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The purpose of this study is to provide real-time route guidance within city to help commuters.

In urban areas to avoid road congestion and to reach the destination on time, intelligent transport system (ITS) utilizes recent advanced technology. To support this, existing route guidance system (RGS) suggests alternative route to commuters. However, ITS requires a system which suggests the alternative route along with the mode of transport such as public, private, taxi services etc. Integrated mode of transport (IMT) implemented in this paper guides the commuters of urban area with the best mode of transport. Inputs to our IMT predictive model are the commuter's choice of (1) minimum travel time (2) minimum cost (3) flexible route and (4) less traffic intensity along with source and destination locations. Based on these user inputs, IMT predictive model suggests optimal mode of transport. In this paper to implement the IMT model, we have considered the transport facility available in Bangalore, a city in India. The city has metro train, bus and taxi services available to the commuters. Implementation is divided into two parts. In the first part, the model checks for the end-to-end connectivity/availability of metro train facility. If metro train connectivity exists, the model concludes this as the best mode of travel. In the second part, for the routes which are not connected by metro train, the optimal mode of transport through road network will be suggested. In the first part, to check the existence of metro train along the routes between source and destination, location-IQ API is used. In the later part, to suggest transport along the road network, Q-learning algorithm of reinforcement learning technique is used.

The findings are the predictive model algorithm to find the best mode of transfer and reinforcement model used in real time route guidance system.

This is a new Idea, not proposed in any research work.

Studies about destination image have been discussed extensively in the literature due to its impact on tourist behavior. Despite the significant number of contributions, existing models are outdated in the context of globalization. This chapter synthesizes relevant literature and evaluates the effects of social media on destination image formation. Built on the seminal work by Gartner and that of Tasci and Gartner, the chapter extends the existing understanding with a conceptual model. The construct posits that, with the social media sites as the agent, an overall conative image of a destination can be formed by the overlap of provision and evaluation of cognitive and affective information by and among suppliers, consumers, and third parties.

The importance of the adverse impacts of network degradation has stimulated substantial international research interest in transport network reliability, that is, the ability of degraded transport networks to cope with travel demand. Most of the recent research effort has focused on the reliability of urban passenger transport networks, in terms of the probability that the network will deliver a required standard of performance. This situation is characterised by high levels of congestion, a dense road network, and quantifiable probability of degradation of the network. Outside major urban centres, the situation is very different. The main dominant consideration in transport network infrastructure provision is accessibility - linking urban centres, providing regional coverage, and basic levels of accessibility for the non-urban community and economy. The network is sparse, congestion is not a significant issue, and access to essential community services and to markets is the major driving force underlying network development. In this context, the vulnerability of the network is perhaps more important than ‘reliability’. This paper develops the concept of network vulnerability. It begins by reviewing the current state of research into network reliability, then proposes extensions and adaptations to the reliability concepts that are more appropriate for strategic-level multi-modal transport systems. Several alternative definitions for vulnerability are proposed. The paper also discusses the development of algorithmic and visualisation tools that may be used to identify specific ‘weak spots’ in a network, where failure of some part of the transport infrastructure would have the most serious effects on access to specific locations and on overall system performance. Finally, the paper describes potential applications of network vulnerability concepts, and proposes directions for further research.

This paper attempts to assess the parking reliability with taking into account drivers' travel choice behaviors under various traffic conditions. Apart from the well-known travel-time reliability, a parking reliability is newly defined as the probability that the drivers' average searching time for parking is less than a given threshold. This is particularly important under conditions of shortage of parking spaces in urban areas. A Monte Carlo simulation approach, which incorporates a combined trip distribution and assignment model with explicit elastic demand function, is proposed to estimate the two reliability measures of road network (i.e. travel-time and parking reliabilities). A numerical example is used to illustrate the applications of the reliability measures and the proposed approach.

With the demographic increase, especially in big cities, heavy traffic, traffic congestion, road accidents and augmented pollution levels hamper transportation networks. Finding the optimal routes in urban scenarios is very challenging since it should consider reducing traffic jams, optimizing travel time, decreasing fuel consumption and reducing pollution levels accordingly. In this regard, the authors propose an enhanced approach based on the Ant Colony algorithm that allows vehicle drivers to search for optimal routes in urban areas from different perspectives, such as shortness and rapidness.

An improved ant colony algorithm (ACO) is used to calculate the optimal routes in an urban road network by adopting an elitism strategy, a random search approach and a flexible pheromone deposit-evaporate mechanism. In addition, the authors make a trade-off between route length, travel time and congestion level.

Experimental tests show that the routes found using the proposed algorithm improved the quality of the results by 30% in comparison with the ACO algorithm. In addition, the authors maintain a level of accuracy between 0.9 and 0.95. Therefore, the overall cost of the found solutions decreased from 67 to 40. In addition, the experimental results demonstrate that the authors’ improved algorithm outperforms not only the original ACO algorithm but also popular meta-heuristic algorithms such as the genetic algorithm (GA) and particle swarm optimization (PSO) in terms of reducing travel costs and improving overall fitness value.

The proposed improvements to the ACO to search for optimal paths for urban roads include incorporating multiple factors, such as travel length, time and congestion level, into the route selection process. Furthermore, random search, elitism strategy and flexible pheromone updating rules are proposed to consider the dynamic changes in road network conditions and make the proposed approach more relevant and effective. These enhancements contribute to the originality of the authors’ work, and they have the potential to advance the field of traffic routing.

This paper is an attempt to bridge the gap between, on the one hand, the mobility behaviour of households and their perception of accessibility to urban amenities and, on the other hand, house price dynamics as captured through hedonic modelling.

In order to analyse the mobility behaviour of individuals and households, their sensitivity to travel time from home to service places is estimated so as to assess their perceived accessibility, using “subjective” indices based on actual trips, as reported in the 2001 origin‐destination survey designed for Quebec City. For comparative purposes, both objective and subjective accessibility indices based, in the former case on observed travel times and, in the latter case on fuzzy logic criteria, are computed and used as a complement to a centrality index in a hedonic model of house prices.

Findings indicate that there are statistically significant differences in the way accessibility is structured depending on trip purposes and household profiles. They also suggest that, while an objective measure of accessibility yields good results, resorting to subjective, and more comprehensive, accessibility indices derived from fuzzy logic provides greater insight into the understanding of commuting patterns and travel behaviour of people.

Better understanding the complexity of individuals’ and households’ mobility behaviour should result in more adequate initiatives and decisions being taken by transportation and city planning authorities.

Accessibility to jobs and services has long been known as a major determinant of urban, residential and non residential, rents. Yet, it is more often than not assumed to derive from a rather straightforward process, which this paper shows is not the case.

Purpose – The objective of this chapter is to draw the attention of policy makers in the fields of urban planning and transport in China to the importance of developing more balanced multi-modal transport systems and the corresponding land-use patterns to support transport systems, particularly walking and cycling in order to address the issues arising from the dense, highly mixed land-use pattern in many Chinese cities. This will help to reverse current planning practices which give car-oriented development top priority and less consideration of walking and cycling.

Methodology – Statistical methods have been applied to analyse modal split in some cities in Japan, Beijing and Shanghai using travel surveys, plus analysis of the experience of policies in various cities around the world, especially in terms of the relationship between the modal shares for public transport and car. Door-to-door travel times have been analysed for Shanghai to understand the potential of cycle or e-bicycle in a dense urban environment.

Findings – The change in travel modal split in Beijing in recent years suggests that simply encouraging public transport cannot control use of car. The data from Japan also shows that normal bus services cannot compete with the car, but it is clear that people will travel less by car if there is a high non-motorized share in the city. Because of the low density of the metro network, the door-to-door travel speed by metro is not as fast as is often imagined, due to the long off-metro time. The people who use metro are often not the people who live very close to metro stations, but some distance away, so improving the connection to the station by cycle or e-bicycle could greatly reduce the total travel time by metro.

Research limitations and implications – More analyses should be conducted in medium-size and small-size cities in China, where the local capacity is low and there is great potential to travel by walking and cycling, but only after clear guidance and policy instruments have been provided by higher authorities.

Practical and social implications – There is still a relatively high share of non-motorized travel in China. Many cities still have extensive cycle infrastructure established under the State Code of Urban Road Transport Planning issued in 1995. Encouraging non-motorized transport systems is not only possible, but also good for the environment, and contributes to travel efficiency and social inclusion.

Originality – This chapter is the summary of several original research studies using primary survey data, encouraging public transport in China. This is the first research to show the great potential of non-motorized mode for controlling car use and improving urban mobility in China. It is also the first chapter to point out the integration of multi-modal transport systems with the corresponding built environment in China.