The deployment of automated vehicles in urban transport systems: a methodology to design dedicated zones

Conceição, Lígia; Correia, Gonçalo Homem de Almeida; Tavares, José Pedro

doi:10.1016/j.trpro.2017.12.025

Cited by 16 publications

(5 citation statements)

References 7 publications

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“…Excluding the long-range trips is likely to somewhat magnify the impact of power consumption in the AD system on the overall vehicle efficiency, as the AD is constantly drawing power irrespective of the speed (thus, the efficiency loss will be less at higher average trip speed). However, there are reasonable predictions (31,32) that earlier deployments of L4/L5 AD would be in urban areas, where most of the trips would not be long range.…”

Section: Methodsmentioning

confidence: 99%

Modeling the Effect of Power Consumption in Automated Driving Systems on Vehicle Energy Efficiency for Real-World Driving in California

Hamza¹,

Willard²,

Chu³

et al. 2019

Transportation Research Record: Journal of the Transportation R

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Vehicle automation has drawn much attention in recent years, as it is perceived to usher in new levels of safety, convenience, and energy efficiency in transportation. Much uncertainty and speculation still exist regarding how automated driving (AD) would affect the overall transportation energy, as a result of some factors that are difficult to predict, such as changes in driving patterns and induced travel demand. There is also much speculation about the optimum vehicle powertrain for which AD systems are to be mounted. This study focuses on a less discussed, less speculative issue that pertains to both transportation energy efficiency and powertrain suitability. The impact of the power consumption in an AD system (for sensors, data processing, and vehicle controls) is analyzed for various powertrains via a publicly open-source simulation code, for more than 59,000 real-world vehicle trips obtained from the California Household Travel Survey. Study of scenarios of power consumption in the AD system that range from present-day values (about 3 kW) to future targets (0.5 kW) reveal interesting trends in vehicle energy efficiency. At 0.5 kW power consumption, the AD system can be of minimal impact to vehicle efficiency; however, at present-day levels of AD power consumption, the electric driving range (for electric vehicles and plug-in hybrids) could be shortened by 27–47% and fuel consumption could increase by up to 37% compared with the same vehicle model with no AD system.

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Section: Methodsmentioning

confidence: 99%

Modeling the Effect of Power Consumption in Automated Driving Systems on Vehicle Energy Efficiency for Real-World Driving in California

Hamza¹,

Willard²,

Chu³

et al. 2019

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

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“…The mothership concept firstly appeared in military and environmental monitoring [16], that is later applied to delivering goods. Recently, there are mainly two applications to delivering goods on the mothership concept, one is van-based drone delivery (VBDD), which has been widely studied [17], another is van-based driverless vehicle delivery (VBDVD), which is recently concerned [18,19].…”

Section: The Mothership Conceptmentioning

confidence: 99%

Multi-depot Routing Problem with Van-based Driverless Vehicles

Xiaolong,

Xiayu

2024

Preprint

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In order to strengthen the coordination between different delivery participants and between different means of transport, this work proposes one extension of multi-depot routing problems where vans and driverless vehicles are used in combination during the delivery. The operation process mainly includes two parts. One is that, vans carry several driverless vehicles and goods, and drop off or pick up driverless vehicles at stops. Another is that, driverless vehicles departing directly from depots or dropped off by vans deliver goods for customers. During the delivery process, vans and driverless vehicles are in close cooperation through the proposed multi-depot joint distribution and the proposed van-van joint distribution. By the two modes, vans can depart from one depot and return to another depot, driverless vehicles can be dropped off by one van at one stop and be picked up by another van at another stop. This multi-depot routing problem with van-based driverless vehicles is formulated as a mixed integer programming model which can be solved by the designed heuristic algorithm. The sensitivity analyses about the capacity of vans for driverless vehicle and the maximum traveling time of driverless vehicles are also performed. The results reveal that they have limited effects on the delivery cost and the application of the two modes. Moreover, the experimental results demonstrate that the application of two modes is affected by the distribution of depots and stops.

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“…Pedestrian studies started after the invention of the first AV [15]. In the beginning, studies focused were on AV safety perception, choices, and attitude towards AV adoption [11], but now after successful testing and deployment of AVs in urban public transportation, researchers are focusing on pedestrian AVs interaction [16]. Currently, AVs have dedicated movement zones and specific routes because pedestrian behavior is not yet fully explored.…”

Section: Related Workmentioning

confidence: 99%

Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction

et al. 2022

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Automobile manufacturers, alongside technology providers, researchers, and public agencies, are conducting extensive testing to design autonomous vehicles (AVs) algorithms that will provide a complete understanding of road users, specifically pedestrians. Pedestrian behavior and actions determination are highly unpredictable depending on behavioral beliefs, context, and socio-demographic variables. Context includes everything that potentially affects one’s behavior; in AVs–pedestrian interaction, context may consist of weather conditions, road structure, social factors norms, and traffic volume. These influencing elements, therefore, need to be focused on during the development of pedestrian interaction algorithms. For this purpose, the pedestrian behavior questionnaire for FAVs (PBQF) is designed based on the theory of planned behavior (TPB). A total of almost 1000 voluntary participants completed this multilingual survey. As socio-demographic values and physiological perception varies with local norms, regions, and ethnicity, participants from 27 countries were therefore chosen to account for this variation. One of the key findings of this study is the influence of pedestrian attributes and the context on pedestrian behavior. Pedestrian action cannot be understood without visual observation of the pedestrian themselves and their context. The findings showed that pedestrians build communication with vehicles based on their driving styles. The vehicle’s driving style leads pedestrians to think that the vehicle is human-driven or autonomous. The results also revealed that pedestrians use several cues to show their intention. The general perception of AVs was also analyzed, and the communication between AVs and pedestrians with different displaying options was investigated.

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The deployment of automated vehicles in urban transport systems: a methodology to design dedicated zones

Cited by 16 publications

References 7 publications

Modeling the Effect of Power Consumption in Automated Driving Systems on Vehicle Energy Efficiency for Real-World Driving in California

Modeling the Effect of Power Consumption in Automated Driving Systems on Vehicle Energy Efficiency for Real-World Driving in California

Multi-depot Routing Problem with Van-based Driverless Vehicles

Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction

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