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This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Purpose – This chapter provides details of research that attempts to relate traffic operational conditions on uninterrupted flow facilities (e.g., freeways and expressways) with real-time crash likelihood. Unlike incident detection, the purpose of this line of work is to proactively assess crash likelihood and potentially reduce the likelihood through proactive traffic management techniques, including variable speed limit and ramp metering among others.

Methodology – The chapter distinguishes between the traditional aggregate crash frequency-based approach to safety evaluation and the approach needed for real-time crash risk estimation. Key references from the literature are summarised in terms of the reported effect of different traffic characteristics that can be derived in near real-time, including average speed, temporal variation in speed, volume and lane-occupancy, on crash occurrence.

Findings – Traffic and weather parameters are among the real-time crash-contributing factors. Among the most significant traffic parameters is speed particularly in the form of coefficient of variation of speed.

Research implications – In the traffic safety field, traditional data sources are infrastructure-based traffic detection systems. In the future, if automatic traffic detection systems could provide reliable data at the vehicle level, new variables such as headway could be introduced. Transferability of real-time crash prediction models is also of interest. Also, the potential effects of different management strategies to reduce real-time crash risk could be evaluated in a simulation environment.

Practical implications – This line of research has been at the forefront of bringing data mining and other machine-learning techniques into the traffic management arena. We expect these analysis techniques to play a more important role in real-time traffic management, not just for safety evaluation but also for congestion pricing and alternate routing.

Purpose – This chapter reviews planning and design approaches for cycle traffic in order to direct future thinking towards the critical aspects of network design that will have a beneficial impact on the utility and nature of the environment for cycling.

Approach – This chapter provides a critique of the approach of adopting a so-called hierarchy of solutions frequently adopted in western countries with low levels of cycling use.

Findings – The guiding principle for designing routes for cycle traffic is that the bicycle is a vehicle capable of speed and, as a consequence, links and junctions need to be designed according to appropriate geometric design standards. In addition, owing to the nature of the cycle and rider combination, the oft repeated Dutch characteristics for good design for cycle traffic of coherence, directness, attractiveness, safety and comfort remain firm.

Practical implications – The practical implications of the outcomes from the chapter are a method of approach for planning infrastructure for cycle traffic which starts with an analysis of demand and works through to the creation of suitable networks for cycle traffic which are grounded in, and extended from, suitably regulated existing highway networks.

Social implications – An extensive transport system suitable in nature for cycle traffic will attract a wide base of users and consequently allow for the benefits of cycling to be captured.

Value of chapter – The value of the chapter rests in its emphasis on the need to treat cycling as a distinct transport mode and, consequentially, planning and engineering needs to be undertaken in a way conducive to providing the basic necessary infrastructure for such a distinct mode.