The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.

This paper presents a carbon efficient transport management system that uses agent-based technology to simulate the existing transport infrastructure of a city. By utilizing realtime information about the current use of transport infrastructure from different data sources (e.g. road-side sensors) the system is capable of providing guidance to everyday commuters. The guidance is primarily in the form of multi-mode route suggestions with the aim of reducing overall carbon-dioxide emissions. This paper describes the architecture of the transport management system along with the design details of multi-agent system. The initial results of the simulations validate the feasibility of the multi-agent system in providing carbon-efficient transport management for an urban city.

Road traffic information has been a primary source for traffic management, user services and other systems that enable road congestion prevention and control; however, road traffic information has not been adequately exploited as a part of the design for wireless communication network. In vehicular ad-hoc networks, the protocol design must consider the dynamic nature of the topology and the probability of available alternate routes for wireless routing. The information provided by either the road itself or the activities on the road can help to void common issues such as broadcast storms, hidden node problems and lost data caused by an increase in road traffic density or sparse road traffic respectively. Routing protocols must therefore be able to dynamically adjust to the current road traffic information. In order to improve message delivery in vehicular ad-hoc networks, this project proposes a collaborative process of utilizing real time road traffic information and route knowledge to enhance routing decisions in order to maximize packet delivery ratio and reduce delays in transmission.