that such integration offers promising solutions for enhancing transportation efficiency, energy management, and overall urban sustainability. It is also highlighted in the article that, in order to reap the benefits of such synergies, a wide-ranging collaboration of policymakers, industry stakeholders, and urban planners is needed.

Synergies and Potential of Industry 4.0 and Automated Vehicles in Smart City Infrastructure

Since the quantitative methodology analysis of the high-density pedestrian shockwaves at a bottleneck is limited, this paper proposes a dynamic time warping (DTW) algorithm for identifying, analyzing, and verifying the shockwaves. A set of real-world trajectory data is used to illustrate the proposed algorithm. Results show that the DTW algorithm is capable of depicting the pedestrian shockwaves elaborately and accurately. Results also show that the shockwave velocity is unsteady, as throughout time the gathering wave velocity and the evanescent wave velocity are decreasing and increasing, respectively. The mutual influence between followers and leaders is decreased when the shockwave spreads. There is a linear relationship between the shockwave velocity and density. Furthermore, singularities present a potential match solution to help identify the changing of pedestrian behaviors. The DTW algorithm for evaluating the pedestrian system stability has significant intrinsic features in the pedestrian traffic control and management.

/pdf/a-dynamic-time-warping-algorithm-based-analysis-of-4zfi3m5ohs.pdf

A Dynamic Time Warping Algorithm Based Analysis of Pedestrian Shockwaves at Bottleneck

The deployment of automated vehicles (AVs) has the potential to disrupt and fundamentally transform urban transportation. As their implementation becomes imminent on cities’ streets, it is of great concern that no comprehensive strategies have been formulated to effectively manage and mitigate their potential negative impacts, particularly with respect to the components of the do no significant harm (DNSH) framework recently introduced in the EU taxonomy. The methodology employed comprises three steps: (i) An extensive literature review on the impact of AVs on the DNSH components; (ii) exploration of designing a coherent pro-active vision by integrating measures identified in the literature as key elements to mitigate the harm; and (iii) an interdisciplinary focus group (FG) to verify whether the impacts of AVs and potential mitigation measures for Bucharest are similar to those identified by the literature and integrated into the pro-active vision. The results suggest that while there are commonalities, variations exist in focus and perspective, underscoring the necessity of examining the mitigation measures encompassed in the vision through additional focus groups conducted in different cities.

Unveiling the Hidden Effects of Automated Vehicles on “Do No Significant Harm’’ Components

We examined how trip-level characteristics may influence autonomous vehicle ownership decisions. Using 639 stated preference survey responses in the US, we developed an integrated choice and latent variable model linking trip- and consumer-level characteristics to AV ownership choices. Results suggested parking cost, travel cost and travel time are important predictors for vehicle ownership at the trip-level; and monthly payment, car ownership importance and autonomous vehicle safety perceptions are significant predictors at the consumer-level. By examining elasticities of vehicle ownership market shares, we found while consumer-level characteristics have the most prominent effect on vehicle ownership decisions, trip-level characteristics have a small but measurable effect. Among trip-level characteristics, parking cost has the largest impact on vehicle ownership decisions, followed by travel cost of ridehailing (both conventional and autonomous), and transit travel time. Finally, we simulated future vehicle ownership decisions under three policy scenarios by leveraging trip- and consumer-level characteristics. 

Effects of trip-level characteristics on autonomous vehicle ownership: A U.S. analysis

Recently, in the literature, microscopic simulation is one of the most attractive methods in impact assessment of automated vehicles (AVs) on traffic flow. AVs can be divided into different categories, each having different driving characteristics. Hence, calibrating microscopic simulators for different AV categories could be challenging in AVs’ impact assessment. The PTV Vissim microscopic traffic simulation software has been calibrated for simulating diverse types of AVs in a large body of literature. There are two main streams of studies in literature adapting AVs' driving behaviors in Vissim following either internal (i.e., adjusting the parameters of the Vissim's default driving behavior models) or external (i.e., adapting AVs' behavior through external VISSIM interfaces) modeling approaches. The current paper investigates how the PTV Vissim has been internally calibrated for the simulation of different types of AVs and compares the calibrated values in the literature with default values introduced in the recent version of PTV Vissim. In the present paper, the reviewed studies are partitioned into two main categories according to the characteristics of the studied AVs, the studies focused on autonomous automated vehicles (AAVs) and the ones focused on cooperative automated vehicles (CAVs). Our findings indicate that the literature expects a lower value for parameters including standstill distance (CC0), headway time (CC1), following variation (CC2), the threshold for entering “following” (CC3), negative/positive following thresholds (CC4/CC5), speed dependency of oscillation (CC6), oscillation acceleration (CC7), safety distance reduction factor (SDRF), and minimum headway front/rear (MinHW) for AVs than conventional vehicles (CVs). Besides, the literature expects higher values for parameters including standstill acceleration (CC8), acceleration at 80 km/h (CC9), looking distances, and maximum deceleration for cooperative braking (MaxDCB) for AVs. When cautious AVs are introduced, deterring effects are expected in the literature (e.g., higher CC0). Moreover, CAVs can have higher looking distance values compared with AAVs.

/pdf/how-ptv-vissim-has-been-calibrated-for-the-simulation-of-2532eb48.pdf

How PTV Vissim Has Been Calibrated for the Simulation of Automated Vehicles in Literature?

Automated vehicles (AVs) are believed to have great potential to improve the traffic capacity and efficiency of the current transport systems. Despite positive findings of the impact of AVs on traffic flow and potential road capacity increase for highways, few studies have been performed regarding the impact of AVs on urban roads. Moreover, studies considering traffic volume increase with a mixture of AVs and human-driven vehicles (HDVs) have rarely been conducted. Therefore, this study investigated the impact of gradual increments of AV penetration and traffic volume on urban roads. The study adopted a microsimulation approach using VISSIM with a Wiedmann 74 model for car-following behavior. Parameters for AVs were set at the SAE level 4 of automation. A real road network was chosen for the simulation having 13 intersections in a total distance of 4.5 km. The road network had various numbers of lanes from a single lane to five lanes in one direction. The network consists of a main arterial road and a parallel road serving nearby commercial and residential blocks. In total, 36 scenarios were investigated by a combination of AV penetrations and an increase in traffic volumes. The study found that, as AV penetration increased, traffic flow also improved, with a reduction of the average delay time of up to 31%. Also, as expected, links with three or four lanes had a more significant impact on the delay. In terms of road capacity increase, when the penetration of AVs was saturated at 100%, the road network could accommodate 40% more traffic.

/pdf/the-impact-of-automated-vehicles-on-traffic-flow-and-road-hfh2c7fdzg.pdf

The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks

Theoratical verification of VSL based on traffic flow model and shock wave theory

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The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks

Theoratical verification of VSL based on traffic flow model and shock wave theory