Mobility Traffic Model Based on Combination of Multiple Transportation Forms in the Smart City

Hariz, Mohammed Bin; Said, Dhaou; Mouftah, Hussein T.

doi:10.1109/iwcmc.2019.8766676

Cited by 4 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A carpooling recommendation system has been proposed in [51] in which a potential model based on a continuous-time Markov chain is proposed to model consumer consciousness and predict future consumer movements. Similarly, The Smart City Concept [67] has developed a mobility system for passengers with trip cost optimization, in which Mobility Traic Algorithm (MTA) has been proposed to handle passenger-speciic needs are primarily based on real-time statistics on buses and carpooling. A more real life scenario which huge number of users, complex…”

Section: Mobility In Carpoolingmentioning

confidence: 99%

Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

et al. 2022

View full text Add to dashboard Cite

Owing to the advancements in communication and computation technologies, the dream of commercialized connected and autonomous cars is becoming a reality. However, among other challenges such as environmental pollution, cost, maintenance, security, and privacy, the ownership of vehicles (especially for Autonomous Vehicles (AV)) is the major obstacle in the realization of this technology at the commercial level. Furthermore, the business model of pay-as-you-go type services further attracts the consumer because there is no need for upfront investment. In this vein, the idea of car-sharing ( aka carpooling) is getting ground due to, at least in part, its simplicity, cost-effectiveness, and affordable choice of transportation. Carpooling systems are still in their infancy and face challenges such as scheduling, matching passengers interests, business model, security, privacy, and communication. To date, a plethora of research work has already been done covering different aspects of carpooling services (ranging from applications to communication and technologies); however, there is still a lack of a holistic, comprehensive survey that can be a one-stop-shop for the researchers in this area to, i) find all the relevant information, and ii) identify the future research directions. To fill these research challenges, this paper provides a comprehensive survey on carpooling in autonomous and connected vehicles and covers architecture, components, and solutions, including scheduling, matching, mobility, pricing models of carpooling. We also discuss the current challenges in carpooling and identify future research directions. This survey is aimed to spur further discussion among the research community for the effective realization of carpooling.

show abstract

Section: Mobility In Carpoolingmentioning

confidence: 99%

Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In this model, the actual pick-up time should not be more than the maximum waiting time for riders at each car and bus station (constraints (4) and ( 5)). Constraint (6) shows that the total distance between the originating station and the destination station must be equal to or less than the product of the acceptable detour distance and the shortest distance between them. Constraint (7) cost of the trip must not exceed the maximum amount that the user can pay, while constraint (8) ensures that the time taken for the trip is less than the maximum time that the user wishes to be on the trip.…”

Section: Set Of Riders σmentioning

confidence: 99%

“…This model allows the user to use two modes of transportation on his trip from origin to destination. This work is an extension of our previous work [6], in which we developed a dynamic scheme that enables riders to use cars or public buses, either exclusively or in combination during their trip, for the lowest fare and quickest time. At each station, passengers can be informed of the capacity of the public bus or car that will pass through the station, and their recent positions.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

2021

Self Cite

View full text Add to dashboard Cite

This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level.

show abstract

“…The passenger p uses some strategies (preferences) to satisfy his goal. From Equation (11), the utility function of the passenger U p is evaluated by minimising the total price TP p and the total trip time TT p . From Equations ( 12) and ( 13), the utility function U b of the public bus b and the utility function U c of the car ride-sharing c are evaluated by maximising the number of passengers in both.…”

Section: T P P ⩽ P Max ð35þmentioning

confidence: 99%

“…Cycling helps to reduce the incidence of many health problems, such as obesity, while helping to maintain a healthy heart. Here [11], a new dynamic mobility scheme that integrates car ride‐sharing with the bus is modified.…”

Section: Introductionmentioning

confidence: 99%

Game theoretic approach for public multi‐mode transportation in smart cities

2021

Self Cite

View full text Add to dashboard Cite

Here, a dynamic multi-mode transportation model is developed in which the passenger, for his trip, can use one or a combination of the transportation forms such as a car, a bus or a bicycle. This model is based on the game theory concept-based trip costoptimization and it is called game theory multi-mode transportation. The proposed system is implemented through a realistic scenario in a specific city using the OMNET++ and the OpenStreetMap software tools. The results show that the average trip price and the average trip time are improved when using the proposed model.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Mobility Traffic Model Based on Combination of Multiple Transportation Forms in the Smart City

Cited by 4 publications

References 11 publications

Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

A Dynamic Mobility Traffic Model Based on Two Modes of Transport in Smart Cities

Game theoretic approach for public multi‐mode transportation in smart cities

Contact Info

Product

Resources

About