Autonomous Vehicle Implementation Predictions - Implications for Transport Planning Summary

Many decision-makers and practitioners (planners, engineers and analysts) wonder how autonomous (also called self-driving or robotic) vehicles will affect future travel demands, and therefore the need for roads, parking facilities and public transit services, and what public policies can minimize their risks and maximize their benefits (APA 2016; Berrada and Leurent 2017; Grush and Niles 2018; Gue. [...] It investigates, based on experience with previous vehicle technologies, how quickly self-driving vehicles are likely to be developed and deployed, critically evaluates their benefits and costs, and discusses their likely travel impacts and their implications for planning decisions such as optimal road, parking and public transit supply. [...] They are likely to increase total vehicle travel and costs for autonomous vehicle owners, but reduce vehicle travel and costs for those who shift from owning to sharing vehicles and drive less than about 6,000 annual vehicle-miles. [...] For example, to increase travel speeds autonomous vehicles can be programmed to take more risks and shortcuts through neighborhoods, to minimize traffic problems they can be programmed to drive slower and avoid congested roads and neighborhood streets. [...] On the other hand, by providing more efficient and affordable public transit and taxi services, improving walking and bicycling conditions, and reducing parking needs, shared autonomous vehicles may encourage vehicle sharing and urban environments.